example_id int64 0 10k | metadata stringlengths 679 723 | classification_prompt stringlengths 4.51k 10.9k | classification_completion stringclasses 14 values | classification_text stringlengths 4.52k 11k | improved_signature stringlengths 2.44k 4.91k | improved_model_weights stringlengths 1.76k 5.03k | training_metrics stringlengths 1.46k 2.92k |
|---|---|---|---|---|---|---|---|
0 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.4, "improved_accuracy": 0.96, "improvement": 0.5599999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9016, "learning_rate": 0.08961895813761998, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.bias": [
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}
## Activation Signature
### 0
fourier: [[34.383204, 40.171638, 40.350547], [22.239335, 23.422166, 36.439215], [24.708134, 25.798288, 114.167165], [20.733268, 22.589542, 25.321610], [29.322260, 30.772489, 105.063039]]
### 2
fourier: [[26.983542, 30.706222, 156.896161], [35.392268, 36.604519, 145.906124], [12.166634, 14.244054, 74.879210], [18.401049, 19.357862, 81.456438], [30.354496, 31.899994, 150.638379]]
### 4
fourier: [[35.891962, 36.976226, 220.481959], [15.819824, 17.162933, 17.979557], [77.692332, 82.350491, 323.400358], [24.942405, 28.378738, 83.535603], [36.321304, 38.649625, 108.816051]]
### 6
fourier: [[17.765842, 18.558664, 43.137447], [27.580222, 28.680641, 78.077336], [72.635444, 73.128317, 320.971643], [41.956065, 43.070383, 105.774383], [20.534104, 21.408613, 95.924661]]
### 8
fourier: [[15.930071, 16.214262, 87.811183], [11.719948, 12.111654, 45.786713], [54.680187, 55.868834, 201.421832], [16.249771, 17.039159, 89.088282], [59.223098, 61.473636, 227.025592]]
### 10
fourier: [[76.864729, 78.751975, 300.674100]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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"network.10.bias": [
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}
## Activation Signature
### 0
fourier: [[34.383204, 40.171638, 40.350547], [22.239335, 23.422166, 36.439215], [24.708134, 25.798288, 114.167165], [20.733268, 22.589542, 25.321610], [29.322260, 30.772489, 105.063039]]
### 2
fourier: [[26.983542, 30.706222, 156.896161], [35.392268, 36.604519, 145.906124], [12.166634, 14.244054, 74.879210], [18.401049, 19.357862, 81.456438], [30.354496, 31.899994, 150.638379]]
### 4
fourier: [[35.891962, 36.976226, 220.481959], [15.819824, 17.162933, 17.979557], [77.692332, 82.350491, 323.400358], [24.942405, 28.378738, 83.535603], [36.321304, 38.649625, 108.816051]]
### 6
fourier: [[17.765842, 18.558664, 43.137447], [27.580222, 28.680641, 78.077336], [72.635444, 73.128317, 320.971643], [41.956065, 43.070383, 105.774383], [20.534104, 21.408613, 95.924661]]
### 8
fourier: [[15.930071, 16.214262, 87.811183], [11.719948, 12.111654, 45.786713], [54.680187, 55.868834, 201.421832], [16.249771, 17.039159, 89.088282], [59.223098, 61.473636, 227.025592]]
### 10
fourier: [[76.864729, 78.751975, 300.674100]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [34.38320379607026, 40.171638428931615, 40.35054685021329]}, "1": {"fourier": [22.239334893166323, 23.422165914417118, 36.439215302467346]}, "2": {"fourier": [24.708134034066976, 25.798288262531763, 114.1671646386385]}, "3": {"fourier": [20.733267764821008, 22.589542105793953, 25.321610129533948]}, "4": {"fourier": [29.32226049742522, 30.77248937422029, 105.06303949654102]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [26.983542456877764, 30.706222016143478, 156.8961609452963]}, "1": {"fourier": [35.392268467454066, 36.60451876552779, 145.90612418949604]}, "2": {"fourier": [12.16663405960166, 14.244054244718246, 74.87920969724655]}, "3": {"fourier": [18.401048568854097, 19.35786244553081, 81.45643821358681]}, "4": {"fourier": [30.35449610410125, 31.89999351256122, 150.63837936520576]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [35.89196153555125, 36.97622649102833, 220.48195853829384]}, "1": {"fourier": [15.819823590633568, 17.16293277608725, 17.979556851089]}, "2": {"fourier": [77.69233215881653, 82.35049057326738, 323.40035815536976]}, "3": {"fourier": [24.9424050654011, 28.37873771312005, 83.53560316562653]}, "4": {"fourier": [36.321303874414944, 38.64962513482666, 108.8160510957241]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [17.765841511260682, 18.55866378065493, 43.137447372078896]}, "1": {"fourier": [27.58022228954291, 28.680640880817172, 78.07733555138111]}, "2": {"fourier": [72.63544416145571, 73.12831693209445, 320.9716428425163]}, "3": {"fourier": [41.95606462020902, 43.07038306629363, 105.77438279986382]}, "4": {"fourier": [20.534104444125308, 21.4086128303517, 95.92466147989035]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [15.930070809228903, 16.214261714513444, 87.81118267774582]}, "1": {"fourier": [11.719947855432828, 12.111653666811062, 45.78671268187463]}, "2": {"fourier": [54.68018739708468, 55.868833800578486, 201.42183224856853]}, "3": {"fourier": [16.249771396118632, 17.03915850581894, 89.0882818698883]}, "4": {"fourier": [59.22309793909146, 61.47363577980473, 227.02559154108167]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [76.8647285612855, 78.75197521340966, 300.6741001754999]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.135936, -0.898229, 0.440865, 0.123276, 0.184175], [-0.163952, -0.131368, -0.137423, -0.442275, 0.483762], [0.553204, 0.234059, 0.012346, -0.007213, 0.122724], [-0.328835, -0.385777, 0.280825, 0.310734, 0.156388], [-0.605177, 0.107524, 0.407967, 0.51625, 0.077238]], "network.0.bias": [0.510683, 0.677385, -0.008098, -0.082661, -0.329981], "network.2.weight": [[0.705301, 0.539599, -0.01023, 0.021263, 0.746458], [0.717342, 0.678719, -0.404586, 0.562974, 0.579811], [-0.511617, 0.060623, -0.159728, -0.452444, 0.218445], [-0.448086, -0.305107, 0.722371, 0.410896, -0.181677], [0.578319, 0.256954, -0.120081, 0.68794, 0.484082]], "network.2.bias": [0.131479, 0.382182, -0.381269, 0.463524, 0.364235], "network.4.weight": 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0.96}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.19858575612306595, "train_acc": 0.955, "val_loss": 0.20985378324985504, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.18956772983074188, "train_acc": 0.945, "val_loss": 0.21755105257034302, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.18157478421926498, "train_acc": 0.94, "val_loss": 0.20880016684532166, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.16584746539592743, "train_acc": 0.95, "val_loss": 0.204482764005661, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.16199803352355957, "train_acc": 0.95, "val_loss": 0.20969551801681519, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.26545940339565277, "train_acc": 0.945, "val_loss": 0.2017844319343567, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.203144408762455, "train_acc": 0.935, "val_loss": 0.20167064666748047, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6844655871391296, "final_val_loss": 0.5125601887702942, "initial_val_acc": 0.4, "final_val_acc": 0.4, "best_val_acc": 0.4}, "improved_stage": {"initial_val_loss": 0.35677871108055115, "final_val_loss": 0.20167064666748047, "initial_val_acc": 0.96, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 2}, "improvement": 0.5599999999999999, "first_improvement_epoch": 1}} |
1 | {"target_pattern": "palindrome", "degraded_accuracy": 0.54, "improved_accuracy": 0.92, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2679, "learning_rate": 0.03008896643339405, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[14.851885, 15.327329, 15.898825], [22.963743, 24.609837, 27.696848], [30.389728, 33.531173, 185.286600], [32.807046, 37.212072, 39.117923], [36.152803, 39.965163, 160.065606], [39.580665, 45.616853, 170.198236], [18.561104, 19.326078, 169.451684]]
### 2
fourier: [[50.933050, 54.518762, 213.488830], [40.851182, 47.725220, 200.940555], [42.676696, 49.175564, 192.379577], [35.210211, 40.682903, 162.006271], [23.396689, 24.007300, 69.851260], [25.102777, 28.823359, 155.948633], [17.049347, 20.196609, 115.573141]]
### 4
fourier: [[19.512372, 23.046826, 98.468363], [14.483058, 14.902334, 94.586165], [103.851358, 121.791820, 475.080219], [16.478766, 18.233073, 81.628709], [8.240283, 8.501608, 9.434308], [74.428500, 86.453561, 323.536141], [1.513779, 1.618856, 45.209161]]
### 6
fourier: [[7.378812, 8.278544, 29.386429], [3.512162, 3.948875, 9.145049], [78.298544, 91.419672, 318.625046], [4.976697, 5.413555, 60.739369], [95.236097, 111.486453, 406.113464], [16.475660, 19.540613, 84.174327], [90.982567, 106.092227, 391.402461]]
### 8
fourier: [[6.356748, 6.493128, 99.974771], [55.181087, 63.533879, 122.318207], [107.653094, 124.884235, 445.411970], [106.372113, 122.459073, 405.089285], [52.408559, 60.756234, 297.236286], [9.602522, 11.166172, 95.869932], [145.392408, 167.834821, 572.534210]]
### 10
fourier: [[3.643212, 4.552472, 185.224415], [6.058853, 7.186650, 118.839482], [29.546753, 34.344121, 94.362722], [26.827730, 30.631902, 183.399550], [80.014948, 91.000631, 305.071365], [233.389950, 267.093946, 891.038268], [54.407988, 62.475707, 252.889593]]
### 12
fourier: [[107.488760, 121.710483, 273.642032]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
0.234134,
0.202157,
0.072488,
0.758658,
-0.239738,
-0.073941,
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],
[
-0.119979,
0.229057,
0.041364,
-0.056458,
0.456891,
0.141302,
0.661115
],
[
-0.45526,
0.246762,
0.468704,
-0.490493,
0.440737,
-0.035569,
0.250425
],
[
0.012547,
-0.353709,
0.467767,
0.461303,
0.026767,
0.127998,
0.179996
],
[
-0.273539,
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-0.065876,
-0.423594,
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-0.369635,
0.282022
],
[
-0.419075,
-0.026043,
0.342473,
-0.738104,
0.623695,
-0.22199,
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]
],
"network.8.bias": [
0.569178,
0.462256,
-0.107848,
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0.399048,
-0.061277,
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],
"network.10.weight": [
[
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[
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[
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[
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],
"network.10.bias": [
0.43289,
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"network.12.weight": [
[
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],
"network.12.bias": [
0.036335
]
}
## Activation Signature
### 0
fourier: [[14.851885, 15.327329, 15.898825], [22.963743, 24.609837, 27.696848], [30.389728, 33.531173, 185.286600], [32.807046, 37.212072, 39.117923], [36.152803, 39.965163, 160.065606], [39.580665, 45.616853, 170.198236], [18.561104, 19.326078, 169.451684]]
### 2
fourier: [[50.933050, 54.518762, 213.488830], [40.851182, 47.725220, 200.940555], [42.676696, 49.175564, 192.379577], [35.210211, 40.682903, 162.006271], [23.396689, 24.007300, 69.851260], [25.102777, 28.823359, 155.948633], [17.049347, 20.196609, 115.573141]]
### 4
fourier: [[19.512372, 23.046826, 98.468363], [14.483058, 14.902334, 94.586165], [103.851358, 121.791820, 475.080219], [16.478766, 18.233073, 81.628709], [8.240283, 8.501608, 9.434308], [74.428500, 86.453561, 323.536141], [1.513779, 1.618856, 45.209161]]
### 6
fourier: [[7.378812, 8.278544, 29.386429], [3.512162, 3.948875, 9.145049], [78.298544, 91.419672, 318.625046], [4.976697, 5.413555, 60.739369], [95.236097, 111.486453, 406.113464], [16.475660, 19.540613, 84.174327], [90.982567, 106.092227, 391.402461]]
### 8
fourier: [[6.356748, 6.493128, 99.974771], [55.181087, 63.533879, 122.318207], [107.653094, 124.884235, 445.411970], [106.372113, 122.459073, 405.089285], [52.408559, 60.756234, 297.236286], [9.602522, 11.166172, 95.869932], [145.392408, 167.834821, 572.534210]]
### 10
fourier: [[3.643212, 4.552472, 185.224415], [6.058853, 7.186650, 118.839482], [29.546753, 34.344121, 94.362722], [26.827730, 30.631902, 183.399550], [80.014948, 91.000631, 305.071365], [233.389950, 267.093946, 891.038268], [54.407988, 62.475707, 252.889593]]
### 12
fourier: [[107.488760, 121.710483, 273.642032]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [14.851885406020168, 15.327329002609316, 15.898824652225157]}, "1": {"fourier": [22.96374293503703, 24.609837488875996, 27.6968475576902]}, "2": {"fourier": [30.389728259886475, 33.531172914776825, 185.28660035133362]}, "3": {"fourier": [32.807046299186396, 37.21207223087549, 39.11792269988414]}, "4": {"fourier": [36.15280268766395, 39.96516331345573, 160.0656055212021]}, "5": {"fourier": [39.58066489988728, 45.61685277530159, 170.19823560863733]}, "6": {"fourier": [18.561103973846222, 19.326078348610004, 169.45168387889862]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [50.93305010006568, 54.51876177817782, 213.488829895854]}, "1": {"fourier": [40.85118164001332, 47.72522021223289, 200.94055522978306]}, "2": {"fourier": [42.67669610346202, 49.17556358954126, 192.37957678735256]}, "3": {"fourier": [35.210210796054625, 40.682903432995786, 162.00627110898495]}, "4": {"fourier": [23.396689267361165, 24.007299533275496, 69.85125966742635]}, "5": {"fourier": [25.102777015942838, 28.82335884070302, 155.94863265752792]}, "6": {"fourier": [17.04934708851315, 20.19660935715838, 115.57314118742943]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [19.512371568484436, 23.046826037144072, 98.46836313605309]}, "1": {"fourier": [14.483058042044041, 14.902334081404389, 94.58616533875465]}, "2": {"fourier": [103.85135784504725, 121.79182025104025, 475.08021853864193]}, "3": {"fourier": [16.478766174839627, 18.23307291502258, 81.62870880961418]}, "4": {"fourier": [8.24028301999672, 8.501608008472852, 9.434308263591216]}, "5": {"fourier": [74.42849952457631, 86.45356121108637, 323.5361412167549]}, "6": {"fourier": [1.5137793744554948, 1.6188555911615172, 45.20916086435318]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [7.378811936938766, 8.278544002045527, 29.38642869889736]}, "1": {"fourier": [3.5121617993878984, 3.9488748321707154, 9.145049139857292]}, "2": {"fourier": [78.2985440736462, 91.41967180621938, 318.6250456608832]}, "3": {"fourier": [4.976696974831775, 5.413555335928494, 60.739368945360184]}, "4": {"fourier": [95.23609677512123, 111.4864526385402, 406.1134640350938]}, "5": {"fourier": [16.475659938465938, 19.540613062296057, 84.17432655394077]}, "6": {"fourier": [90.98256738136965, 106.09222685777769, 391.4024610668421]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [6.356747508550272, 6.493127963923195, 99.9747708439827]}, "1": {"fourier": [55.18108741312582, 63.53387945166109, 122.3182065486908]}, "2": {"fourier": [107.65309378757155, 124.88423531278838, 445.411969602108]}, "3": {"fourier": [106.37211283382929, 122.45907295408236, 405.0892848819494]}, "4": {"fourier": [52.408558533948195, 60.75623392450584, 297.2362861633301]}, "5": {"fourier": [9.602521548213321, 11.166171886940397, 95.86993163824081]}, "6": {"fourier": [145.39240829984527, 167.8348212187903, 572.5342103093863]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [3.643212194906667, 4.552471656075601, 185.22441506385803]}, "1": {"fourier": [6.05885317444087, 7.18664997973918, 118.83948218822479]}, "2": {"fourier": [29.54675304636633, 34.344121428194875, 94.36272190511227]}, "3": {"fourier": [26.82772976841645, 30.631902115817855, 183.39955019950867]}, "4": {"fourier": [80.01494778583218, 91.00063090909461, 305.07136453688145]}, "5": {"fourier": [233.3899504994503, 267.09394591696304, 891.0382679700851]}, "6": {"fourier": [54.407987832949935, 62.47570705130021, 252.88959285616875]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [107.48875957181731, 121.71048258216115, 273.6420324742794]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.125469, -0.22807, 0.229685, -0.28477, -0.072223], [0.568673, 0.057374, 0.065451, -0.042699, -0.605954], [0.249031, 0.147676, -0.169346, 0.24949, 0.667312], [-0.473476, 0.076141, -0.093008, 0.431775, -0.657419], [0.285524, 0.080429, -0.115421, 0.182172, 0.817199], [0.710107, -0.189389, -0.079083, 0.344341, 0.633212], [-0.054273, 0.00614, -0.057302, -0.44436, -0.220286]], "network.0.bias": [0.630073, -0.127634, 0.475448, 0.116184, 0.119195, -0.001673, -0.482158], "network.2.weight": [[-0.087187, 0.164694, 0.272816, -0.290646, 0.700657, 0.387527, 0.074296], [-0.175392, 0.457536, 0.367264, -0.352358, 0.32458, 0.405885, 0.180145], [-0.441343, 0.498286, 0.104979, -0.315393, 0.280045, 0.671565, -0.284754], [-0.346153, 0.333924, 0.168156, -0.184189, 0.0652, 0.666748, -0.174136], [-0.439547, 0.320737, 0.052312, -0.403155, 0.419374, 0.059859, 0.06173], [-0.423469, 0.197154, -0.449059, -0.100629, -0.429938, 0.082728, 0.169577], [-0.321659, 0.162583, -0.454295, 0.152977, -0.27218, 0.194535, 0.182906]], "network.2.bias": [-0.086853, 0.152959, 0.249638, 0.141462, 0.060801, -0.03562, -0.241457], "network.4.weight": [[0.10578, 0.097875, 0.13872, 0.223178, -0.14328, 0.325529, 0.026482], [-0.337622, -0.177456, 0.212671, -0.053248, 0.166839, -0.01583, 0.009006], [0.552865, 0.556139, 0.756597, 0.520099, 0.321702, -0.178331, 0.051394], [-0.297142, -0.071886, 0.257613, -0.342738, 0.116841, 0.251029, -0.236805], [0.363105, 0.008424, -0.640911, 0.19778, -0.199553, -0.127511, -0.422148], [0.444967, 0.531354, 0.466258, 0.04871, 0.544862, -0.139811, 0.010258], [-0.201225, 0.286734, 0.031337, -0.141088, 0.057019, -0.289465, -0.06515]], "network.4.bias": [0.044227, -0.357857, -0.138158, -0.072947, 0.251627, -0.222342, 0.479936], "network.6.weight": [[0.314783, -0.360857, -0.099691, 0.151684, 0.453793, -0.028933, 0.596061], [0.078682, 0.200224, -0.07585, -0.367313, -0.461652, 0.117345, 0.218022], [0.314368, -0.075892, 0.268086, -0.115635, -0.433748, 0.588586, -0.713785], [-0.026679, 0.048687, -0.017516, -0.258455, 0.343984, -0.023492, 0.16277], [-0.026475, -0.220489, 0.733669, 0.302964, -0.129162, 0.261333, -0.39972], [-0.444032, 0.362949, 0.056518, -0.321557, -0.393488, -0.196118, 0.133509], [0.40012, -0.193117, 0.380514, -0.366282, -0.367698, 0.578967, -0.404105]], "network.6.bias": [0.254125, -0.259396, 0.068044, 0.754287, -0.062867, -0.054344, 0.059135], "network.8.weight": [[0.480701, -0.341995, -0.032437, 0.552938, -0.058583, 0.066752, 0.086191], [0.234134, 0.202157, 0.072488, 0.758658, -0.239738, -0.073941, -0.365062], [-0.119979, 0.229057, 0.041364, -0.056458, 0.456891, 0.141302, 0.661115], [-0.45526, 0.246762, 0.468704, -0.490493, 0.440737, -0.035569, 0.250425], [0.012547, -0.353709, 0.467767, 0.461303, 0.026767, 0.127998, 0.179996], [-0.273539, 0.222246, -0.065876, -0.423594, -0.354655, -0.369635, 0.282022], [-0.419075, -0.026043, 0.342473, -0.738104, 0.623695, -0.22199, 0.590027]], "network.8.bias": [0.569178, 0.462256, -0.107848, 0.199125, 0.399048, -0.061277, 0.354973], "network.10.weight": [[0.524196, 0.549181, 0.120931, -0.367401, 0.396959, 0.027463, 0.08965], [0.553386, -0.089661, 0.176877, 0.164919, 0.20124, -0.222673, -0.266719], [-0.180499, -0.178738, 0.356455, 0.214917, 0.202369, 0.336856, -0.307676], [-0.320524, -0.251655, 0.051755, 0.293225, -0.301818, -0.179426, -0.354398], [0.289126, 0.037438, -0.037894, -0.261906, -0.0301, -0.10259, -0.309351], [-0.477042, -0.58939, 0.609604, 0.60943, 0.187873, 0.154253, 0.597694], [-0.059992, 0.173675, -0.034314, -0.019777, -0.17461, 0.374467, -0.26644]], "network.10.bias": [0.43289, 0.165043, -0.118111, 0.111755, -0.21986, 0.331246, -0.252966], "network.12.weight": [[0.567076, 0.45531, -0.180927, 0.052572, 0.105219, -0.457545, -0.010897]], "network.12.bias": [0.036335]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6893084645271301, "train_acc": 0.565, "val_loss": 0.6865367293357849, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6810666918754578, "train_acc": 0.565, "val_loss": 0.6784811615943909, "val_acc": 0.54}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6685593724250793, "train_acc": 0.565, "val_loss": 0.6517688035964966, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6524258255958557, "train_acc": 0.49, "val_loss": 0.569166898727417, "val_acc": 0.54}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.568692147731781, "train_acc": 0.64, "val_loss": 0.46440890431404114, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.46779032051563263, "train_acc": 0.825, "val_loss": 0.355616956949234, "val_acc": 0.84}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.3691777288913727, "train_acc": 0.86, "val_loss": 0.311698317527771, "val_acc": 0.86}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.3332885801792145, "train_acc": 0.875, "val_loss": 0.22795723378658295, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.26788821816444397, "train_acc": 0.89, "val_loss": 0.2353765070438385, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3176712542772293, "train_acc": 0.885, "val_loss": 0.32308822870254517, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.32575756311416626, "train_acc": 0.83, "val_loss": 0.1803550273180008, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.3036663830280304, "train_acc": 0.885, "val_loss": 0.18534092605113983, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.2714708149433136, "train_acc": 0.895, "val_loss": 0.21064597368240356, "val_acc": 0.92}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6865367293357849, "final_val_loss": 0.6517688035964966, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.569166898727417, "final_val_loss": 0.21064597368240356, "initial_val_acc": 0.54, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 7}, "improvement": 0.38, "first_improvement_epoch": 2}} |
2 | {"target_pattern": "alternating", "degraded_accuracy": 0.52, "improved_accuracy": 0.86, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9451, "learning_rate": 0.07352170370310572, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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"network.2.weight": [
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}
## Activation Signature
### 0
fourier: [[25.244357, 25.272165, 69.597547], [48.968251, 51.870678, 261.766865], [30.022897, 32.905340, 32.935295], [48.427342, 52.840009, 54.680328], [40.043085, 40.993936, 293.984221], [26.338300, 27.985484, 104.897283], [55.837392, 63.117938, 281.585477]]
### 2
fourier: [[18.521589, 19.276363, 50.356526], [19.394233, 20.147705, 22.035089], [17.851729, 19.620269, 91.940210], [40.485911, 43.096359, 198.776936], [19.487518, 19.579427, 24.509010], [29.038945, 30.751904, 138.947095], [16.295723, 16.650091, 26.103504]]
### 4
fourier: [[39.249205, 41.083122, 134.435886], [48.723950, 53.753581, 147.284509], [47.586959, 51.904086, 147.524885], [17.554351, 17.686233, 19.492713], [11.808143, 12.752008, 115.478164], [18.675900, 19.078702, 39.867086], [33.240452, 36.661944, 229.742472]]
### 6
fourier: [[37.675401, 38.083815, 136.105376], [54.960334, 60.429346, 245.158862], [12.745414, 12.970052, 23.714065], [45.479666, 46.168844, 208.873761], [35.447406, 38.049398, 123.179521], [19.115612, 19.433337, 68.582013], [63.694788, 70.311100, 317.901670]]
### 8
fourier: [[37.371955, 39.677794, 189.993346], [64.609793, 71.337862, 277.435309], [59.256032, 63.874632, 216.409304], [118.816062, 128.795860, 527.065263], [61.709469, 67.579969, 219.202833], [50.689166, 55.633455, 159.592305], [84.150578, 90.854217, 350.660369]]
### 10
fourier: [[94.997292, 105.683004, 292.246114]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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]
}
## Activation Signature
### 0
fourier: [[25.244357, 25.272165, 69.597547], [48.968251, 51.870678, 261.766865], [30.022897, 32.905340, 32.935295], [48.427342, 52.840009, 54.680328], [40.043085, 40.993936, 293.984221], [26.338300, 27.985484, 104.897283], [55.837392, 63.117938, 281.585477]]
### 2
fourier: [[18.521589, 19.276363, 50.356526], [19.394233, 20.147705, 22.035089], [17.851729, 19.620269, 91.940210], [40.485911, 43.096359, 198.776936], [19.487518, 19.579427, 24.509010], [29.038945, 30.751904, 138.947095], [16.295723, 16.650091, 26.103504]]
### 4
fourier: [[39.249205, 41.083122, 134.435886], [48.723950, 53.753581, 147.284509], [47.586959, 51.904086, 147.524885], [17.554351, 17.686233, 19.492713], [11.808143, 12.752008, 115.478164], [18.675900, 19.078702, 39.867086], [33.240452, 36.661944, 229.742472]]
### 6
fourier: [[37.675401, 38.083815, 136.105376], [54.960334, 60.429346, 245.158862], [12.745414, 12.970052, 23.714065], [45.479666, 46.168844, 208.873761], [35.447406, 38.049398, 123.179521], [19.115612, 19.433337, 68.582013], [63.694788, 70.311100, 317.901670]]
### 8
fourier: [[37.371955, 39.677794, 189.993346], [64.609793, 71.337862, 277.435309], [59.256032, 63.874632, 216.409304], [118.816062, 128.795860, 527.065263], [61.709469, 67.579969, 219.202833], [50.689166, 55.633455, 159.592305], [84.150578, 90.854217, 350.660369]]
### 10
fourier: [[94.997292, 105.683004, 292.246114]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.244357064938395, 25.272165219150512, 69.59754720330238]}, "1": {"fourier": [48.9682509831439, 51.870677516907044, 261.766864720732]}, "2": {"fourier": [30.022897412038205, 32.90533997602122, 32.93529503047466]}, "3": {"fourier": [48.42734209241126, 52.84000857941661, 54.6803275735822]}, "4": {"fourier": [40.04308502649903, 40.9939355408848, 293.98422111570835]}, "5": {"fourier": [26.338300214048274, 27.985483861109625, 104.89728327095509]}, "6": {"fourier": [55.83739192132204, 63.11793834628959, 281.58547699451447]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [18.521589227751786, 19.276363074645158, 50.35652565956116]}, "1": {"fourier": [19.394232771600162, 20.147705175842603, 22.035089133860694]}, "2": {"fourier": [17.85172878903702, 19.620268991875896, 91.94020974636078]}, "3": {"fourier": [40.48591137302813, 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"val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.2488829791545868, "train_acc": 0.915, "val_loss": 0.5403603315353394, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.24245692789554596, "train_acc": 0.93, "val_loss": 0.4776495099067688, "val_acc": 0.86}], "summary": {"total_epochs": 7, "degraded_epochs": 2, "improved_epochs": 5, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.6948902606964111, "final_val_loss": 0.6221851110458374, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.46326887607574463, "final_val_loss": 0.4776495099067688, "initial_val_acc": 0.82, "final_val_acc": 0.86, "best_val_acc": 0.86, "best_epoch": 6}, "improvement": 0.33999999999999997, "first_improvement_epoch": 1}} |
3 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.9, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7902, "learning_rate": 0.019119242316001303, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[19.862496, 20.830531, 23.455965], [29.712725, 31.584885, 209.921728], [19.809704, 24.477208, 56.491790], [24.325519, 28.552861, 31.141662], [14.279831, 14.689653, 17.131972], [31.136291, 34.110272, 236.940058]]
### 2
fourier: [[9.745191, 9.929557, 82.387070], [12.619947, 13.233478, 94.839780], [13.122304, 14.454589, 15.650824], [6.903355, 7.369968, 16.468549], [9.535084, 9.806261, 91.145412], [14.965161, 15.037413, 74.762907]]
### 4
fourier: [[5.158812, 5.856387, 60.326506], [3.188784, 3.624030, 23.633399], [1.688623, 2.290111, 7.728030], [4.073637, 4.140504, 43.246370], [2.257040, 2.810492, 23.866414], [4.303764, 4.712712, 58.447111]]
### 6
fourier: [[5.606738, 6.359093, 83.880835], [3.324797, 3.968807, 31.967752], [2.081108, 2.471892, 23.352558], [4.720023, 5.318862, 79.813636], [0.233760, 0.261278, 2.982098], [4.487900, 4.923892, 68.209054]]
### 8
fourier: [[6.836366, 7.788530, 70.304173]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[19.862496, 20.830531, 23.455965], [29.712725, 31.584885, 209.921728], [19.809704, 24.477208, 56.491790], [24.325519, 28.552861, 31.141662], [14.279831, 14.689653, 17.131972], [31.136291, 34.110272, 236.940058]]
### 2
fourier: [[9.745191, 9.929557, 82.387070], [12.619947, 13.233478, 94.839780], [13.122304, 14.454589, 15.650824], [6.903355, 7.369968, 16.468549], [9.535084, 9.806261, 91.145412], [14.965161, 15.037413, 74.762907]]
### 4
fourier: [[5.158812, 5.856387, 60.326506], [3.188784, 3.624030, 23.633399], [1.688623, 2.290111, 7.728030], [4.073637, 4.140504, 43.246370], [2.257040, 2.810492, 23.866414], [4.303764, 4.712712, 58.447111]]
### 6
fourier: [[5.606738, 6.359093, 83.880835], [3.324797, 3.968807, 31.967752], [2.081108, 2.471892, 23.352558], [4.720023, 5.318862, 79.813636], [0.233760, 0.261278, 2.982098], [4.487900, 4.923892, 68.209054]]
### 8
fourier: [[6.836366, 7.788530, 70.304173]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.862496341990465, 20.830531205643247, 23.455964750442998]}, "1": {"fourier": [29.712725321245426, 31.584885187962293, 209.921728387475]}, "2": {"fourier": [19.809703701121816, 24.477207544049705, 56.49178962409496]}, "3": {"fourier": [24.32551949189835, 28.552861332166607, 31.14166227207478]}, "4": {"fourier": [14.279830885156663, 14.68965345871899, 17.1319721534859]}, "5": {"fourier": [31.136290711930258, 34.11027155000762, 236.94005820155144]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [9.745190527610298, 9.929556625790516, 82.38706992566586]}, "1": {"fourier": [12.61994737826265, 13.233477836810962, 94.83977988362312]}, "2": {"fourier": [13.122304276839248, 14.454588573889383, 15.650823926708854]}, "3": {"fourier": [6.903354595228121, 7.369967934524945, 16.468548573553562]}, "4": {"fourier": [9.535083748666587, 9.806261003419548, 91.14541153609753]}, "5": {"fourier": [14.965161305190763, 15.037413277237276, 74.76290714740753]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [5.158811801971683, 5.856386962219855, 60.32650563120842]}, "1": {"fourier": [3.1887840447338505, 3.624029569712434, 23.633399114012718]}, "2": {"fourier": [1.6886234188619673, 2.2901106814488355, 7.728029906749725]}, "3": {"fourier": [4.073637328838318, 4.1405041450608175, 43.246370285749435]}, "4": {"fourier": [2.257039626267557, 2.810491875959659, 23.86641366034746]}, "5": {"fourier": [4.303764085341598, 4.712711633767883, 58.447111159563065]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [5.606738163454502, 6.359093270389631, 83.88083507120609]}, "1": {"fourier": [3.324797332654858, 3.968807305387114, 31.967751752585173]}, "2": {"fourier": [2.0811077691742383, 2.471892257453908, 23.35255754739046]}, "3": {"fourier": [4.720022961085628, 5.318861896205335, 79.81363618373871]}, "4": {"fourier": [0.23375989508949832, 0.2612782926839001, 2.98209759965539]}, "5": {"fourier": [4.487900273981504, 4.923891626604455, 68.20905402302742]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [6.836365559188387, 7.788529974472033, 70.30417285859585]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.308248, -0.106554, 0.317253, -0.270284, -0.076717], [-0.130905, 0.026878, -0.542554, -0.487697, -0.206054], [0.471833, 0.197985, 0.03069, -0.204486, -0.204377], [0.484639, -0.258715, 0.389787, -0.268101, -0.179084], [-0.239469, 0.005306, 0.241567, 0.199968, -0.297911], [-0.124459, -0.071256, 0.220915, 0.475926, 0.67989]], "network.0.bias": [0.015848, 0.214772, 0.30621, -0.191614, -0.165518, 0.5968], "network.2.weight": [[0.124599, 0.234848, -0.195303, 0.261541, 0.003123, -0.308994], [-0.331412, -0.163493, -0.015405, 0.141672, 0.164427, -0.338402], [-0.152695, 0.130336, -0.279607, -0.304313, -0.423584, 0.210375], [-0.046642, -0.208845, -0.350994, 0.063696, -0.344599, 0.105945], [-0.061839, 0.247712, -0.11397, 0.288401, 0.019977, -0.297684], [0.247831, 0.008517, -0.154214, -0.222045, 0.341944, -0.378961]], "network.2.bias": [-0.156689, -0.139741, -0.119344, -0.130299, -0.273499, 0.151582], "network.4.weight": [[-0.538956, -0.301866, -0.561536, -0.02514, -0.404367, -0.497798], [0.105127, 0.135962, 0.193674, 0.376524, 0.19196, 0.610889], [-0.594477, -0.487278, -0.197287, 0.116766, -0.300355, -0.103628], [-0.399337, 0.121736, -0.379296, -0.21849, -0.182644, -0.129434], [-0.015705, 0.070121, 0.348506, -0.188676, 0.138639, 0.537886], [-0.367265, -0.227509, -0.19863, -0.593053, -0.541858, -0.457003]], "network.4.bias": [0.531708, -0.158666, -0.073632, 0.456872, -0.230031, 0.469603], "network.6.weight": [[0.329071, -0.498207, 0.332671, 0.230136, -0.532708, 0.643445], [-0.435571, 0.395488, -0.308415, 0.195936, 0.154233, -0.364883], [-0.366484, 0.229135, -0.296155, -0.021536, 0.117018, 0.027221], [0.616569, 0.111167, -0.118406, 0.187173, 0.158521, 0.615021], [0.078434, 0.394491, -0.053647, 0.212129, 0.345927, -0.016275], [0.320474, -0.345668, 0.0394, 0.497217, -0.655889, 0.190344]], "network.6.bias": [0.245959, 0.054373, -0.026117, 0.228214, -0.064169, 0.226606], "network.8.weight": [[-0.526297, 0.226127, 0.398418, -0.247134, 0.001141, -0.626907]], "network.8.bias": [0.255489]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7180013060569763, "train_acc": 0.425, "val_loss": 0.6934688091278076, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7019679844379425, "train_acc": 0.425, "val_loss": 0.6853039264678955, "val_acc": 0.68}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6843142807483673, "train_acc": 0.575, "val_loss": 0.6770879626274109, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6714287102222443, "train_acc": 0.575, "val_loss": 0.6651756763458252, "val_acc": 0.5}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6483409404754639, "train_acc": 0.575, "val_loss": 0.6376786828041077, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6328597962856293, "train_acc": 0.53, "val_loss": 0.5665894746780396, "val_acc": 0.84}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.572889506816864, "train_acc": 0.775, "val_loss": 0.49300551414489746, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5088239163160324, "train_acc": 0.835, "val_loss": 0.4252799153327942, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.4628315716981888, "train_acc": 0.83, "val_loss": 0.3757992684841156, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.37355081737041473, "train_acc": 0.85, "val_loss": 0.38032832741737366, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.36860182881355286, "train_acc": 0.85, "val_loss": 0.3454854488372803, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.3211270272731781, "train_acc": 0.86, "val_loss": 0.3219808340072632, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.3318009674549103, "train_acc": 0.85, "val_loss": 0.34785231947898865, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.35081204771995544, "train_acc": 0.865, "val_loss": 0.3642524778842926, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.3323000818490982, "train_acc": 0.87, "val_loss": 0.32225313782691956, "val_acc": 0.86}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6934688091278076, "final_val_loss": 0.6376786828041077, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5665894746780396, "final_val_loss": 0.32225313782691956, "initial_val_acc": 0.84, "final_val_acc": 0.86, "best_val_acc": 0.9, "best_epoch": 6}, "improvement": 0.4, "first_improvement_epoch": 4}} |
4 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.64, "improved_accuracy": 0.86, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9859, "learning_rate": 0.015384002471586396, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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],
[
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[
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[
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[
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],
"network.0.bias": [
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"network.2.weight": [
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],
[
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[
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[
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[
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],
"network.2.bias": [
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],
"network.4.weight": [
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[
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[
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[
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],
[
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]
],
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],
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[
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[
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[
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[
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],
"network.6.bias": [
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"network.8.weight": [
[
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0.333334,
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]
],
"network.8.bias": [
0.144534
]
}
## Activation Signature
### 0
fourier: [[25.760290, 26.184900, 86.412873], [24.915543, 26.225291, 178.722497], [29.024818, 32.599501, 168.503991], [26.189072, 31.088983, 55.384145], [28.173956, 31.290883, 33.072054]]
### 2
fourier: [[33.132748, 37.249733, 180.373191], [11.319644, 11.371465, 20.990937], [31.176552, 36.537869, 174.249795], [22.413155, 22.765480, 87.454885], [10.533273, 11.753672, 12.083696]]
### 4
fourier: [[2.233928, 2.459772, 39.998685], [5.398062, 6.225882, 54.781467], [46.001567, 51.758616, 243.401373], [36.525696, 41.272591, 193.938742], [43.110570, 47.962721, 222.843906]]
### 6
fourier: [[41.198592, 46.410542, 220.087933], [9.149944, 10.104752, 60.336608], [69.716113, 78.398193, 357.265496], [17.362365, 19.808017, 57.728613], [42.092502, 47.005391, 230.024288]]
### 8
fourier: [[49.617480, 55.886713, 239.003486]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.490115,
-0.014935,
0.309498,
0.129559,
-0.346239
],
[
-0.099157,
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-0.152816,
-0.473807,
-0.371314
],
[
0.770528,
0.127912,
-0.002052,
0.235109,
-0.385436
],
[
0.596325,
0.068987,
0.011688,
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0.164491
],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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],
[
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],
[
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],
[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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],
[
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],
[
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],
[
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],
[
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]
],
"network.4.bias": [
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0.007807
],
"network.6.weight": [
[
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],
[
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],
[
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],
[
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],
[
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]
],
"network.6.bias": [
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0.119937
],
"network.8.weight": [
[
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-0.629808,
0.333334,
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]
],
"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[25.760290, 26.184900, 86.412873], [24.915543, 26.225291, 178.722497], [29.024818, 32.599501, 168.503991], [26.189072, 31.088983, 55.384145], [28.173956, 31.290883, 33.072054]]
### 2
fourier: [[33.132748, 37.249733, 180.373191], [11.319644, 11.371465, 20.990937], [31.176552, 36.537869, 174.249795], [22.413155, 22.765480, 87.454885], [10.533273, 11.753672, 12.083696]]
### 4
fourier: [[2.233928, 2.459772, 39.998685], [5.398062, 6.225882, 54.781467], [46.001567, 51.758616, 243.401373], [36.525696, 41.272591, 193.938742], [43.110570, 47.962721, 222.843906]]
### 6
fourier: [[41.198592, 46.410542, 220.087933], [9.149944, 10.104752, 60.336608], [69.716113, 78.398193, 357.265496], [17.362365, 19.808017, 57.728613], [42.092502, 47.005391, 230.024288]]
### 8
fourier: [[49.617480, 55.886713, 239.003486]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.760289924081444, 26.184900339264573, 86.41287272423506]}, "1": {"fourier": [24.9155429796375, 26.225291385790893, 178.7224967032671]}, "2": {"fourier": [29.024818433880576, 32.599501199529016, 168.50399085879326]}, "3": {"fourier": [26.18907234782617, 31.088983077976433, 55.38414515554905]}, "4": {"fourier": [28.17395645681246, 31.290882909560285, 33.07205416707333]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [33.13274783767294, 37.249732673943505, 180.37319089472294]}, "1": {"fourier": [11.319643687297244, 11.371464855885709, 20.990936817601323]}, "2": {"fourier": [31.17655232524513, 36.53786908348092, 174.24979478865862]}, "3": {"fourier": [22.413154854779695, 22.76547957026484, 87.45488462969661]}, "4": {"fourier": [10.533272968519743, 11.753671697409393, 12.083695859486738]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [2.2339278490704366, 2.4597717044279785, 39.998685240745544]}, "1": {"fourier": [5.398062069113655, 6.225881874334993, 54.78146728873253]}, "2": {"fourier": [46.001567001784665, 51.758616291263, 243.40137268044055]}, "3": {"fourier": [36.52569615267115, 41.27259126044697, 193.93874222785234]}, "4": {"fourier": [43.110569557690305, 47.962720648690635, 222.84390626009554]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [41.198592146027835, 46.410541544521365, 220.08793264627457]}, "1": {"fourier": [9.149944321764117, 10.104751847907004, 60.33660836517811]}, "2": {"fourier": [69.71611322336109, 78.39819319083759, 357.2654961422086]}, "3": {"fourier": [17.362364531968304, 19.808017395176492, 57.728612676262856]}, "4": {"fourier": [42.09250217229839, 47.00539094884869, 230.02428844571114]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [49.61748049967727, 55.8867127618805, 239.0034855529666]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.490115, -0.014935, 0.309498, 0.129559, -0.346239], [-0.099157, -0.083075, -0.152816, -0.473807, -0.371314], [0.770528, 0.127912, -0.002052, 0.235109, -0.385436], [0.596325, 0.068987, 0.011688, -0.296899, 0.164491], [-0.022468, 0.03651, 0.708453, -0.52115, -0.20134]], "network.0.bias": [-0.119875, 0.082194, 0.65578, 0.156972, -0.069177], "network.2.weight": [[0.459525, -0.193837, 0.608708, 0.285532, 0.178922], [-0.121903, 0.002356, -0.0295, -0.003489, 0.571354], [0.495116, -0.121997, 0.556749, 0.148564, 0.403205], [0.743419, 0.077521, -0.143338, 0.07489, 0.61667], [0.313957, -0.130418, -0.15065, 0.341614, 0.108904]], "network.2.bias": [-0.028663, 0.032932, -0.072576, -0.052439, -0.330283], "network.4.weight": [[0.028013, 0.312583, -0.064444, -0.171507, 0.186128], [0.180827, 0.054785, -0.261857, -0.272733, 0.337052], [0.794152, 0.556423, 0.137221, 0.656312, 0.059673], [0.505367, 0.372168, 0.625924, -0.212468, 0.332403], [0.56674, -0.081706, 0.542264, 0.157652, 0.524919]], "network.4.bias": [-0.351487, -0.300211, -0.00327, -0.065848, 0.007807], "network.6.weight": [[0.390837, -0.374882, -0.283566, -0.381474, -0.334873], [-0.390806, -0.397559, -0.360419, 0.086452, 0.105742], [0.405974, 0.299639, 0.537839, 0.392613, 0.718797], [-0.213986, -0.03172, -0.003601, -0.690389, 0.184278], [0.219681, 0.139951, -0.188363, 0.643107, 0.629333]], "network.6.bias": [-0.026605, -0.14395, -0.111508, 0.401064, 0.119937], "network.8.weight": [[-0.366589, 0.108788, -0.629808, 0.333334, -0.126564]], "network.8.bias": [0.144534]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.69880810379982, "train_acc": 0.455, "val_loss": 0.700002908706665, "val_acc": 0.36}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6939691603183746, "train_acc": 0.465, "val_loss": 0.6915084719657898, "val_acc": 0.64}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6896198689937592, "train_acc": 0.545, "val_loss": 0.6834803819656372, "val_acc": 0.64}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6873939633369446, "train_acc": 0.545, "val_loss": 0.6739575266838074, "val_acc": 0.64}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6832259595394135, "train_acc": 0.545, "val_loss": 0.661853015422821, "val_acc": 0.64}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6886840462684631, "train_acc": 0.465, "val_loss": 0.6516995429992676, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.6680925786495209, "train_acc": 0.465, "val_loss": 0.6326808333396912, "val_acc": 0.64}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6414750516414642, "train_acc": 0.465, "val_loss": 0.5954495668411255, "val_acc": 0.7}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.600050151348114, "train_acc": 0.725, "val_loss": 0.5419714450836182, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5602608025074005, "train_acc": 0.79, "val_loss": 0.48676085472106934, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.5134894698858261, "train_acc": 0.845, "val_loss": 0.4420314431190491, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.49070701003074646, "train_acc": 0.845, "val_loss": 0.4069390594959259, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.4432169795036316, "train_acc": 0.875, "val_loss": 0.3799767792224884, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.4145009368658066, "train_acc": 0.895, "val_loss": 0.3557356894016266, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.3952796906232834, "train_acc": 0.915, "val_loss": 0.3362659215927124, "val_acc": 0.86}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.700002908706665, "final_val_loss": 0.661853015422821, "initial_val_acc": 0.36, "final_val_acc": 0.64, "best_val_acc": 0.64}, "improved_stage": {"initial_val_loss": 0.6516995429992676, "final_val_loss": 0.3362659215927124, "initial_val_acc": 0.64, "final_val_acc": 0.86, "best_val_acc": 0.86, "best_epoch": 12}, "improvement": 0.21999999999999997, "first_improvement_epoch": 4}} |
5 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.56, "improved_accuracy": 0.94, "improvement": 0.3799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4854, "learning_rate": 0.09414589333639692, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[22.509394, 25.808452, 181.941775], [33.624487, 34.692526, 145.412719], [24.110785, 24.947208, 96.081872], [34.785448, 37.420894, 105.311487], [31.308469, 34.692860, 114.019371], [29.807172, 30.142874, 235.612087], [36.238226, 36.901390, 144.363445], [31.526234, 32.153089, 108.834988]]
### 2
fourier: [[14.253772, 16.530652, 129.188152], [14.771179, 16.340755, 62.302903], [20.005182, 20.242219, 25.444792], [23.129846, 24.242467, 219.015231], [38.410689, 50.980682, 177.080224], [40.271926, 47.480560, 216.423396], [43.111424, 56.228439, 183.635752], [28.487222, 32.490256, 134.678793]]
### 4
fourier: [[94.130530, 111.969346, 547.006598], [97.883265, 115.820908, 603.482728], [28.457606, 33.571920, 133.338475], [71.182109, 86.906926, 431.855907], [30.310153, 32.917107, 240.561133], [17.969487, 23.801188, 107.124011], [2.616950, 2.980476, 45.682239], [15.556514, 20.103952, 124.092486]]
### 6
fourier: [[90.085279, 107.293536, 516.865363], [28.147625, 32.937880, 194.121757], [16.827810, 19.835621, 107.637871], [25.365263, 30.201938, 190.056531], [93.194696, 112.455612, 565.510586], [31.351414, 37.176446, 207.345265], [118.003960, 141.420639, 677.418418], [92.144025, 110.197888, 569.982477]]
### 8
fourier: [[77.259543, 92.615510, 423.209772]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.0.bias": [
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"network.2.weight": [
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}
## Activation Signature
### 0
fourier: [[22.509394, 25.808452, 181.941775], [33.624487, 34.692526, 145.412719], [24.110785, 24.947208, 96.081872], [34.785448, 37.420894, 105.311487], [31.308469, 34.692860, 114.019371], [29.807172, 30.142874, 235.612087], [36.238226, 36.901390, 144.363445], [31.526234, 32.153089, 108.834988]]
### 2
fourier: [[14.253772, 16.530652, 129.188152], [14.771179, 16.340755, 62.302903], [20.005182, 20.242219, 25.444792], [23.129846, 24.242467, 219.015231], [38.410689, 50.980682, 177.080224], [40.271926, 47.480560, 216.423396], [43.111424, 56.228439, 183.635752], [28.487222, 32.490256, 134.678793]]
### 4
fourier: [[94.130530, 111.969346, 547.006598], [97.883265, 115.820908, 603.482728], [28.457606, 33.571920, 133.338475], [71.182109, 86.906926, 431.855907], [30.310153, 32.917107, 240.561133], [17.969487, 23.801188, 107.124011], [2.616950, 2.980476, 45.682239], [15.556514, 20.103952, 124.092486]]
### 6
fourier: [[90.085279, 107.293536, 516.865363], [28.147625, 32.937880, 194.121757], [16.827810, 19.835621, 107.637871], [25.365263, 30.201938, 190.056531], [93.194696, 112.455612, 565.510586], [31.351414, 37.176446, 207.345265], [118.003960, 141.420639, 677.418418], [92.144025, 110.197888, 569.982477]]
### 8
fourier: [[77.259543, 92.615510, 423.209772]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [22.509394282314062, 25.808451994717814, 181.94177502393723]}, "1": {"fourier": [33.62448678864054, 34.69252648210499, 145.4127191901207]}, "2": {"fourier": [24.11078469696945, 24.947207663878988, 96.0818722397089]}, "3": {"fourier": [34.78544813435153, 37.42089447786506, 105.31148744374514]}, "4": {"fourier": [31.308469318077595, 34.692860083528025, 114.01937147974968]}, "5": {"fourier": [29.807171733883628, 30.142873723971736, 235.6120869219303]}, "6": {"fourier": [36.23822621300638, 36.90138957120242, 144.36344462260604]}, "7": {"fourier": [31.526234433924362, 32.15308926705055, 108.83498787879944]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [14.253772004870036, 16.530652416593075, 129.1881524026394]}, "1": {"fourier": [14.77117862093435, 16.340755236074433, 62.302902944386005]}, "2": {"fourier": [20.005182303631024, 20.242218554019928, 25.444791937128997]}, "3": {"fourier": [23.12984600748401, 24.242466527904693, 219.0152313709259]}, "4": {"fourier": [38.41068860643188, 50.98068227351364, 177.0802241563797]}, "5": {"fourier": [40.271926263631705, 47.48056001404084, 216.423395678401]}, "6": {"fourier": [43.11142376762797, 56.22843902535745, 183.63575169444084]}, "7": {"fourier": [28.48722215278363, 32.49025565720051, 134.67879305779934]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [94.13052998177625, 111.96934649439315, 547.0065982043743]}, "1": {"fourier": [97.8832649580291, 115.82090839128207, 603.4827276170254]}, "2": {"fourier": [28.45760646289335, 33.57192001498557, 133.33847466111183]}, "3": {"fourier": [71.1821089841394, 86.90692609792707, 431.85590711236]}, "4": {"fourier": [30.310153028292504, 32.91710744611577, 240.56113266944885]}, "5": {"fourier": [17.969486969936515, 23.801187630571544, 107.1240112632513]}, "6": {"fourier": [2.6169502660950905, 2.9804758079973843, 45.68223948776722]}, "7": {"fourier": [15.556513669706636, 20.103952075701677, 124.09248566627502]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [90.08527869124741, 107.29353563929271, 516.865362778306]}, "1": {"fourier": [28.14762472877437, 32.937880465182, 194.12175703048706]}, "2": {"fourier": [16.827810167046376, 19.83562123458681, 107.63787073642015]}, "3": {"fourier": [25.36526261108191, 30.201937954439906, 190.0565309524536]}, "4": {"fourier": [93.1946960138902, 112.45561232049577, 565.5105858147144]}, "5": {"fourier": [31.35141372272347, 37.1764463536553, 207.34526506066322]}, "6": {"fourier": [118.00395968118082, 141.42063894197003, 677.4184179008007]}, "7": {"fourier": [92.14402466483313, 110.19788833220699, 569.982477158308]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [77.25954305839583, 92.61550950425045, 423.2097719311714]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.001613, -0.651691, 0.079222, -0.03881, -0.174839], [-0.546113, -0.410611, 0.167723, 0.601282, 0.70513], [-0.053146, -0.383179, 0.174119, 0.707695, -0.352943], [0.978731, -0.065162, -0.055761, 0.247774, -0.332194], [-0.410368, -0.315961, -0.296105, 0.479161, -0.124446], [0.005497, -0.442614, -0.091421, -0.409622, -0.321745], [-0.44108, -0.041034, -0.406374, 0.190663, -0.446263], [-0.554386, 0.065021, 0.013437, 0.227783, 0.828883]], "network.0.bias": [-0.698667, 0.534098, 0.38592, 0.065735, -0.43597, -0.352013, 0.01003, 0.241873], "network.2.weight": [[-0.479875, -0.004748, -0.269473, -0.361379, -0.235998, 0.046999, -0.361028, -0.242454], [-0.230541, -0.092611, 0.56695, 0.226278, 0.10478, -0.260977, -0.075106, -0.109196], [-0.33562, 0.106426, 0.613264, -0.341284, 0.186141, 0.177662, -0.286536, 0.173137], [0.048361, -0.192044, -0.203077, -0.56429, -0.305309, 0.003926, -0.289593, -0.338048], [0.466273, 0.618087, 0.672689, -0.519406, 0.339248, -0.114418, -0.071848, 0.305485], [-0.246438, 0.432004, 0.808658, -0.255904, 0.841036, -0.33238, -0.052277, 0.55635], [-0.319157, 0.736652, 0.627286, -0.596751, 0.669523, -0.12036, 0.016909, 0.264159], [-0.062776, 0.510101, 0.557531, -0.140273, 0.388714, -0.351053, -0.218452, 0.167915]], "network.2.bias": [-0.205857, 0.025648, -0.529216, -0.509702, 0.164972, -0.005436, 0.163021, -0.26622], "network.4.weight": [[0.005203, 0.188744, 0.175682, 0.008915, 0.82998, 0.831086, 0.490141, 0.49631], [0.048379, 0.453976, 0.081049, 0.535599, 0.923949, 0.928215, 0.496929, 0.400592], [0.385767, -0.093716, -0.061865, 0.431539, 0.16771, -0.117148, -0.504305, -0.374021], [0.239516, 0.402737, -0.138008, 0.009443, 1.040694, 0.569301, 0.47912, -0.084484], [-0.153422, -0.481724, 0.091868, -0.226576, -0.233929, -0.152361, -0.350272, -0.065038], [0.328131, 0.204603, -0.527486, 0.293737, 0.038383, 0.228657, -0.441577, -0.217193], [-0.18699, -0.097596, -0.013128, 0.169829, -0.184505, 0.147711, -0.048135, 0.027359], [0.252833, 0.03447, -0.283017, -0.071841, -0.36452, -0.025828, -0.037222, 0.088584]], "network.4.bias": [-0.127676, 0.033618, 0.353642, -0.22775, -0.503371, -0.281508, -0.311589, -0.39375], "network.6.weight": [[0.335322, 0.459571, -0.190779, 0.187842, -0.233638, -0.147952, 0.001423, 0.126851], [-0.131862, -0.331597, 0.086474, 0.234137, 0.3095, -0.238337, -0.302186, -0.232704], [-0.2999, -0.053468, 0.308114, 0.23342, -0.35204, -0.337733, 0.283981, -0.339767], [0.115329, -0.293754, -0.257193, -0.106409, -0.254996, -0.044153, 0.042363, 0.280874], [-0.361535, -0.221839, -0.313945, -0.529774, -0.052776, -0.555494, -0.069123, 0.067854], [-0.180653, -0.156951, -0.107795, 0.013709, 0.282067, -0.025399, 0.111302, -0.226032], [0.490122, 0.363562, -0.171223, 0.507346, -0.098587, -0.068868, -0.010884, -0.131857], [-0.074418, -0.624164, -0.382713, -0.340753, -0.270624, -0.276418, 0.274616, -0.082277]], "network.6.bias": [-0.269778, -0.257928, -0.145847, -0.320486, -0.035375, -0.2139, -0.319051, -0.03992], "network.8.weight": [[-0.335062, -0.249554, 0.131497, -0.351041, 0.094175, -0.212405, -0.398146, 0.010686]], "network.8.bias": [0.22665]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6972275674343109, "train_acc": 0.565, "val_loss": 0.6631535291671753, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.640335738658905, "train_acc": 0.565, "val_loss": 0.5430698394775391, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6313904821872711, "train_acc": 0.485, "val_loss": 0.659690797328949, "val_acc": 0.56}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6631079614162445, "train_acc": 0.64, "val_loss": 0.4942764937877655, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.511699303984642, "train_acc": 0.825, "val_loss": 0.39119118452072144, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.4300283342599869, "train_acc": 0.88, "val_loss": 0.3592006266117096, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.35281842947006226, "train_acc": 0.92, "val_loss": 0.2978377044200897, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.33381524682044983, "train_acc": 0.92, "val_loss": 0.2613140344619751, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.3144533038139343, "train_acc": 0.915, "val_loss": 0.24112871289253235, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.2733195126056671, "train_acc": 0.92, "val_loss": 0.2250891923904419, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.25545214116573334, "train_acc": 0.925, "val_loss": 0.22542546689510345, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.2456374168395996, "train_acc": 0.92, "val_loss": 0.20207610726356506, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6631535291671753, "final_val_loss": 0.5430698394775391, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.659690797328949, "final_val_loss": 0.20207610726356506, "initial_val_acc": 0.56, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 4}, "improvement": 0.3799999999999999, "first_improvement_epoch": 1}} |
6 | {"target_pattern": "has_majority", "degraded_accuracy": 0.38, "improved_accuracy": 0.76, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8556, "learning_rate": 0.09363094593146719, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.bias": [
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],
"network.4.weight": [
[
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],
[
0.523336,
0.1392,
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0.17583,
0.518866
],
[
0.780878,
-0.552223,
-0.19263,
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],
[
1.028464,
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0.700758,
0.779375
],
[
-0.883589,
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]
],
"network.4.bias": [
0.030708,
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0.02147,
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],
"network.6.weight": [
[
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0.794303,
-0.443084
],
[
-0.14356,
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0.156678
],
[
0.144408,
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],
[
0.431628,
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0.511717
],
[
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]
],
"network.6.bias": [
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],
"network.8.weight": [
[
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0.429427,
0.770787,
-0.217734
]
],
"network.8.bias": [
-0.0063
]
}
## Activation Signature
### 0
fourier: [[19.231211, 20.091906, 121.321314], [20.628940, 23.636099, 120.729359], [29.026732, 31.055191, 31.206397], [58.984957, 65.167561, 428.133311], [33.956969, 35.050131, 155.071070]]
### 2
fourier: [[8.178855, 8.550514, 78.308032], [16.184863, 17.184702, 61.705221], [12.271935, 14.908226, 62.616598], [22.392513, 25.324532, 125.697229], [9.371963, 11.107606, 102.940668]]
### 4
fourier: [[5.350530, 6.219275, 8.776415], [4.915102, 5.282738, 34.090625], [14.198838, 14.966199, 107.961229], [17.047771, 19.513970, 21.466928], [8.904700, 10.094812, 51.098591]]
### 6
fourier: [[11.704780, 14.231318, 16.354520], [7.236418, 8.441930, 82.870600], [6.512561, 7.750107, 37.627327], [15.950572, 18.404965, 24.453831], [2.775251, 3.239274, 89.690863]]
### 8
fourier: [[12.884357, 15.186604, 40.464840]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.467865,
0.150234
],
[
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[
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],
[
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],
[
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"network.0.bias": [
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],
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],
[
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],
[
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],
[
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],
[
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]
],
"network.2.bias": [
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0.605396,
0.052805,
-0.460182
],
"network.4.weight": [
[
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],
[
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0.17583,
0.518866
],
[
0.780878,
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-0.19263,
-0.543729,
0.107889
],
[
1.028464,
0.118793,
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0.700758,
0.779375
],
[
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]
],
"network.4.bias": [
0.030708,
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0.02147,
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],
"network.6.weight": [
[
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0.794303,
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],
[
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0.156678
],
[
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0.469443
],
[
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0.511717
],
[
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]
],
"network.6.bias": [
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],
"network.8.weight": [
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0.429427,
0.770787,
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]
],
"network.8.bias": [
-0.0063
]
}
## Activation Signature
### 0
fourier: [[19.231211, 20.091906, 121.321314], [20.628940, 23.636099, 120.729359], [29.026732, 31.055191, 31.206397], [58.984957, 65.167561, 428.133311], [33.956969, 35.050131, 155.071070]]
### 2
fourier: [[8.178855, 8.550514, 78.308032], [16.184863, 17.184702, 61.705221], [12.271935, 14.908226, 62.616598], [22.392513, 25.324532, 125.697229], [9.371963, 11.107606, 102.940668]]
### 4
fourier: [[5.350530, 6.219275, 8.776415], [4.915102, 5.282738, 34.090625], [14.198838, 14.966199, 107.961229], [17.047771, 19.513970, 21.466928], [8.904700, 10.094812, 51.098591]]
### 6
fourier: [[11.704780, 14.231318, 16.354520], [7.236418, 8.441930, 82.870600], [6.512561, 7.750107, 37.627327], [15.950572, 18.404965, 24.453831], [2.775251, 3.239274, 89.690863]]
### 8
fourier: [[12.884357, 15.186604, 40.464840]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.231210870143794, 20.091906388056312, 121.3213138282299]}, "1": {"fourier": [20.62894000032097, 23.636099345782963, 120.72935879230499]}, "2": {"fourier": [29.02673154117011, 31.055191413076425, 31.20639655457191]}, "3": {"fourier": [58.98495681814243, 65.16756077888233, 428.13331085443497]}, "4": {"fourier": [33.95696851189697, 35.050131442550146, 155.07107010483742]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [8.178855121389212, 8.5505138838387, 78.30803197622299]}, "1": {"fourier": [16.184863428615046, 17.18470197410077, 61.705221354961395]}, "2": {"fourier": [12.271934986536166, 14.908225917577312, 62.61659750342369]}, "3": {"fourier": [22.39251328184292, 25.324532311135346, 125.69722947478294]}, "4": {"fourier": [9.371963140719961, 11.10760645452578, 102.94066792726517]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [5.350530235174561, 6.219275433310836, 8.776415262371302]}, "1": {"fourier": [4.915102267737545, 5.2827381385060646, 34.090624794363976]}, "2": {"fourier": [14.198837558887227, 14.966199029364752, 107.96122944355011]}, "3": {"fourier": [17.047770979634084, 19.513969572918622, 21.46692797376319]}, "4": {"fourier": [8.904700389611744, 10.094811876339692, 51.09859064221382]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [11.704779849285156, 14.231317520973798, 16.35452013941466]}, "1": {"fourier": [7.2364182330820315, 8.441929862071511, 82.87060046195984]}, "2": {"fourier": [6.5125610937426295, 7.750107203275023, 37.62732681632042]}, "3": {"fourier": [15.950572473737402, 18.404964685095806, 24.453830875456333]}, "4": {"fourier": [2.7752513064756, 3.2392735537050386, 89.6908627152443]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [12.884357279682265, 15.186603766652688, 40.46483977744356]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.111184, 0.079379, 0.119502, 0.467865, 0.150234], [-0.149945, 0.088502, 0.371995, 0.39204, 0.227954], [0.193066, -0.231414, -0.774995, 0.406882, 0.34858], [-0.610763, -0.056776, -0.666464, -0.547847, -0.744138], [0.190817, 0.72547, -0.066974, 0.230656, -0.043192]], "network.0.bias": [-0.096496, -0.532141, 0.471224, -0.40875, -0.137873], "network.2.weight": [[0.231186, -0.274164, -0.061727, 0.150011, -0.228848], [0.10109, -0.315169, -0.705904, -0.032283, 0.292298], [-0.261853, -0.3543, 0.587148, -0.009293, 0.339714], [0.228882, 0.165455, -0.126189, -0.036, 0.53467], [-0.164751, -0.032178, -0.182157, 0.309476, -0.188757]], "network.2.bias": [-0.375621, -0.48082, 0.605396, 0.052805, -0.460182], "network.4.weight": [[0.137467, -0.071874, 0.40067, -0.159442, -0.263934], [0.523336, 0.1392, -0.217782, 0.17583, 0.518866], [0.780878, -0.552223, -0.19263, -0.543729, 0.107889], [1.028464, 0.118793, -1.030961, 0.700758, 0.779375], [-0.883589, -0.430173, 0.552193, -0.282319, -0.459086]], "network.4.bias": [0.030708, -0.319963, -0.261218, 0.02147, 0.372523], "network.6.weight": [[-0.041475, 0.443972, 0.148457, 0.794303, -0.443084], [-0.14356, 0.769507, -0.392891, -0.569463, 0.156678], [0.144408, 0.140853, -0.552124, -0.238432, 0.469443], [0.431628, -0.78309, -0.07598, -0.784865, 0.511717], [-0.355843, 0.345115, 0.359276, -0.214608, 0.250616]], "network.6.bias": [-0.069169, -0.777006, 0.204102, 0.129994, -0.942177], "network.8.weight": [[-0.626305, -0.45979, 0.429427, 0.770787, -0.217734]], "network.8.bias": [-0.0063]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6833219230175018, "train_acc": 0.6, "val_loss": 0.760266900062561, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6676255762577057, "train_acc": 0.6, "val_loss": 0.772173285484314, "val_acc": 0.38}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6871190965175629, "train_acc": 0.6, "val_loss": 0.7569517493247986, "val_acc": 0.38}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6442614793777466, "train_acc": 0.6, "val_loss": 0.7183055281639099, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6547995507717133, "train_acc": 0.555, "val_loss": 0.7208482623100281, "val_acc": 0.58}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.6014353036880493, "train_acc": 0.645, "val_loss": 0.5471457242965698, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.596281111240387, "train_acc": 0.695, "val_loss": 0.6912820339202881, "val_acc": 0.58}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.5946456789970398, "train_acc": 0.665, "val_loss": 0.5646780133247375, "val_acc": 0.72}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.55918288230896, "train_acc": 0.71, "val_loss": 0.5659821033477783, "val_acc": 0.66}], "summary": {"total_epochs": 9, "degraded_epochs": 4, "improved_epochs": 5, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.760266900062561, "final_val_loss": 0.7183055281639099, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.7208482623100281, "final_val_loss": 0.5659821033477783, "initial_val_acc": 0.58, "final_val_acc": 0.66, "best_val_acc": 0.76, "best_epoch": 5}, "improvement": 0.38, "first_improvement_epoch": 3}} |
7 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.98, "improvement": 0.48, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9319, "learning_rate": 0.04720846293947128, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.4.bias": [
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## Activation Signature
### 0
fourier: [[24.239908, 25.985162, 30.552407], [40.862095, 45.993507, 189.915539], [27.677036, 28.506403, 203.121309], [29.034116, 38.176562, 65.016538], [41.159642, 42.486429, 257.816363], [27.327611, 33.846884, 49.684814], [24.511096, 29.301338, 77.866445], [27.239557, 30.577728, 32.342304]]
### 2
fourier: [[16.694255, 17.983420, 26.242971], [18.146815, 20.991301, 90.175251], [14.742725, 17.673518, 49.791537], [20.807610, 21.392891, 51.301342], [22.607534, 23.280159, 147.796580], [51.962168, 56.569716, 222.553339], [13.509318, 19.235859, 126.057751], [9.612581, 9.820324, 48.487757]]
### 4
fourier: [[26.039422, 30.031367, 119.367917], [27.553970, 33.704128, 217.012602], [12.825529, 14.680832, 87.897167], [25.718016, 29.934646, 204.374043], [19.800366, 22.451373, 114.890254], [39.659974, 44.877406, 53.831134], [13.439971, 14.844715, 34.430935], [15.765990, 19.563377, 97.395656]]
### 6
fourier: [[10.891611, 12.025016, 129.155213], [17.060580, 20.717108, 92.854431], [42.644595, 51.291628, 435.804136], [50.795914, 51.491518, 57.231721], [54.409930, 59.655216, 302.614226], [37.531244, 42.353604, 188.913810], [36.144071, 38.526001, 167.359285], [5.440550, 5.678590, 34.354156]]
### 8
fourier: [[68.935881, 70.591015, 153.205646], [106.811869, 127.987910, 819.226386], [92.301152, 104.960435, 592.582724], [18.774532, 22.564180, 135.022559], [19.325993, 24.773341, 236.709441], [83.656434, 95.200291, 523.469788], [106.127135, 120.998964, 655.641574], [9.135241, 10.038376, 174.481855]]
### 10
fourier: [[214.532141, 250.358607, 1436.696465]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[24.239908, 25.985162, 30.552407], [40.862095, 45.993507, 189.915539], [27.677036, 28.506403, 203.121309], [29.034116, 38.176562, 65.016538], [41.159642, 42.486429, 257.816363], [27.327611, 33.846884, 49.684814], [24.511096, 29.301338, 77.866445], [27.239557, 30.577728, 32.342304]]
### 2
fourier: [[16.694255, 17.983420, 26.242971], [18.146815, 20.991301, 90.175251], [14.742725, 17.673518, 49.791537], [20.807610, 21.392891, 51.301342], [22.607534, 23.280159, 147.796580], [51.962168, 56.569716, 222.553339], [13.509318, 19.235859, 126.057751], [9.612581, 9.820324, 48.487757]]
### 4
fourier: [[26.039422, 30.031367, 119.367917], [27.553970, 33.704128, 217.012602], [12.825529, 14.680832, 87.897167], [25.718016, 29.934646, 204.374043], [19.800366, 22.451373, 114.890254], [39.659974, 44.877406, 53.831134], [13.439971, 14.844715, 34.430935], [15.765990, 19.563377, 97.395656]]
### 6
fourier: [[10.891611, 12.025016, 129.155213], [17.060580, 20.717108, 92.854431], [42.644595, 51.291628, 435.804136], [50.795914, 51.491518, 57.231721], [54.409930, 59.655216, 302.614226], [37.531244, 42.353604, 188.913810], [36.144071, 38.526001, 167.359285], [5.440550, 5.678590, 34.354156]]
### 8
fourier: [[68.935881, 70.591015, 153.205646], [106.811869, 127.987910, 819.226386], [92.301152, 104.960435, 592.582724], [18.774532, 22.564180, 135.022559], [19.325993, 24.773341, 236.709441], [83.656434, 95.200291, 523.469788], [106.127135, 120.998964, 655.641574], [9.135241, 10.038376, 174.481855]]
### 10
fourier: [[214.532141, 250.358607, 1436.696465]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [24.239907579149094, 25.985161768157088, 30.55240732436437]}, "1": {"fourier": [40.862095123672475, 45.993506645281236, 189.91553899645805]}, "2": {"fourier": [27.677036194663874, 28.506403050687098, 203.1213087104261]}, "3": {"fourier": [29.03411603408792, 38.17656188382519, 65.01653771102428]}, "4": {"fourier": [41.15964236560565, 42.48642858839395, 257.8163632154465]}, "5": {"fourier": [27.327610953365866, 33.8468837817049, 49.684813648462296]}, "6": {"fourier": [24.51109641536791, 29.301338399592552, 77.86644522845745]}, "7": {"fourier": [27.239556519591737, 30.577728479848314, 32.342304322877325]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [16.694255216460103, 17.983419545995126, 26.242971030024965]}, "1": {"fourier": [18.146814662708078, 20.991300849494436, 90.1752505004406]}, "2": {"fourier": 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10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.734558, 0.403281, 0.109562, -0.157404, 0.124721], [0.772002, 0.621187, 0.032802, 0.252832, -0.394774], [0.147661, -0.06025, -0.479747, -0.365764, -0.479681], [0.219906, 0.494107, -0.303334, 0.331789, -0.352491], [0.757366, 0.542575, 0.005426, 0.276706, -0.072355], [-0.592572, 0.020554, 0.166355, 0.41041, -0.361415], [0.401139, 0.389966, 0.215592, -0.281244, -0.244124], [0.449318, -0.646114, 0.376211, -0.05197, 0.069474]], "network.0.bias": [0.019879, -0.106297, 0.047235, -0.094758, 0.417959, 0.470168, 0.109233, -0.024534], "network.2.weight": 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0.16569632291793823, "train_acc": 0.95, "val_loss": 0.13746234774589539, "val_acc": 0.96}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7026543617248535, "final_val_loss": 0.6631693840026855, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5259669423103333, "final_val_loss": 0.13746234774589539, "initial_val_acc": 0.94, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 7}, "improvement": 0.48, "first_improvement_epoch": 1}} |
8 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.42, "improved_accuracy": 0.96, "improvement": 0.54, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9749, "learning_rate": 0.04776131004515171, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[39.356512, 41.040242, 259.817416], [29.285403, 30.732455, 127.161914], [31.581262, 38.003251, 44.110759], [24.269099, 32.828562, 126.758743], [27.887035, 30.317434, 36.424264]]
### 2
fourier: [[16.950517, 18.205559, 104.363146], [18.647874, 18.808079, 68.290958], [21.917224, 25.435536, 206.844197], [31.924005, 33.261489, 179.167879], [17.165656, 18.329753, 133.843710]]
### 4
fourier: [[11.439758, 14.666757, 84.898202], [5.136961, 6.704474, 7.215453], [1.769258, 2.336713, 52.413203], [5.896536, 6.506657, 72.329736], [16.324477, 16.366021, 21.655821]]
### 6
fourier: [[13.240877, 15.785761, 82.041143], [12.854468, 15.259489, 70.527797], [8.068733, 8.809828, 36.801794], [8.970318, 10.296470, 59.405351], [4.432688, 5.266625, 16.766362]]
### 8
fourier: [[0.338181, 0.340741, 8.405609], [13.776102, 16.232758, 112.826199], [11.856109, 14.012736, 35.078392], [1.471535, 1.537471, 45.260822], [10.180470, 11.706034, 31.888369]]
### 10
fourier: [[8.431327, 8.641873, 11.053904], [1.830203, 2.294763, 32.077375], [4.194124, 4.330176, 11.890446], [2.484481, 2.611442, 43.070502], [0.809800, 0.932569, 32.492696]]
### 12
fourier: [[3.706439, 3.775418, 27.797136]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[39.356512, 41.040242, 259.817416], [29.285403, 30.732455, 127.161914], [31.581262, 38.003251, 44.110759], [24.269099, 32.828562, 126.758743], [27.887035, 30.317434, 36.424264]]
### 2
fourier: [[16.950517, 18.205559, 104.363146], [18.647874, 18.808079, 68.290958], [21.917224, 25.435536, 206.844197], [31.924005, 33.261489, 179.167879], [17.165656, 18.329753, 133.843710]]
### 4
fourier: [[11.439758, 14.666757, 84.898202], [5.136961, 6.704474, 7.215453], [1.769258, 2.336713, 52.413203], [5.896536, 6.506657, 72.329736], [16.324477, 16.366021, 21.655821]]
### 6
fourier: [[13.240877, 15.785761, 82.041143], [12.854468, 15.259489, 70.527797], [8.068733, 8.809828, 36.801794], [8.970318, 10.296470, 59.405351], [4.432688, 5.266625, 16.766362]]
### 8
fourier: [[0.338181, 0.340741, 8.405609], [13.776102, 16.232758, 112.826199], [11.856109, 14.012736, 35.078392], [1.471535, 1.537471, 45.260822], [10.180470, 11.706034, 31.888369]]
### 10
fourier: [[8.431327, 8.641873, 11.053904], [1.830203, 2.294763, 32.077375], [4.194124, 4.330176, 11.890446], [2.484481, 2.611442, 43.070502], [0.809800, 0.932569, 32.492696]]
### 12
fourier: [[3.706439, 3.775418, 27.797136]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [39.35651230091677, 41.04024235502975, 259.81741635501385]}, "1": {"fourier": [29.28540270818286, 30.732454900031634, 127.16191418468952]}, "2": {"fourier": [31.58126195799247, 38.00325081881472, 44.11075904965401]}, "3": {"fourier": [24.2690988846261, 32.82856203325383, 126.75874251127243]}, "4": {"fourier": [27.887034975514666, 30.317433782918997, 36.42426358195457]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [16.950517232383206, 18.205559247179348, 104.36314591765404]}, "1": {"fourier": [18.64787405349966, 18.808078554588615, 68.29095836728811]}, "2": {"fourier": [21.917223771832695, 25.435536251365622, 206.8441967368126]}, "3": {"fourier": [31.924004852803606, 33.26148855886507, 179.16787871718407]}, "4": {"fourier": [17.165655918910325, 18.329753338038632, 133.8437104821205]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [11.439758294414476, 14.666756783637307, 84.89820173382759]}, "1": {"fourier": [5.136960723711016, 6.7044744023336875, 7.215452961623669]}, "2": {"fourier": [1.7692576928085324, 2.3367129399242272, 52.41320291161537]}, "3": {"fourier": [5.896535955499258, 6.506657152209655, 72.3297361433506]}, "4": {"fourier": [16.324476907096074, 16.366020759508075, 21.655820797918746]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [13.240877224391543, 15.785761325150274, 82.04114282131195]}, "1": {"fourier": [12.854468094076784, 15.259488874907955, 70.52779699862003]}, "2": {"fourier": [8.06873271750891, 8.809827929348032, 36.801794201135635]}, "3": {"fourier": [8.970317670443544, 10.296470447224237, 59.405351251363754]}, "4": {"fourier": [4.432687854232332, 5.266624735347059, 16.76636166870594]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [0.3381805901286699, 0.3407408927382011, 8.4056086987257]}, "1": {"fourier": [13.776102108542473, 16.232758009915564, 112.8261994831264]}, "2": {"fourier": [11.856109092888024, 14.01273551855869, 35.07839193940163]}, "3": {"fourier": [1.4715350735370836, 1.5374712230973797, 45.2608223259449]}, "4": {"fourier": [10.180469624916109, 11.706033992836788, 31.888368785381317]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [8.431327312499073, 8.641873274010937, 11.053904131054878]}, "1": {"fourier": [1.8302030473267679, 2.2947626653835327, 32.07737484574318]}, "2": {"fourier": [4.194123685633453, 4.33017599985383, 11.890446454286575]}, "3": {"fourier": [2.4844812071222018, 2.6114422622635716, 43.070502042770386]}, "4": {"fourier": [0.8098004015587686, 0.9325686385126639, 32.492695927619934]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [3.706438742841647, 3.775417934497764, 27.797136291861534]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.245496, 0.248902, 0.285427, 0.318474, 0.681197], [0.371698, 0.446275, -0.086902, 0.280985, -0.197645], [-0.713429, 0.195988, 0.315694, 0.330346, -0.370811], [-0.057154, -0.550881, -0.278557, 0.219863, -0.36703], [-0.596521, -0.032086, -0.194699, 0.398796, 0.52646]], "network.0.bias": [0.008482, -0.040125, 0.110284, 0.229583, -0.240704], "network.2.weight": [[-0.262108, -0.107199, -0.285936, 0.154122, -0.472814], [0.253202, 0.409743, -0.395258, -0.345516, -0.402111], [-0.17374, -0.600807, -0.258416, -0.380246, -0.076232], [-0.672244, -0.166596, 0.347899, 0.221961, -0.07373], [0.159439, -0.28922, 0.346175, 0.241631, 0.620611]], "network.2.bias": [0.351467, 0.126334, -0.595319, -0.109255, 0.654476], "network.4.weight": [[0.375654, -0.2556, 0.108827, -0.446314, 0.563218], [-0.247083, 0.156191, -0.044341, 0.300338, -0.221685], [0.063027, 0.049065, -0.36721, 0.056369, -0.076338], [-0.362951, -0.089719, -0.035969, -0.22142, -0.424396], [-0.293989, 0.546356, -0.083268, -0.419644, -0.65355]], "network.4.bias": [0.295143, 0.134432, -0.510396, -0.08702, 0.55018], "network.6.weight": [[0.817168, -0.19308, 0.136911, -0.42908, -0.421113], [0.754333, -0.027178, -0.128758, -0.216499, -0.493242], [-0.298021, -0.448844, -0.314121, -0.340095, -0.637293], [0.405594, -0.018915, -0.330075, 0.433892, -0.467955], [0.454159, 0.196946, -0.385369, 0.281672, 0.032228]], "network.6.bias": [0.295312, 0.241302, 0.178091, 0.448804, -0.290741], "network.8.weight": [[0.074177, -0.107319, -0.105117, -0.029678, 0.044791], [0.607976, 0.282162, 0.013822, 0.512756, 0.145427], [-0.336964, -0.270942, -0.163894, -0.617997, -0.271166], [-0.236537, 0.290774, 0.063319, -0.319337, 0.240862], [-0.514106, -0.406462, -0.423266, -0.198012, 0.314056]], "network.8.bias": [-0.059808, -0.011708, 0.697098, -0.344371, 0.601523], "network.10.weight": [[-0.356494, -0.301275, 0.464121, 0.158912, 0.598648], [-0.059607, -0.226763, -0.41008, 0.016497, -0.013595], [-0.311035, 0.196851, -0.393766, -0.363756, 0.05598], [-0.391154, -0.207717, -0.554663, 0.19046, -0.263792], [-0.404038, 0.083789, 0.153535, -0.438568, 0.142796]], "network.10.bias": [0.354151, -0.008378, -0.063093, -0.100457, -0.507697], "network.12.weight": [[0.408929, -0.231835, -0.356745, -0.111804, -0.044761]], "network.12.bias": [-0.335161]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6746063232421875, "train_acc": 0.595, "val_loss": 0.7366824150085449, "val_acc": 0.42}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6757084429264069, "train_acc": 0.595, "val_loss": 0.7434150576591492, "val_acc": 0.42}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6772147119045258, "train_acc": 0.595, "val_loss": 0.7370006442070007, "val_acc": 0.42}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6666013300418854, "train_acc": 0.595, "val_loss": 0.7140834927558899, "val_acc": 0.42}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6517724692821503, "train_acc": 0.595, "val_loss": 0.6739091277122498, "val_acc": 0.42}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6394225656986237, "train_acc": 0.52, "val_loss": 0.5896424651145935, "val_acc": 0.96}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5616037249565125, "train_acc": 0.925, "val_loss": 0.4709840714931488, "val_acc": 0.96}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.4464101344347, "train_acc": 0.92, "val_loss": 0.32218611240386963, "val_acc": 0.96}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.34115898609161377, "train_acc": 0.9, "val_loss": 0.2454855740070343, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.2534078061580658, "train_acc": 0.92, "val_loss": 0.16236171126365662, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.2731766104698181, "train_acc": 0.91, "val_loss": 0.1729488968849182, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.2181781679391861, "train_acc": 0.91, "val_loss": 0.1519535779953003, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.19092459231615067, "train_acc": 0.94, "val_loss": 0.20882190763950348, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.21854931116104126, "train_acc": 0.93, "val_loss": 0.17031818628311157, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.212548166513443, "train_acc": 0.94, "val_loss": 0.15061479806900024, "val_acc": 0.96}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7366824150085449, "final_val_loss": 0.6739091277122498, "initial_val_acc": 0.42, "final_val_acc": 0.42, "best_val_acc": 0.42}, "improved_stage": {"initial_val_loss": 0.5896424651145935, "final_val_loss": 0.15061479806900024, "initial_val_acc": 0.96, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 5}, "improvement": 0.54, "first_improvement_epoch": 4}} |
9 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.64, "improved_accuracy": 0.86, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8252, "learning_rate": 0.027729101250368093, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[37.430545, 44.469973, 301.825669], [33.974580, 39.587100, 227.725828], [31.064875, 32.196658, 38.127141], [20.234226, 22.201366, 177.860651], [29.714333, 31.180617, 73.296611], [33.261093, 37.891970, 128.858647], [23.180002, 24.971147, 38.143507], [18.533844, 19.426785, 20.151632]]
### 2
fourier: [[28.950432, 31.708622, 121.574923], [16.117751, 16.929406, 107.806265], [12.439873, 13.759460, 37.322944], [13.103931, 13.462611, 41.630206], [12.850551, 16.669107, 34.917658], [20.993682, 24.246200, 196.704668], [20.372329, 21.233180, 22.635855], [16.282944, 19.938192, 39.693385]]
### 4
fourier: [[6.942977, 7.631719, 102.940852], [32.747437, 35.926303, 94.069706], [7.065903, 7.863892, 61.031774], [33.100566, 35.717653, 158.841592], [4.032765, 4.039953, 50.259045], [21.351018, 24.786846, 74.449661], [27.357048, 29.313658, 36.461291], [3.137085, 3.808468, 87.386082]]
### 6
fourier: [[20.502240, 21.656105, 23.278646], [23.599721, 24.259610, 49.031945], [35.586999, 37.651030, 120.051608], [5.234545, 5.533708, 79.354671], [49.354062, 52.894879, 178.705651], [17.034417, 18.539165, 31.710984], [15.388356, 16.540527, 102.290352], [12.577645, 13.779569, 14.317964]]
### 8
fourier: [[69.002042, 72.422399, 199.257247]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[37.430545, 44.469973, 301.825669], [33.974580, 39.587100, 227.725828], [31.064875, 32.196658, 38.127141], [20.234226, 22.201366, 177.860651], [29.714333, 31.180617, 73.296611], [33.261093, 37.891970, 128.858647], [23.180002, 24.971147, 38.143507], [18.533844, 19.426785, 20.151632]]
### 2
fourier: [[28.950432, 31.708622, 121.574923], [16.117751, 16.929406, 107.806265], [12.439873, 13.759460, 37.322944], [13.103931, 13.462611, 41.630206], [12.850551, 16.669107, 34.917658], [20.993682, 24.246200, 196.704668], [20.372329, 21.233180, 22.635855], [16.282944, 19.938192, 39.693385]]
### 4
fourier: [[6.942977, 7.631719, 102.940852], [32.747437, 35.926303, 94.069706], [7.065903, 7.863892, 61.031774], [33.100566, 35.717653, 158.841592], [4.032765, 4.039953, 50.259045], [21.351018, 24.786846, 74.449661], [27.357048, 29.313658, 36.461291], [3.137085, 3.808468, 87.386082]]
### 6
fourier: [[20.502240, 21.656105, 23.278646], [23.599721, 24.259610, 49.031945], [35.586999, 37.651030, 120.051608], [5.234545, 5.533708, 79.354671], [49.354062, 52.894879, 178.705651], [17.034417, 18.539165, 31.710984], [15.388356, 16.540527, 102.290352], [12.577645, 13.779569, 14.317964]]
### 8
fourier: [[69.002042, 72.422399, 199.257247]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [37.43054472797677, 44.46997342701249, 301.82566894590855]}, "1": {"fourier": [33.974579791533316, 39.587099587294205, 227.7258283495903]}, "2": {"fourier": [31.064875369602802, 32.196657819976586, 38.12714061141014]}, "3": {"fourier": [20.234226272390323, 22.20136634340204, 177.8606513440609]}, "4": {"fourier": [29.714332851832243, 31.180616701924563, 73.29661095142365]}, "5": {"fourier": [33.261093128834034, 37.89197040539723, 128.85864660143852]}, "6": {"fourier": [23.180001979343807, 24.971146723783402, 38.14350685477257]}, "7": {"fourier": [18.533844198662383, 19.426785361991975, 20.15163180050866]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [28.950432279298827, 31.7086218113657, 121.5749232172966]}, "1": {"fourier": [16.117751370990465, 16.929405930369917, 107.80626458674669]}, "2": {"fourier": [12.439872558390144, 13.759459952075025, 37.32294353842735]}, "3": {"fourier": [13.1039307427513, 13.4626113768921, 41.63020619750023]}, "4": {"fourier": [12.850550849548167, 16.669106551609296, 34.91765833646059]}, "5": {"fourier": [20.993682236907468, 24.246199725419412, 196.7046681046486]}, "6": {"fourier": [20.372328583515486, 21.233180296064422, 22.635854840278625]}, "7": {"fourier": [16.28294449086631, 19.938191905586578, 39.69338520616293]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [6.942977269731001, 7.631718831950605, 102.94085228443146]}, "1": {"fourier": [32.7474369839175, 35.92630329582678, 94.06970556080341]}, "2": {"fourier": [7.065902872723787, 7.863891958437862, 61.031773924827576]}, "3": {"fourier": [33.100565795248855, 35.717653054008785, 158.8415915518999]}, "4": {"fourier": [4.032765318153928, 4.03995346599574, 50.2590446472168]}, "5": {"fourier": [21.351017788164487, 24.786846368480813, 74.44966128468513]}, "6": {"fourier": [27.357047857830928, 29.313657954788923, 36.46129118651152]}, "7": {"fourier": [3.137084767102688, 3.8084679617290624, 87.38608187437057]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [20.50224037151143, 21.656105280798577, 23.27864645867866]}, "1": {"fourier": [23.599720938664237, 24.25960991704025, 49.03194549679756]}, "2": {"fourier": [35.586998837439715, 37.65103028164798, 120.05160847306252]}, "3": {"fourier": [5.234545065459361, 5.5337078546332314, 79.35467141866684]}, "4": {"fourier": [49.354061868976515, 52.894879471346144, 178.70565125346184]}, "5": {"fourier": [17.034416769427814, 18.53916543128926, 31.71098381280899]}, "6": {"fourier": [15.388355874927655, 16.540527423059718, 102.29035234451294]}, "7": {"fourier": [12.577645019228624, 13.77956943214199, 14.317964259706011]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [69.00204156593075, 72.42239911362627, 199.25724723935127]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.395897, -0.413117, -0.242448, -0.403703, -0.426829], [0.229572, 0.388031, 0.271335, 0.582938, -0.636034], [0.693356, -0.021533, -0.035991, -0.261946, -0.559489], [0.043796, -0.307495, -0.354587, -0.102432, -0.194888], [0.239432, 0.250254, 0.323411, -0.626069, -0.337048], [0.258398, 0.340629, 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"improved_stage": {"initial_val_loss": 0.5014207363128662, "final_val_loss": 0.3554674983024597, "initial_val_acc": 0.8, "final_val_acc": 0.86, "best_val_acc": 0.86, "best_epoch": 10}, "improvement": 0.21999999999999997, "first_improvement_epoch": 1}} |
10 | {"target_pattern": "ends_with", "degraded_accuracy": 0.5, "improved_accuracy": 0.88, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1579, "learning_rate": 0.09508480999907651, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[32.841591, 36.861500, 175.538239], [23.839375, 24.977051, 55.322729], [31.589452, 38.018701, 101.860119], [43.140652, 45.295944, 189.958153], [47.942190, 50.246900, 215.843429]]
### 2
fourier: [[47.988953, 51.134752, 164.310749], [25.214554, 29.955469, 214.218322], [20.396077, 22.700051, 156.149303], [18.198752, 20.075689, 90.533889], [30.636567, 30.836859, 157.541119]]
### 4
fourier: [[13.890633, 14.260131, 159.252931], [10.613750, 11.271735, 94.475003], [39.544976, 41.827241, 120.809777], [47.223380, 49.375066, 135.890203], [26.564683, 29.283635, 29.712324]]
### 6
fourier: [[42.224054, 43.783043, 115.055350], [44.089671, 45.578440, 119.853340], [17.161146, 18.584611, 50.297908], [8.427215, 8.516913, 77.059043], [31.517431, 32.382273, 72.703585]]
### 8
fourier: [[23.180180, 23.618783, 49.037025], [15.107014, 15.878534, 114.892840], [29.929771, 30.272800, 78.746651], [46.292537, 47.658129, 139.681824], [70.425162, 71.608083, 211.024785]]
### 10
fourier: [[34.869338, 35.943870, 110.636497], [43.105886, 44.209502, 151.785174], [22.128686, 23.394370, 118.905717], [4.003820, 4.146222, 19.165475], [31.625941, 32.985922, 151.998035]]
### 12
fourier: [[33.934264, 35.323860, 109.886157]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[32.841591, 36.861500, 175.538239], [23.839375, 24.977051, 55.322729], [31.589452, 38.018701, 101.860119], [43.140652, 45.295944, 189.958153], [47.942190, 50.246900, 215.843429]]
### 2
fourier: [[47.988953, 51.134752, 164.310749], [25.214554, 29.955469, 214.218322], [20.396077, 22.700051, 156.149303], [18.198752, 20.075689, 90.533889], [30.636567, 30.836859, 157.541119]]
### 4
fourier: [[13.890633, 14.260131, 159.252931], [10.613750, 11.271735, 94.475003], [39.544976, 41.827241, 120.809777], [47.223380, 49.375066, 135.890203], [26.564683, 29.283635, 29.712324]]
### 6
fourier: [[42.224054, 43.783043, 115.055350], [44.089671, 45.578440, 119.853340], [17.161146, 18.584611, 50.297908], [8.427215, 8.516913, 77.059043], [31.517431, 32.382273, 72.703585]]
### 8
fourier: [[23.180180, 23.618783, 49.037025], [15.107014, 15.878534, 114.892840], [29.929771, 30.272800, 78.746651], [46.292537, 47.658129, 139.681824], [70.425162, 71.608083, 211.024785]]
### 10
fourier: [[34.869338, 35.943870, 110.636497], [43.105886, 44.209502, 151.785174], [22.128686, 23.394370, 118.905717], [4.003820, 4.146222, 19.165475], [31.625941, 32.985922, 151.998035]]
### 12
fourier: [[33.934264, 35.323860, 109.886157]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [32.84159110903037, 36.861500356933185, 175.53823877871037]}, "1": {"fourier": [23.839375417450363, 24.977051145687433, 55.32272933423519]}, "2": {"fourier": [31.589452179146633, 38.018701438931494, 101.86011911183596]}, "3": {"fourier": [43.14065214466722, 45.29594429101372, 189.95815259218216]}, "4": {"fourier": [47.942189631963586, 50.246900361970916, 215.84342865645885]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [47.98895304875866, 51.13475179960459, 164.31074875593185]}, "1": {"fourier": [25.214553748930634, 29.955469186827806, 214.2183217406273]}, "2": {"fourier": [20.396077182376384, 22.70005117647873, 156.14930260926485]}, "3": {"fourier": [18.198751803747598, 20.07568862316393, 90.53388926386833]}, "4": {"fourier": [30.63656654113341, 30.836859408354986, 157.5411191880703]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [13.890632971404674, 14.260131114271593, 159.25293067097664]}, "1": {"fourier": [10.613749580260361, 11.271735407940213, 94.47500306367874]}, "2": {"fourier": [39.544975592399524, 41.8272412065439, 120.80977691709995]}, "3": {"fourier": [47.2233796656325, 49.37506570736181, 135.89020250178874]}, "4": {"fourier": [26.564682987077468, 29.283634968682218, 29.712323887580098]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [42.22405383169038, 43.78304298376208, 115.05534964799881]}, "1": {"fourier": [44.08967076451675, 45.57844047757819, 119.85334020853043]}, "2": {"fourier": [17.161146096326064, 18.584611039513206, 50.29790812730789]}, "3": {"fourier": [8.427214632598144, 8.516912752350455, 77.05904319882393]}, "4": {"fourier": [31.517431152315375, 32.38227346801523, 72.70358487963676]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [23.180179735288682, 23.61878323753242, 49.03702549636364]}, "1": {"fourier": [15.10701352308067, 15.878533749082623, 114.89284026622772]}, "2": {"fourier": [29.92977131313904, 30.272800191813033, 78.74665062129498]}, "3": {"fourier": [46.29253729667844, 47.658129139008985, 139.68182396888733]}, "4": {"fourier": [70.4251620306719, 71.60808263671998, 211.02478470653296]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [34.869338177271565, 35.943870122732314, 110.63649662397802]}, "1": {"fourier": [43.105885968558304, 44.209502027168334, 151.7851736843586]}, "2": {"fourier": [22.12868638365026, 23.394370384424885, 118.90571731328964]}, "3": {"fourier": [4.00381987834051, 4.146221740440957, 19.16547480598092]}, "4": {"fourier": [31.625940928983436, 32.98592241396818, 151.9980347454548]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [33.93426365427427, 35.32385984162126, 109.88615668565035]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.35581, -0.020805, 0.309191, 0.260601, 0.816865], [0.520949, 0.016465, -0.563783, -0.216985, 0.14942], [0.806871, 0.123734, -0.176138, -0.008146, 0.276843], [0.033472, 0.551363, 0.310258, 0.563418, -1.04347], [0.507523, 0.028368, 0.21001, 0.138349, 0.891983]], "network.0.bias": [0.218947, 0.165716, -0.053836, 0.494922, -0.120497], "network.2.weight": [[0.29063, 0.172904, 0.494971, -0.296711, 0.456256], [-0.129501, -0.130216, -0.236338, -0.248167, -0.366786], [0.133821, -0.38782, -0.245333, 0.646494, 0.195806], [0.242011, 0.442096, -0.004534, -0.182418, 0.154718], [-0.375796, -0.146937, -0.353512, 0.097258, -0.178401]], "network.2.bias": [0.205628, -0.311053, -0.165975, 0.478807, -0.328101], "network.4.weight": [[0.016212, -0.384459, -0.633364, -0.568734, -0.247068], [-0.101329, 0.383555, -0.090229, -0.339815, -0.349275], [0.630445, -0.239994, -0.307319, 0.386407, 0.045512], [0.804235, -0.053306, -0.195243, 0.382824, -0.098236], [-0.222659, 0.443686, 0.61503, -0.625712, 0.253541]], "network.4.bias": [-0.110793, -0.356415, 0.307535, -0.043826, 0.249251], "network.6.weight": [[0.348501, -0.268313, 0.541712, 0.336252, -0.569912], [0.32979, -0.312879, 0.622626, 0.308457, -0.570364], [0.118304, 0.445564, -0.058422, -0.082902, 0.764134], [0.109366, 0.406377, -0.078904, -0.189077, -0.359533], [0.062409, 0.144846, -0.039689, 0.64421, -0.322087]], "network.6.bias": [0.342894, 0.32189, 0.205462, -0.152563, 0.041595], "network.8.weight": [[-0.382375, -0.130884, 0.137815, -0.011547, -0.066542], [0.161919, -0.538537, -0.005874, 0.278318, -0.003687], [-0.048837, -0.529373, 0.226405, 0.445914, -0.156868], [-0.314848, -0.808774, 0.176031, -0.103636, -0.012539], [0.779371, 0.636046, -0.457045, 0.358206, 0.366052]], "network.8.bias": [0.21855, -0.662998, 0.04214, 0.102098, 0.09223], "network.10.weight": [[-0.179214, 0.16617, 0.033222, -0.395418, 0.507662], [-0.39392, -0.037792, -0.208455, -0.23255, 0.618087], [-0.225577, -0.339957, -0.258746, 0.330125, -0.347431], [0.32701, -0.325867, -0.25051, -0.01928, -0.057055], [0.162683, -0.390672, 0.117621, -0.163938, -0.476543]], "network.10.bias": [0.00174, 0.223589, -0.397092, -0.080449, -0.484593], "network.12.weight": [[-0.260731, -0.600494, -0.296545, 0.423743, 0.122104]], "network.12.bias": [0.158802]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7276186645030975, "train_acc": 0.575, "val_loss": 0.7131456136703491, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6732656061649323, "train_acc": 0.575, "val_loss": 0.6757310628890991, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6634600162506104, "train_acc": 0.5, "val_loss": 0.5158546566963196, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.7300393283367157, "train_acc": 0.71, "val_loss": 0.43082183599472046, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4715665578842163, "train_acc": 0.84, "val_loss": 0.5658320784568787, "val_acc": 0.74}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.5846738517284393, "train_acc": 0.715, "val_loss": 0.5944726467132568, "val_acc": 0.64}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.5743566751480103, "train_acc": 0.675, "val_loss": 0.480214923620224, "val_acc": 0.76}], "summary": {"total_epochs": 7, "degraded_epochs": 2, "improved_epochs": 5, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.7131456136703491, "final_val_loss": 0.6757310628890991, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5158546566963196, "final_val_loss": 0.480214923620224, "initial_val_acc": 0.82, "final_val_acc": 0.76, "best_val_acc": 0.88, "best_epoch": 3}, "improvement": 0.38, "first_improvement_epoch": 1}} |
11 | {"target_pattern": "ends_with", "degraded_accuracy": 0.52, "improved_accuracy": 0.9, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2113, "learning_rate": 0.0493680412770662, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[40.200591, 50.268213, 132.738869], [23.458453, 24.693778, 54.115567], [48.637006, 56.745102, 190.454710], [27.651209, 34.999226, 39.839884], [47.097344, 57.708841, 111.099360], [26.142767, 29.944749, 118.764665], [59.389685, 59.474237, 182.943607], [26.584536, 27.354818, 59.477202]]
### 2
fourier: [[20.173728, 20.318022, 126.212289], [65.537210, 76.116088, 81.736036], [125.532694, 142.225014, 399.280698], [13.634009, 14.429758, 85.902652], [15.228872, 16.197591, 97.948765], [64.917861, 74.357383, 123.532017], [149.575928, 169.673089, 491.652277], [125.158597, 133.485073, 387.350348]]
### 4
fourier: [[119.980967, 135.628494, 455.881928], [172.805997, 191.504756, 508.911847], [101.593949, 107.667573, 220.870506], [104.859308, 111.864298, 158.809545], [72.450173, 82.882766, 271.442771], [119.809177, 136.692839, 450.766539], [67.997432, 80.205675, 339.302749], [215.593290, 238.684446, 624.186486]]
### 6
fourier: [[295.750069, 326.517620, 826.125678], [143.887074, 155.639046, 366.284531], [65.461071, 68.861321, 76.217707], [148.331532, 160.387787, 359.515462], [172.013059, 188.671028, 480.761968], [8.389371, 10.010558, 42.814446], [90.907771, 105.441295, 346.952232], [11.209973, 12.173672, 124.115314]]
### 8
fourier: [[77.612018, 89.319662, 283.326655], [427.863336, 468.267105, 1149.559172], [55.448200, 63.495256, 186.361974], [410.367594, 455.225053, 1154.698703], [27.022264, 35.727556, 171.564604], [395.021208, 431.633036, 1051.698827], [188.259400, 199.147075, 438.601166], [303.119739, 338.291699, 872.542654]]
### 10
fourier: [[626.815915, 705.081569, 1809.504080]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.bias": [
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}
## Activation Signature
### 0
fourier: [[40.200591, 50.268213, 132.738869], [23.458453, 24.693778, 54.115567], [48.637006, 56.745102, 190.454710], [27.651209, 34.999226, 39.839884], [47.097344, 57.708841, 111.099360], [26.142767, 29.944749, 118.764665], [59.389685, 59.474237, 182.943607], [26.584536, 27.354818, 59.477202]]
### 2
fourier: [[20.173728, 20.318022, 126.212289], [65.537210, 76.116088, 81.736036], [125.532694, 142.225014, 399.280698], [13.634009, 14.429758, 85.902652], [15.228872, 16.197591, 97.948765], [64.917861, 74.357383, 123.532017], [149.575928, 169.673089, 491.652277], [125.158597, 133.485073, 387.350348]]
### 4
fourier: [[119.980967, 135.628494, 455.881928], [172.805997, 191.504756, 508.911847], [101.593949, 107.667573, 220.870506], [104.859308, 111.864298, 158.809545], [72.450173, 82.882766, 271.442771], [119.809177, 136.692839, 450.766539], [67.997432, 80.205675, 339.302749], [215.593290, 238.684446, 624.186486]]
### 6
fourier: [[295.750069, 326.517620, 826.125678], [143.887074, 155.639046, 366.284531], [65.461071, 68.861321, 76.217707], [148.331532, 160.387787, 359.515462], [172.013059, 188.671028, 480.761968], [8.389371, 10.010558, 42.814446], [90.907771, 105.441295, 346.952232], [11.209973, 12.173672, 124.115314]]
### 8
fourier: [[77.612018, 89.319662, 283.326655], [427.863336, 468.267105, 1149.559172], [55.448200, 63.495256, 186.361974], [410.367594, 455.225053, 1154.698703], [27.022264, 35.727556, 171.564604], [395.021208, 431.633036, 1051.698827], [188.259400, 199.147075, 438.601166], [303.119739, 338.291699, 872.542654]]
### 10
fourier: [[626.815915, 705.081569, 1809.504080]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [40.20059076538523, 50.2682127535004, 132.738868907094]}, "1": {"fourier": [23.458452925065252, 24.693777775358125, 54.115567207336426]}, "2": {"fourier": [48.637006050488175, 56.74510216131609, 190.45471001416445]}, "3": {"fourier": [27.65120908528642, 34.99922578267295, 39.83988360356655]}, "4": {"fourier": [47.09734421644084, 57.70884130643749, 111.09935952350497]}, "5": {"fourier": [26.142766667403382, 29.944749069769827, 118.7646647952497]}, "6": {"fourier": [59.38968468636911, 59.47423731563563, 182.94360683858395]}, "7": {"fourier": [26.584536156588463, 27.354818253267336, 59.47720177471638]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [20.17372833370998, 20.31802206469483, 126.21228884160519]}, "1": {"fourier": [65.5372102139385, 76.11608768999577, 81.73603629152555]}, "2": {"fourier": [125.53269384970694, 142.22501422824237, 399.2806982398033]}, "3": {"fourier": [13.634008712410171, 14.429758407846556, 85.90265202522278]}, "4": {"fourier": [15.22887200842514, 16.197591203140853, 97.94876465201378]}, "5": {"fourier": [64.91786077157323, 74.35738337136405, 123.53201720118523]}, "6": {"fourier": [149.57592849103642, 169.67308920130088, 491.6522766277194]}, "7": {"fourier": [125.15859741660775, 133.48507283612045, 387.3503483235836]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [119.98096652338936, 135.62849412137408, 455.881927549839]}, "1": {"fourier": [172.80599694404913, 191.50475582803895, 508.91184664331377]}, "2": {"fourier": [101.5939491034446, 107.6675727024175, 220.87050587683916]}, "3": {"fourier": [104.85930845829901, 111.86429767514065, 158.80954539775848]}, "4": {"fourier": [72.45017263287237, 82.88276619045867, 271.4427714198828]}, "5": {"fourier": [119.80917654921784, 136.69283923394815, 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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [77.61201753394997, 89.3196619726346, 283.32665514945984]}, "1": {"fourier": [427.8633363126991, 468.26710539671245, 1149.5591718703508]}, "2": {"fourier": [55.448200403998946, 63.495256102382044, 186.36197412759066]}, "3": {"fourier": [410.36759394134964, 455.2250532303114, 1154.6987034082413]}, "4": {"fourier": [27.02226400426474, 35.72755595570945, 171.5646042227745]}, "5": {"fourier": [395.02120817898884, 431.6330363981166, 1051.6988266557455]}, "6": {"fourier": [188.25939982536656, 199.14707528365196, 438.6011655330658]}, "7": {"fourier": [303.1197393609639, 338.29169945085056, 872.5426537394524]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [626.8159146154346, 705.0815692845865, 1809.5040798187256]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, 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"improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.27022719383239746, "train_acc": 0.89, "val_loss": 0.37836921215057373, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.31519490480422974, "train_acc": 0.885, "val_loss": 0.6331797242164612, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.3053025007247925, "train_acc": 0.87, "val_loss": 0.29988059401512146, "val_acc": 0.9}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6892942786216736, "final_val_loss": 0.6021696925163269, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.4556771516799927, "final_val_loss": 0.29988059401512146, "initial_val_acc": 0.86, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 12}, "improvement": 0.38, "first_improvement_epoch": 2}} |
12 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.38, "improved_accuracy": 0.92, "improvement": 0.54, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1822, "learning_rate": 0.04873785800456769, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[21.905861, 28.025916, 38.460427], [40.914325, 44.764116, 183.050819], [34.283197, 36.981623, 179.074902], [13.740685, 16.544151, 46.617024], [28.053823, 29.640397, 130.579849], [28.120984, 32.140924, 145.274946], [43.716072, 44.893056, 205.284265], [23.670669, 24.279187, 43.973600]]
### 2
fourier: [[68.802851, 73.311918, 396.770266], [31.624534, 33.705578, 123.108112], [40.961411, 41.735438, 266.258019], [18.450615, 18.703302, 96.855852], [10.931442, 11.443778, 84.045212], [50.925227, 51.533836, 298.699735], [14.507778, 15.238946, 86.340240], [15.180923, 16.622405, 119.245774]]
### 4
fourier: [[58.891905, 60.860540, 345.329087], [42.585309, 43.456971, 255.482712], [29.404703, 30.248524, 190.886494], [70.865126, 72.511347, 405.963597], [21.252467, 21.482584, 160.931415], [25.842198, 27.655677, 191.643508], [69.308122, 70.562530, 390.152411], [21.389562, 22.985184, 129.940122]]
### 6
fourier: [[129.760944, 132.822844, 758.357907], [123.085400, 125.762535, 747.503819], [17.074117, 17.081335, 105.862211], [7.874519, 8.145666, 70.634340], [21.598661, 22.131056, 142.905630], [52.728680, 53.396607, 310.711587], [94.105847, 95.805292, 529.992807], [57.412563, 58.375784, 335.790166]]
### 8
fourier: [[139.000173, 141.842148, 777.909535]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.8.bias": [
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}
## Activation Signature
### 0
fourier: [[21.905861, 28.025916, 38.460427], [40.914325, 44.764116, 183.050819], [34.283197, 36.981623, 179.074902], [13.740685, 16.544151, 46.617024], [28.053823, 29.640397, 130.579849], [28.120984, 32.140924, 145.274946], [43.716072, 44.893056, 205.284265], [23.670669, 24.279187, 43.973600]]
### 2
fourier: [[68.802851, 73.311918, 396.770266], [31.624534, 33.705578, 123.108112], [40.961411, 41.735438, 266.258019], [18.450615, 18.703302, 96.855852], [10.931442, 11.443778, 84.045212], [50.925227, 51.533836, 298.699735], [14.507778, 15.238946, 86.340240], [15.180923, 16.622405, 119.245774]]
### 4
fourier: [[58.891905, 60.860540, 345.329087], [42.585309, 43.456971, 255.482712], [29.404703, 30.248524, 190.886494], [70.865126, 72.511347, 405.963597], [21.252467, 21.482584, 160.931415], [25.842198, 27.655677, 191.643508], [69.308122, 70.562530, 390.152411], [21.389562, 22.985184, 129.940122]]
### 6
fourier: [[129.760944, 132.822844, 758.357907], [123.085400, 125.762535, 747.503819], [17.074117, 17.081335, 105.862211], [7.874519, 8.145666, 70.634340], [21.598661, 22.131056, 142.905630], [52.728680, 53.396607, 310.711587], [94.105847, 95.805292, 529.992807], [57.412563, 58.375784, 335.790166]]
### 8
fourier: [[139.000173, 141.842148, 777.909535]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.905860900858382, 28.025916466598055, 38.460427314043045]}, "1": {"fourier": [40.914324919049676, 44.76411589451114, 183.05081883072853]}, "2": {"fourier": [34.28319671557234, 36.981623079421354, 179.07490211725235]}, "3": {"fourier": [13.740685230184678, 16.544151078478468, 46.61702410131693]}, "4": {"fourier": [28.053823431390096, 29.640397282610632, 130.57984852790833]}, "5": {"fourier": [28.120984129253106, 32.140923785411445, 145.27494625002146]}, "6": {"fourier": [43.716072313346544, 44.89305647414984, 205.28426472842693]}, "7": {"fourier": [23.670669267706117, 24.27918735898583, 43.973599538207054]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [68.80285127299489, 73.31191821456463, 396.77026569098234]}, "1": {"fourier": [31.624534125398007, 33.705577647501, 123.10811164975166]}, "2": {"fourier": [40.961411427662306, 41.73543816565725, 266.25801880657673]}, "3": {"fourier": [18.450615020514867, 18.70330186726689, 96.85585194826126]}, "4": {"fourier": [10.93144212383535, 11.4437780717232, 84.04521244764328]}, "5": {"fourier": [50.92522674890856, 51.5338359965534, 298.6997350305319]}, "6": {"fourier": [14.507778370569348, 15.238946360692086, 86.3402396440506]}, "7": {"fourier": [15.18092267285201, 16.622405019285974, 119.24577425420284]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [58.89190457487305, 60.860540212857, 345.32908744364977]}, "1": {"fourier": [42.58530929605799, 43.45697129292497, 255.48271156474948]}, "2": {"fourier": [29.404702977972494, 30.24852369476696, 190.88649439811707]}, "3": {"fourier": [70.8651257729718, 72.51134657259234, 405.9635965079069]}, "4": {"fourier": [21.25246716722792, 21.4825843205431, 160.93141549825668]}, "5": {"fourier": [25.84219764069505, 27.65567699343283, 191.64350754022598]}, "6": {"fourier": [69.30812236568036, 70.56253034157844, 390.15241101384163]}, "7": {"fourier": [21.389561781680168, 22.98518447843167, 129.94012168049812]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [129.76094448022837, 132.82284368852703, 758.3579065389931]}, "1": {"fourier": [123.08539951024432, 125.76253467631767, 747.5038191229105]}, "2": {"fourier": [17.074117413976374, 17.08133465141318, 105.86221068352461]}, "3": {"fourier": [7.874519081149884, 8.145666342935032, 70.63434013724327]}, "4": {"fourier": [21.59866066729415, 22.131055823066205, 142.90562987327576]}, "5": {"fourier": [52.72868018150511, 53.39660742631878, 310.7115865200758]}, "6": {"fourier": [94.10584708576603, 95.80529156260029, 529.9928068444133]}, "7": {"fourier": [57.41256293443995, 58.375783894907656, 335.79016621410847]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [139.0001728686944, 141.84214771631127, 777.9095346927643]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.115463, 0.287483, -0.325066, 0.194319, -0.314336], [0.7861, 0.542822, 0.29277, -0.157636, -0.245119], [0.777305, 0.225672, 0.105386, 0.251865, -0.545866], [-0.090353, -0.229129, 0.202248, 0.329155, -0.038548], [0.60164, 0.256534, -0.113572, 0.253767, -0.338528], [-0.291729, -0.544491, -0.125875, 0.253131, -0.433429], [0.710234, 0.5557, 0.459728, -0.022114, -0.382819], [-0.248121, 0.307252, -0.405295, 0.087673, -0.179556]], "network.0.bias": [0.409796, 0.095289, 0.524167, -0.032857, 0.345286, -0.004266, -0.056273, 0.140355], "network.2.weight": [[0.666855, 0.640797, 0.426445, -0.085714, 0.260639, 0.071954, 0.511927, 0.083087], [0.061971, 0.036715, -0.334752, 0.517216, -0.487298, -0.487417, -0.294, 0.203007], [0.538459, 0.158438, 0.363477, -0.165353, 0.217035, 0.215647, 0.318011, 0.440556], [0.323951, 0.035257, 0.002212, -0.038236, 0.452442, -0.059193, 0.039488, -0.18406], [0.373517, -0.124036, -0.38512, -0.238768, -0.068623, 0.315169, 0.157137, -0.003593], [0.513285, 0.354788, 0.314939, 0.079823, 0.490461, 0.273867, 0.253671, 0.086918], [0.307768, -0.175843, -0.354227, -0.168732, 0.270973, -0.174213, -0.089531, -0.460465], [-0.106157, 0.10505, -0.097524, -0.414985, -0.374969, -0.020542, -0.104906, -0.156948]], "network.2.bias": [0.117854, 0.313025, 0.395397, 0.056686, -0.271082, 0.125179, -0.051622, -0.165802], "network.4.weight": [[0.461049, -0.072732, 0.595885, -0.152342, -0.088803, 0.097761, 0.162883, 0.00394], [0.314459, -0.075386, 0.332605, 0.130329, 0.447933, 0.090735, -0.306572, 0.212836], [0.145333, -0.54134, 0.122969, -0.10268, -0.137505, 0.303728, 0.126465, -0.095525], [0.480572, -0.163448, 0.451143, 0.124459, -0.015016, 0.32473, -0.190292, -0.077219], [0.002995, -0.125959, -0.235026, -0.069661, 0.110882, -0.211164, -0.189872, 0.107078], [-0.366238, -0.117776, -0.269494, 0.196529, 0.159777, 0.13625, -0.032812, 0.298991], [0.435751, -0.256063, 0.31312, 0.269813, 0.419755, 0.413796, -0.040534, 0.000237], [0.292474, -0.137409, 0.199172, -0.25454, -0.046237, -0.052617, 0.161747, 0.426054]], "network.4.bias": [-0.113584, 0.032639, 0.261991, -0.141788, -0.320159, -0.371507, -0.15619, 0.024465], "network.6.weight": [[0.532838, 0.608594, 0.262747, 0.354452, -0.040008, 0.324926, 0.390601, 0.575911], [0.596821, 0.276208, 0.652381, 0.431799, 0.156626, -0.22604, 0.268286, 0.350403], [-0.122725, 0.14566, -0.086069, -0.09444, -0.319536, -0.140988, -0.174259, 0.249296], [0.030645, -0.100644, 0.193749, -0.280482, 0.046072, 0.072419, 0.135753, -0.029846], [-0.005515, 0.111304, -0.361846, 0.199321, 0.114407, -0.122948, -0.316887, -0.34876], [-0.154362, -0.051687, -0.237918, -0.120052, -0.114186, -0.056962, -0.406485, 0.11199], [0.145119, 0.371393, 0.080161, 0.593185, 0.180179, 0.091096, 0.336685, 0.085408], [-0.275883, -0.162092, 0.121314, -0.134282, -0.353852, 0.141409, -0.426757, 0.064245]], "network.6.bias": [-0.040536, 0.215457, -0.112411, -0.309403, -0.129626, -0.059367, -0.159965, -0.101845], "network.8.weight": [[-0.452991, -0.191081, -0.218758, -0.026695, 0.077774, 0.008249, -0.602386, -0.062911]], "network.8.bias": [0.311768]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6910922229290009, "train_acc": 0.515, "val_loss": 0.6403840780258179, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.5626020133495331, "train_acc": 0.595, "val_loss": 0.5719516277313232, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.49698516726493835, "train_acc": 0.66, "val_loss": 0.5013895630836487, "val_acc": 0.9}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.41881324350833893, "train_acc": 0.86, "val_loss": 0.4354802668094635, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4103071391582489, "train_acc": 0.86, "val_loss": 0.4138626158237457, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3703653812408447, "train_acc": 0.87, "val_loss": 0.4048392176628113, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.3677143156528473, "train_acc": 0.86, "val_loss": 0.38348492980003357, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.3262241780757904, "train_acc": 0.89, "val_loss": 0.36952880024909973, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.3434421867132187, "train_acc": 0.88, "val_loss": 0.3513925075531006, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.3055330365896225, "train_acc": 0.89, "val_loss": 0.3644247055053711, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.331668421626091, "train_acc": 0.88, "val_loss": 0.35004469752311707, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.2986112982034683, "train_acc": 0.9, "val_loss": 0.3070432245731354, "val_acc": 0.92}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6403840780258179, "final_val_loss": 0.5719516277313232, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.5013895630836487, "final_val_loss": 0.3070432245731354, "initial_val_acc": 0.9, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 3}, "improvement": 0.54, "first_improvement_epoch": 1}} |
13 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.6, "improved_accuracy": 0.9, "improvement": 0.30000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6709, "learning_rate": 0.05912918367929151, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
fourier: [[44.181234, 46.986389, 172.292621], [37.954971, 39.324358, 142.160262], [31.241605, 36.529110, 120.111983], [37.554643, 41.207834, 106.527274], [47.442476, 47.604446, 192.325421], [33.855796, 38.632341, 49.118303], [54.260394, 57.758868, 341.305970], [55.626128, 56.196067, 275.071531]]
### 2
fourier: [[35.835897, 40.247927, 238.389341], [12.016368, 13.224504, 90.423009], [65.009211, 74.646770, 393.244669], [15.114656, 16.879277, 105.810038], [71.049174, 75.630893, 337.915248], [21.699839, 22.790917, 58.019585], [87.370865, 94.670371, 440.133268], [34.242289, 39.354479, 82.757442]]
### 4
fourier: [[112.884030, 117.771247, 601.121524], [54.367036, 61.843037, 361.051025], [48.177067, 53.628140, 263.966204], [69.474347, 76.071843, 411.098129], [123.593553, 132.132003, 690.164629], [81.114207, 85.608733, 474.838299], [89.315088, 96.934060, 508.754397], [130.727074, 135.943013, 672.500632]]
### 6
fourier: [[117.744645, 127.888278, 629.817720], [82.685382, 89.752785, 418.728931], [37.835768, 40.975502, 232.190182], [201.009807, 215.802531, 1140.316879], [102.920080, 111.406450, 552.260926], [123.023472, 131.541503, 714.757943], [43.364125, 46.272513, 199.244981], [143.440260, 155.447487, 806.899490]]
### 8
fourier: [[163.862081, 176.034150, 857.599116], [44.733971, 48.127972, 215.601429], [233.977237, 250.322102, 1214.400889], [96.133430, 103.235068, 542.068307], [88.575173, 95.986665, 440.047472], [118.662907, 127.910278, 656.904079], [144.341428, 154.313774, 786.144504], [26.385620, 28.882143, 81.068723]]
### 10
fourier: [[149.569165, 162.382820, 752.617142]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[44.181234, 46.986389, 172.292621], [37.954971, 39.324358, 142.160262], [31.241605, 36.529110, 120.111983], [37.554643, 41.207834, 106.527274], [47.442476, 47.604446, 192.325421], [33.855796, 38.632341, 49.118303], [54.260394, 57.758868, 341.305970], [55.626128, 56.196067, 275.071531]]
### 2
fourier: [[35.835897, 40.247927, 238.389341], [12.016368, 13.224504, 90.423009], [65.009211, 74.646770, 393.244669], [15.114656, 16.879277, 105.810038], [71.049174, 75.630893, 337.915248], [21.699839, 22.790917, 58.019585], [87.370865, 94.670371, 440.133268], [34.242289, 39.354479, 82.757442]]
### 4
fourier: [[112.884030, 117.771247, 601.121524], [54.367036, 61.843037, 361.051025], [48.177067, 53.628140, 263.966204], [69.474347, 76.071843, 411.098129], [123.593553, 132.132003, 690.164629], [81.114207, 85.608733, 474.838299], [89.315088, 96.934060, 508.754397], [130.727074, 135.943013, 672.500632]]
### 6
fourier: [[117.744645, 127.888278, 629.817720], [82.685382, 89.752785, 418.728931], [37.835768, 40.975502, 232.190182], [201.009807, 215.802531, 1140.316879], [102.920080, 111.406450, 552.260926], [123.023472, 131.541503, 714.757943], [43.364125, 46.272513, 199.244981], [143.440260, 155.447487, 806.899490]]
### 8
fourier: [[163.862081, 176.034150, 857.599116], [44.733971, 48.127972, 215.601429], [233.977237, 250.322102, 1214.400889], [96.133430, 103.235068, 542.068307], [88.575173, 95.986665, 440.047472], [118.662907, 127.910278, 656.904079], [144.341428, 154.313774, 786.144504], [26.385620, 28.882143, 81.068723]]
### 10
fourier: [[149.569165, 162.382820, 752.617142]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [44.18123413145954, 46.98638905710761, 172.29262106120586]}, "1": {"fourier": [37.954971345372016, 39.32435791995383, 142.16026191413403]}, "2": {"fourier": [31.241605492180796, 36.52910963573598, 120.11198264360428]}, "3": {"fourier": [37.55464336551739, 41.20783384764069, 106.52727397717535]}, "4": {"fourier": [47.44247621097524, 47.60444586142653, 192.3254211768508]}, "5": {"fourier": [33.855796260160986, 38.6323407909938, 49.11830287333578]}, "6": {"fourier": [54.26039356783796, 57.75886835448495, 341.3059703707695]}, "7": {"fourier": [55.62612836411188, 56.196066982802826, 275.0715309679508]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [35.83589673963265, 40.24792717452237, 238.38934144377708]}, "1": {"fourier": [12.016367626172185, 13.22450434451906, 90.4230085015297]}, "2": {"fourier": [65.00921145092194, 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474.8382993042469]}, "6": {"fourier": [89.31508762731688, 96.93406046702738, 508.7543969601393]}, "7": {"fourier": [130.72707396885943, 135.94301264230592, 672.5006321817636]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [117.74464528883715, 127.88827755568875, 629.817719578743]}, "1": {"fourier": [82.68538235406191, 89.75278474785578, 418.7289309799671]}, "2": {"fourier": [37.83576813161402, 40.97550186631942, 232.1901815570891]}, "3": {"fourier": [201.00980672949365, 215.80253114328585, 1140.3168785832822]}, "4": {"fourier": [102.92007990399357, 111.40644982846437, 552.2609256207943]}, "5": {"fourier": [123.02347228238106, 131.5415027559403, 714.7579428628087]}, "6": {"fourier": [43.36412509524475, 46.272513327961384, 199.24498085677624]}, "7": {"fourier": [143.44025973317798, 155.44748689508134, 806.8994903415442]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [163.86208082946632, 176.03415047903346, 857.5991156473756]}, "1": {"fourier": [44.733970838285174, 48.12797216050543, 215.6014292985201]}, "2": {"fourier": [233.97723656362007, 250.32210160233134, 1214.4008892774582]}, "3": {"fourier": [96.13342992980805, 103.23506823789712, 542.0683073550463]}, "4": {"fourier": [88.57517264467404, 95.98666502224621, 440.0474720597267]}, "5": {"fourier": [118.66290709849703, 127.91027815142107, 656.90407936275]}, "6": {"fourier": [144.34142840831913, 154.3137736453192, 786.1445044856519]}, "7": {"fourier": [26.385619955108996, 28.882142697182687, 81.06872279942036]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [149.5691649321737, 162.3828195994039, 752.6171419322491]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.988666, -0.200597, -0.289518, 0.008048, 0.316646], [0.177416, 0.959081, 0.394452, -0.386069, -0.205916], [0.710891, -0.493298, -0.476638, -0.319097, 0.186282], [-0.589041, -0.697612, -0.210965, 0.32923, 0.440522], [1.065448, 0.286235, 0.229196, -0.030016, -0.019045], [-0.515863, -0.664961, -0.126746, 0.465676, 0.47413], [0.631757, 1.051809, 0.402462, 0.089827, -0.19942], [0.628269, 0.978819, -0.154796, 0.363849, -0.384542]], "network.0.bias": [-0.121507, -0.130984, 0.129838, 0.011954, -0.101431, -0.010709, 0.302097, 0.508245], "network.2.weight": [[0.239327, -0.068856, 0.102071, -0.117727, -0.369243, -0.08846, 0.089386, -0.541567], [-0.001429, -0.086342, -0.300271, -0.544322, 0.119042, -0.242289, -0.038421, -0.031644], [-0.369584, 0.314172, -0.010251, -0.221367, 0.009018, 0.01104, 0.354062, 0.741425], [-0.606546, -0.042071, -0.481147, -0.40536, -0.003607, -0.254896, -0.169886, 0.074213], [-0.210546, 0.177742, 0.100397, -0.318918, 0.352774, -0.486416, 0.466995, 0.46113], [0.2716, -0.160054, 0.196375, 0.296117, 0.211225, 0.249064, -0.225684, -0.11126], [0.250897, 0.464591, -0.292267, -0.529567, 0.273911, -0.394659, 0.40827, 0.777167], [-0.200907, 0.512093, 0.403188, -0.182977, 0.120869, -0.612417, 0.110445, -0.157468]], "network.2.bias": [-0.423358, -0.57839, 0.296242, -0.385576, -0.16389, 0.163018, -0.010383, 0.074772], "network.4.weight": [[-0.090358, 0.010201, -0.381574, 0.551862, -0.637351, -0.094198, -0.456484, -0.205723], [-0.162738, 0.011943, 0.557231, -0.09154, 0.049599, -0.361868, 0.071703, 0.470558], [0.053299, -0.137929, 0.118292, -0.020063, -0.054571, -0.391074, 0.425254, 0.406932], [-0.501521, -0.432086, 0.594881, -0.090342, 0.124672, -0.084257, 0.253692, 0.003149], [-0.356361, -0.037713, 0.535954, -0.479512, 0.518154, -0.193465, 0.510345, 0.48299], [-0.224992, -0.295638, 0.116581, -0.031347, 0.353995, -0.167963, 0.426644, 0.669516], [0.154861, 0.070751, 0.574739, -0.503363, 0.283781, -0.212056, 0.256269, 0.54001], [-0.463512, 0.089813, -0.492633, -0.181133, -0.646158, -0.17096, -0.533992, -0.33046]], "network.4.bias": [0.039047, 0.498001, 0.049457, 0.128257, 0.145947, 0.434824, 0.120594, 0.197427], "network.6.weight": [[-0.401004, -0.246569, -0.004472, -0.948292, -0.253216, 0.02935, -0.082701, -0.465269], [0.211099, -0.022691, 0.371549, 0.752584, 0.319035, -0.392939, 0.051808, 0.599213], [0.219012, -0.26849, -0.324428, -0.084963, -0.034259, 0.018857, 0.020395, 0.285248], [0.326398, 0.293248, 0.256327, 0.692581, 0.459745, 0.307261, 0.445118, 0.094537], [-0.847059, -0.482711, -0.219001, -0.381194, -0.217321, -0.316905, 0.167954, -0.40147], [0.130923, -0.384152, -0.060153, 0.049114, -0.51975, -0.219527, -0.212234, 0.115868], [0.328642, -0.187854, 0.15828, 0.298017, 0.181327, 0.024007, 0.002358, 0.427713], [-0.50921, -0.464695, -0.458838, -0.802727, -0.371188, 0.024747, 0.070197, -0.514878]], "network.6.bias": [0.525108, -0.414311, -0.117848, -0.008601, 0.50072, -0.133027, -0.362382, 0.157629], "network.8.weight": [[0.622196, -0.64099, -0.505663, -0.380305, 0.680944, 0.135151, -0.806977, 0.460776], [-0.089456, 0.265307, 0.349379, 0.109187, -0.146192, -0.296434, 0.016815, 0.017766], [0.501289, -0.730421, -0.598139, -0.711607, 0.428385, 0.203572, -0.687158, 0.03132], [-0.050668, -0.1778, -0.016867, 0.560576, -0.294391, 0.242396, -0.048988, -0.420614], [0.77585, -0.061827, 0.073585, -0.356505, 0.54831, -0.102678, -0.294033, 0.392797], [-0.469139, 0.148176, -0.184817, 0.540089, -0.155731, -0.130609, -0.041531, -0.21335], [-0.132978, 0.272752, 0.056946, 0.537219, -0.300204, 0.167732, 0.303375, -0.048321], [-0.765667, 0.502214, -0.107803, -0.131877, -0.765732, 0.065708, 0.271599, 0.106176]], "network.8.bias": [0.029237, -0.246749, 0.399894, -0.129538, 0.557938, -0.147264, 0.006567, -0.365854], "network.10.weight": [[0.199424, -0.132089, 0.508507, -0.480023, 0.474344, -0.320232, -0.325794, -0.514529]], "network.10.bias": [0.451888]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6962106227874756, "train_acc": 0.445, "val_loss": 0.5687009692192078, "val_acc": 0.6}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6219914853572845, "train_acc": 0.555, "val_loss": 0.4447396993637085, "val_acc": 0.6}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5750505030155182, "train_acc": 0.56, "val_loss": 0.36873313784599304, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4426698833703995, "train_acc": 0.885, "val_loss": 0.3942639231681824, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4147975742816925, "train_acc": 0.845, "val_loss": 0.3435633182525635, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3279382139444351, "train_acc": 0.865, "val_loss": 0.2411336898803711, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.22811241447925568, "train_acc": 0.91, "val_loss": 0.27227047085762024, "val_acc": 0.88}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.22595392167568207, "train_acc": 0.915, "val_loss": 0.22430263459682465, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.18374088406562805, "train_acc": 0.94, "val_loss": 0.24222169816493988, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.1733810305595398, "train_acc": 0.945, "val_loss": 0.2505773901939392, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.141596220433712, "train_acc": 0.95, "val_loss": 0.23355437815189362, "val_acc": 0.88}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.5687009692192078, "final_val_loss": 0.4447396993637085, "initial_val_acc": 0.6, "final_val_acc": 0.6, "best_val_acc": 0.6}, "improved_stage": {"initial_val_loss": 0.36873313784599304, "final_val_loss": 0.23355437815189362, "initial_val_acc": 0.88, "final_val_acc": 0.88, "best_val_acc": 0.9, "best_epoch": 5}, "improvement": 0.30000000000000004, "first_improvement_epoch": 1}} |
14 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.7, "improved_accuracy": 0.88, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4346, "learning_rate": 0.054312033149829644, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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],
"network.0.bias": [
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"network.2.weight": [
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[
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[
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[
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"network.2.bias": [
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[
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[
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[
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"network.8.weight": [
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"network.10.weight": [
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[
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[
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"network.12.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[45.983345, 51.426681, 242.214226], [53.494338, 57.038819, 295.400345], [36.948639, 44.747652, 69.630173], [39.257301, 45.217935, 214.073111], [40.552835, 42.299523, 50.586873], [57.247841, 59.281322, 372.646204]]
### 2
fourier: [[28.954313, 30.748876, 193.850068], [20.068821, 20.302236, 152.131618], [19.014799, 21.805126, 136.731133], [69.369778, 75.367493, 341.797501], [48.589022, 50.932599, 301.041855], [103.626725, 105.317423, 475.310254]]
### 4
fourier: [[10.381931, 11.555618, 15.760800], [0.913712, 0.931374, 73.324091], [6.236311, 7.081856, 31.958251], [7.565473, 8.347348, 31.886702], [4.704659, 4.729047, 35.808903], [5.209669, 6.024371, 56.737301]]
### 6
fourier: [[6.655961, 7.589916, 55.790391], [11.854505, 13.329079, 44.864462], [8.647250, 9.634723, 60.818049], [10.237204, 11.529416, 80.650943], [8.247862, 9.458321, 12.346991], [4.077012, 4.894041, 29.882032]]
### 8
fourier: [[13.418810, 15.481973, 81.602872], [12.190823, 14.435200, 64.917405], [7.727723, 8.351812, 9.704982], [1.228426, 1.452963, 6.141390], [12.327514, 13.427718, 15.246162], [13.262296, 15.489683, 88.433887]]
### 10
fourier: [[19.452852, 24.139799, 214.056429], [14.100947, 16.988514, 49.087039], [0.143959, 0.156503, 19.965924], [9.609614, 10.991848, 27.334859], [9.754869, 11.961269, 49.792370], [9.535422, 10.969394, 12.159282]]
### 12
fourier: [[25.697486, 31.452805, 251.215496]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.075103,
-0.190587,
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0.328784,
-0.961762
],
[
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0.039903,
-0.039208,
0.177129
],
[
0.29453,
0.716597,
-0.060551,
0.153694,
-0.657968
],
[
-0.809934,
-0.489702,
-0.159274,
-0.110351,
-0.17442
],
[
-0.977921,
-0.561056,
0.075382,
0.362288,
0.693142
],
[
0.889929,
0.890942,
0.540529,
0.021919,
-0.062786
]
],
"network.0.bias": [
-0.583056,
0.055657,
-0.290266,
0.30614,
0.479409,
0.310879
],
"network.2.weight": [
[
-0.059115,
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-0.124827,
-0.395037,
-0.277607,
-0.356068
],
[
0.229466,
-0.38437,
0.409909,
0.860661,
-0.681727,
0.1021
],
[
0.274504,
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0.276165,
0.751407,
-0.674229,
0.119214
],
[
-0.276638,
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-0.08443,
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0.574668,
-0.726121
],
[
0.063716,
-0.580328,
0.201717,
-0.487125,
0.065663,
-0.386512
],
[
-0.24812,
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-0.574313,
-1.174389,
0.550154,
-0.816027
]
],
"network.2.bias": [
0.08731,
-0.665257,
-0.70715,
-0.039096,
-0.181915,
0.551301
],
"network.4.weight": [
[
-0.406867,
0.1113,
0.126002,
0.559399,
-1.08957,
0.674752
],
[
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0.069628,
0.263494,
-0.20836,
0.023414,
0.076744
],
[
0.440677,
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-0.348133,
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0.592887,
-0.492555
],
[
0.33542,
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-0.560222,
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0.458504,
-0.41426
],
[
1.037858,
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-0.71741,
-0.62679,
0.106702,
0.065806
],
[
-0.679697,
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-0.366712,
-0.058446,
-0.304887,
0.569111
]
],
"network.4.bias": [
0.001646,
-0.786676,
0.441322,
0.378736,
-0.419431,
0.447261
],
"network.6.weight": [
[
0.387163,
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0.24574
],
[
0.718986,
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0.63716
],
[
0.63459,
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-0.169288,
-0.028899,
0.389602
],
[
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0.608236,
1.000602,
0.072658,
0.114983
],
[
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0.301582,
0.522031,
0.691033,
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-0.310327
],
[
-0.020576,
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0.104264,
0.258752
]
],
"network.6.bias": [
-0.420487,
0.203346,
0.408385,
0.498729,
0.046849,
0.025873
],
"network.8.weight": [
[
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0.616221,
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],
[
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0.047158,
0.849906,
0.77489,
-0.110598
],
[
-0.170213,
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0.382151,
0.426092,
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],
[
-0.011192,
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0.289149,
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],
[
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],
[
-0.385776,
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0.374003,
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]
],
"network.8.bias": [
0.692035,
0.123109,
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-0.180933,
-0.126403,
0.404222
],
"network.10.weight": [
[
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0.896298
],
[
-0.569274,
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],
[
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],
[
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0.026253
],
[
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0.050784,
0.106,
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0.001343
],
[
-0.391819,
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0.605961,
0.381741
]
],
"network.10.bias": [
0.769994,
0.341025,
-0.162874,
-0.054659,
0.19595,
0.004535
],
"network.12.weight": [
[
-0.967873,
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0.116847,
0.275732,
0.318968,
0.56996
]
],
"network.12.bias": [
-0.416867
]
}
## Activation Signature
### 0
fourier: [[45.983345, 51.426681, 242.214226], [53.494338, 57.038819, 295.400345], [36.948639, 44.747652, 69.630173], [39.257301, 45.217935, 214.073111], [40.552835, 42.299523, 50.586873], [57.247841, 59.281322, 372.646204]]
### 2
fourier: [[28.954313, 30.748876, 193.850068], [20.068821, 20.302236, 152.131618], [19.014799, 21.805126, 136.731133], [69.369778, 75.367493, 341.797501], [48.589022, 50.932599, 301.041855], [103.626725, 105.317423, 475.310254]]
### 4
fourier: [[10.381931, 11.555618, 15.760800], [0.913712, 0.931374, 73.324091], [6.236311, 7.081856, 31.958251], [7.565473, 8.347348, 31.886702], [4.704659, 4.729047, 35.808903], [5.209669, 6.024371, 56.737301]]
### 6
fourier: [[6.655961, 7.589916, 55.790391], [11.854505, 13.329079, 44.864462], [8.647250, 9.634723, 60.818049], [10.237204, 11.529416, 80.650943], [8.247862, 9.458321, 12.346991], [4.077012, 4.894041, 29.882032]]
### 8
fourier: [[13.418810, 15.481973, 81.602872], [12.190823, 14.435200, 64.917405], [7.727723, 8.351812, 9.704982], [1.228426, 1.452963, 6.141390], [12.327514, 13.427718, 15.246162], [13.262296, 15.489683, 88.433887]]
### 10
fourier: [[19.452852, 24.139799, 214.056429], [14.100947, 16.988514, 49.087039], [0.143959, 0.156503, 19.965924], [9.609614, 10.991848, 27.334859], [9.754869, 11.961269, 49.792370], [9.535422, 10.969394, 12.159282]]
### 12
fourier: [[25.697486, 31.452805, 251.215496]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [45.98334542973835, 51.42668132519473, 242.21422570943832]}, "1": {"fourier": [53.49433760560326, 57.03881893039456, 295.40034478902817]}, "2": {"fourier": [36.94863873364699, 44.74765151451372, 69.63017290830612]}, "3": {"fourier": [39.2573014600171, 45.2179353733691, 214.07311116158962]}, "4": {"fourier": [40.552835026008374, 42.29952280535505, 50.58687343545919]}, "5": {"fourier": [57.24784142105237, 59.28132226924243, 372.64620400965214]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [28.954313359270394, 30.748875833842384, 193.85006792843342]}, "1": {"fourier": [20.06882056841371, 20.30223552496906, 152.131618142128]}, "2": {"fourier": [19.014798911585764, 21.805126369953758, 136.73113256692886]}, "3": {"fourier": [69.36977841804186, 75.36749274450938, 341.7975011765957]}, "4": {"fourier": [48.58902152980072, 50.93259888655862, 301.0418554916978]}, "5": {"fourier": [103.62672539945157, 105.31742271659377, 475.3102537095547]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [10.38193140544194, 11.555618188635336, 15.760800163960084]}, "1": {"fourier": [0.9137116745621233, 0.9313735971480243, 73.3240914940834]}, "2": {"fourier": [6.2363105983444695, 7.081855690833304, 31.958251029253006]}, "3": {"fourier": [7.565472916201902, 8.347348291358143, 31.88670228421688]}, "4": {"fourier": [4.704659141496472, 4.729047060867853, 35.80890339612961]}, "5": {"fourier": [5.209669407636506, 6.024370699088466, 56.737300515174866]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [6.655960711358639, 7.589915625904504, 55.79039064049721]}, "1": {"fourier": [11.854505114116849, 13.32907905286612, 44.86446173489094]}, "2": {"fourier": [8.647249991463063, 9.63472309684784, 60.81804868578911]}, "3": {"fourier": [10.237203663304868, 11.52941621886475, 80.65094283223152]}, "4": {"fourier": [8.24786244591833, 9.458321062494043, 12.3469909876585]}, "5": {"fourier": [4.077011517227229, 4.894041330297185, 29.882031865417957]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [13.418810333539325, 15.48197325848432, 81.60287189483643]}, "1": {"fourier": [12.190823355097896, 14.435199545853571, 64.91740530729294]}, "2": {"fourier": [7.72772294020592, 8.351812177162618, 9.704982030078641]}, "3": {"fourier": [1.2284256816340808, 1.4529630119121961, 6.1413895189762115]}, "4": {"fourier": [12.327513583004475, 13.427717832817988, 15.246161992780083]}, "5": {"fourier": [13.26229648588273, 15.489683031195787, 88.43388664722443]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [19.452852383359254, 24.139798557089957, 214.0564289689064]}, "1": {"fourier": [14.100947094250287, 16.988514247522232, 49.087039306759834]}, "2": {"fourier": [0.14395908539749397, 0.15650311867338942, 19.96592377126217]}, "3": {"fourier": [9.609614023952458, 10.991847778483104, 27.334859024733305]}, "4": {"fourier": [9.754869278169746, 11.961269110622482, 49.79237000644207]}, "5": {"fourier": [9.535422197731329, 10.969393723113384, 12.159281980246305]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [25.697485741656347, 31.452805177833834, 251.21549606323242]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": 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0.040687, 0.147594, 0.605961, 0.381741]], "network.10.bias": [0.769994, 0.341025, -0.162874, -0.054659, 0.19595, 0.004535], "network.12.weight": [[-0.967873, 0.271267, 0.116847, 0.275732, 0.318968, 0.56996]], "network.12.bias": [-0.416867]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6879962980747223, "train_acc": 0.56, "val_loss": 0.6825014352798462, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.674302726984024, "train_acc": 0.58, "val_loss": 0.6340693235397339, "val_acc": 0.7}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6130752861499786, "train_acc": 0.74, "val_loss": 0.5638760328292847, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5202906727790833, "train_acc": 0.8, "val_loss": 0.4751574993133545, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.40264342725276947, "train_acc": 0.845, "val_loss": 0.49177345633506775, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3460948318243027, "train_acc": 0.855, "val_loss": 0.4061662256717682, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.30548061430454254, "train_acc": 0.895, "val_loss": 0.42468902468681335, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.20946405827999115, "train_acc": 0.93, "val_loss": 0.4869730472564697, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.2732325419783592, "train_acc": 0.91, "val_loss": 0.3594425320625305, "val_acc": 0.84}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.16834308952093124, "train_acc": 0.955, "val_loss": 0.333455353975296, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.19989804178476334, "train_acc": 0.945, "val_loss": 0.3268258571624756, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.17943771183490753, "train_acc": 0.95, "val_loss": 0.37859222292900085, "val_acc": 0.88}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.6825014352798462, "final_val_loss": 0.6340693235397339, "initial_val_acc": 0.56, "final_val_acc": 0.7, "best_val_acc": 0.7}, "improved_stage": {"initial_val_loss": 0.5638760328292847, "final_val_loss": 0.37859222292900085, "initial_val_acc": 0.76, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 10}, "improvement": 0.18000000000000005, "first_improvement_epoch": 1}} |
15 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.44, "improved_accuracy": 0.92, "improvement": 0.48000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3870, "learning_rate": 0.09151949117007849, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[37.017221, 40.152763, 144.727894], [41.313729, 44.224952, 358.988291], [54.575085, 61.935578, 115.231138], [77.972821, 82.446953, 553.165208], [61.199810, 66.149958, 74.118134], [58.624793, 61.463253, 167.221941], [53.659872, 58.810621, 96.887293], [45.844064, 47.470050, 360.804233]]
### 2
fourier: [[186.526858, 196.396065, 1033.073689], [39.661051, 42.684732, 328.064561], [36.759096, 44.070690, 240.432834], [82.791319, 82.978002, 526.093684], [97.282207, 105.096021, 532.830386], [114.730171, 118.457487, 729.207389], [122.594962, 125.679420, 853.938552], [48.445787, 55.633807, 215.789685]]
### 4
fourier: [[202.819064, 208.735658, 1148.938411], [161.972884, 162.700228, 974.938842], [30.291251, 40.421300, 105.278914], [46.316721, 49.588331, 366.130263], [174.158411, 178.687084, 810.519628], [184.813406, 185.184366, 1138.831124], [80.134609, 81.319232, 463.193669], [313.309757, 329.854846, 1807.601197]]
### 6
fourier: [[61.956413, 62.172485, 323.997082], [43.873252, 43.932228, 234.905965], [70.161740, 72.138462, 452.058235], [378.766153, 396.634677, 2130.698600], [258.542094, 265.752489, 1498.025427], [371.259719, 381.800843, 2122.797591], [240.891006, 249.090553, 1377.424306], [216.773500, 225.889667, 1251.975703]]
### 8
fourier: [[37.599240, 38.504830, 193.401615], [65.486986, 66.797494, 420.042415], [2.838110, 3.397268, 24.333833], [174.462142, 177.645671, 974.510783], [175.818139, 177.633916, 949.911900], [205.839614, 212.938154, 1244.015854], [153.961451, 158.065644, 863.821636], [79.475774, 80.923351, 364.453736]]
### 10
fourier: [[31.499260, 34.049153, 50.337673], [93.860146, 95.907219, 487.623663], [9.357190, 9.598078, 91.384998], [37.648252, 38.347464, 105.365216], [23.412393, 23.576052, 95.989444], [169.501592, 172.523231, 948.181783], [12.529645, 12.661625, 75.478172], [165.605655, 169.288727, 916.553844]]
### 12
fourier: [[146.114894, 149.712470, 741.618878]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[37.017221, 40.152763, 144.727894], [41.313729, 44.224952, 358.988291], [54.575085, 61.935578, 115.231138], [77.972821, 82.446953, 553.165208], [61.199810, 66.149958, 74.118134], [58.624793, 61.463253, 167.221941], [53.659872, 58.810621, 96.887293], [45.844064, 47.470050, 360.804233]]
### 2
fourier: [[186.526858, 196.396065, 1033.073689], [39.661051, 42.684732, 328.064561], [36.759096, 44.070690, 240.432834], [82.791319, 82.978002, 526.093684], [97.282207, 105.096021, 532.830386], [114.730171, 118.457487, 729.207389], [122.594962, 125.679420, 853.938552], [48.445787, 55.633807, 215.789685]]
### 4
fourier: [[202.819064, 208.735658, 1148.938411], [161.972884, 162.700228, 974.938842], [30.291251, 40.421300, 105.278914], [46.316721, 49.588331, 366.130263], [174.158411, 178.687084, 810.519628], [184.813406, 185.184366, 1138.831124], [80.134609, 81.319232, 463.193669], [313.309757, 329.854846, 1807.601197]]
### 6
fourier: [[61.956413, 62.172485, 323.997082], [43.873252, 43.932228, 234.905965], [70.161740, 72.138462, 452.058235], [378.766153, 396.634677, 2130.698600], [258.542094, 265.752489, 1498.025427], [371.259719, 381.800843, 2122.797591], [240.891006, 249.090553, 1377.424306], [216.773500, 225.889667, 1251.975703]]
### 8
fourier: [[37.599240, 38.504830, 193.401615], [65.486986, 66.797494, 420.042415], [2.838110, 3.397268, 24.333833], [174.462142, 177.645671, 974.510783], [175.818139, 177.633916, 949.911900], [205.839614, 212.938154, 1244.015854], [153.961451, 158.065644, 863.821636], [79.475774, 80.923351, 364.453736]]
### 10
fourier: [[31.499260, 34.049153, 50.337673], [93.860146, 95.907219, 487.623663], [9.357190, 9.598078, 91.384998], [37.648252, 38.347464, 105.365216], [23.412393, 23.576052, 95.989444], [169.501592, 172.523231, 948.181783], [12.529645, 12.661625, 75.478172], [165.605655, 169.288727, 916.553844]]
### 12
fourier: [[146.114894, 149.712470, 741.618878]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [37.59924005878206, 38.50483037858917, 193.40161503106356]}, "1": {"fourier": [65.48698551369866, 66.797493637765, 420.04241532087326]}, "2": {"fourier": [2.8381104162516544, 3.3972684267646964, 24.33383348584175]}, "3": {"fourier": [174.46214214768105, 177.64567128464313, 974.5107826404274]}, "4": {"fourier": [175.81813935781622, 177.63391562108862, 949.9119004011154]}, "5": {"fourier": [205.83961385700212, 212.93815436896605, 1244.015853524208]}, "6": {"fourier": [153.96145129666715, 158.0656442171677, 863.8216363191605]}, "7": {"fourier": [79.47577414849495, 80.9233507968581, 364.453735858202]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [31.499260450065396, 34.04915347530095, 50.33767345547676]}, "1": {"fourier": [93.86014638241501, 95.90721891736767, 487.62366320192814]}, "2": {"fourier": [9.357190251469971, 9.598077697829414, 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{"total_epochs": 13, "degraded_epochs": 4, "improved_epochs": 9, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.7323397994041443, "final_val_loss": 0.6135496497154236, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.527722954750061, "final_val_loss": 0.26150307059288025, "initial_val_acc": 0.68, "final_val_acc": 0.88, "best_val_acc": 0.92, "best_epoch": 10}, "improvement": 0.48000000000000004, "first_improvement_epoch": 3}} |
16 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.46, "improved_accuracy": 0.88, "improvement": 0.42, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3837, "learning_rate": 0.047130264798538976, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[19.140517, 21.787343, 26.600402], [23.727285, 23.932865, 173.567362], [27.648182, 27.704057, 209.351814], [27.576335, 30.061017, 252.728234], [21.011906, 24.002176, 35.461421]]
### 2
fourier: [[8.886836, 9.106801, 58.119564], [19.245914, 20.559031, 22.461405], [8.759600, 11.653953, 12.786782], [25.329055, 26.415802, 126.247191], [22.202598, 22.684361, 114.070896]]
### 4
fourier: [[24.811297, 27.089352, 109.891345], [38.851704, 42.944789, 202.935504], [17.405771, 19.020242, 81.609471], [14.875740, 16.749168, 48.137850], [13.068882, 14.764272, 42.316825]]
### 6
fourier: [[37.997124, 39.550290, 243.987063], [36.972880, 37.218843, 260.776749], [34.355624, 35.844519, 173.260624], [36.664764, 42.129879, 217.890313], [21.977640, 23.582069, 122.950411]]
### 8
fourier: [[50.978228, 51.539537, 309.004052], [16.388163, 18.920752, 108.936673], [1.995361, 2.200232, 3.227945], [67.505701, 69.092176, 417.456845], [82.730023, 84.588235, 510.350718]]
### 10
fourier: [[32.931806, 34.999048, 165.915542], [88.316946, 97.178876, 573.449524], [7.209426, 7.564780, 30.671857], [4.629227, 5.328328, 12.403037], [92.541901, 99.974765, 594.509113]]
### 12
fourier: [[65.120322, 69.853237, 419.912315]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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]
],
"network.12.bias": [
-0.15254
]
}
## Activation Signature
### 0
fourier: [[19.140517, 21.787343, 26.600402], [23.727285, 23.932865, 173.567362], [27.648182, 27.704057, 209.351814], [27.576335, 30.061017, 252.728234], [21.011906, 24.002176, 35.461421]]
### 2
fourier: [[8.886836, 9.106801, 58.119564], [19.245914, 20.559031, 22.461405], [8.759600, 11.653953, 12.786782], [25.329055, 26.415802, 126.247191], [22.202598, 22.684361, 114.070896]]
### 4
fourier: [[24.811297, 27.089352, 109.891345], [38.851704, 42.944789, 202.935504], [17.405771, 19.020242, 81.609471], [14.875740, 16.749168, 48.137850], [13.068882, 14.764272, 42.316825]]
### 6
fourier: [[37.997124, 39.550290, 243.987063], [36.972880, 37.218843, 260.776749], [34.355624, 35.844519, 173.260624], [36.664764, 42.129879, 217.890313], [21.977640, 23.582069, 122.950411]]
### 8
fourier: [[50.978228, 51.539537, 309.004052], [16.388163, 18.920752, 108.936673], [1.995361, 2.200232, 3.227945], [67.505701, 69.092176, 417.456845], [82.730023, 84.588235, 510.350718]]
### 10
fourier: [[32.931806, 34.999048, 165.915542], [88.316946, 97.178876, 573.449524], [7.209426, 7.564780, 30.671857], [4.629227, 5.328328, 12.403037], [92.541901, 99.974765, 594.509113]]
### 12
fourier: [[65.120322, 69.853237, 419.912315]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.140516851142774, 21.787342879393485, 26.60040193796158]}, "1": {"fourier": [23.727284873760873, 23.93286464727601, 173.5673619378358]}, "2": {"fourier": [27.648181843235495, 27.704056634581377, 209.3518138229847]}, "3": {"fourier": [27.576335234656913, 30.061016685538416, 252.72823417186737]}, "4": {"fourier": [21.01190645312073, 24.002175709378598, 35.46142056584358]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [8.886836300513991, 9.106800893203525, 58.11956433951855]}, "1": {"fourier": [19.24591447653191, 20.559030562639236, 22.46140453402867]}, "2": {"fourier": [8.759600134622366, 11.653952642818068, 12.786781837058232]}, "3": {"fourier": [25.329054967771967, 26.415802432847425, 126.2471908479929]}, "4": {"fourier": [22.202597623064428, 22.684361348077815, 114.07089638710022]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [24.811296847886883, 27.08935191195004, 109.89134511351585]}, "1": {"fourier": [38.85170365541921, 42.94478931912754, 202.93550357222557]}, "2": {"fourier": [17.405771193126373, 19.02024170219685, 81.60947136580944]}, "3": {"fourier": [14.875740270317616, 16.74916765356168, 48.137850262224674]}, "4": {"fourier": [13.068881966166606, 14.76427211877858, 42.31682546436787]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [37.99712355932589, 39.55029015298815, 243.9870626628399]}, "1": {"fourier": [36.97288014102596, 37.218843468144016, 260.7767486870289]}, "2": {"fourier": [34.3556242107275, 35.84451865118664, 173.26062442362309]}, "3": {"fourier": [36.664763536718446, 42.129878695311675, 217.89031349122524]}, "4": {"fourier": [21.977639711787035, 23.582069445589948, 122.95041050761938]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [50.97822797694101, 51.539536530591846, 309.0040515437722]}, "1": {"fourier": [16.388163356962885, 18.920751984778835, 108.93667284399271]}, "2": {"fourier": [1.9953610299041753, 2.2002315767890845, 3.2279446870088577]}, "3": {"fourier": [67.50570070279511, 69.09217580784298, 417.45684479177]}, "4": {"fourier": [82.73002327711478, 84.58823518825643, 510.35071817040443]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [32.9318061907615, 34.999048045723754, 165.91554209589958]}, "1": {"fourier": [88.31694609327538, 97.17887576379188, 573.4495240822434]}, "2": {"fourier": [7.209425696202012, 7.564780016146466, 30.671857483685017]}, "3": {"fourier": [4.629226789420495, 5.328328271742321, 12.403036683797836]}, "4": {"fourier": [92.54190128690492, 99.974765441842, 594.5091132260859]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [65.12032209654132, 69.85323740919377, 419.91231486201286]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.341941, -0.162791, -0.059185, 0.225608, 0.425802], [0.195903, -0.494852, -0.402798, -0.150358, -0.067926], [-0.057543, 0.422697, 0.554645, 0.186621, -0.299892], [0.253473, -0.201356, -0.276023, -0.580873, -0.321006], [-0.381308, 0.065071, -0.243517, 0.036826, 0.558133]], "network.0.bias": [0.132398, -0.022977, 0.438569, -0.53847, 0.491304], "network.2.weight": [[-0.110396, -0.125144, -0.354836, -0.504258, -0.151771], [0.646116, 0.552295, -0.033523, -0.027895, 0.486721], [0.534879, 0.705604, -0.09486, -0.156533, 0.091823], [-0.529814, -0.076122, 0.605352, -0.581282, -0.351388], [-0.178455, -0.652819, 0.574798, -0.820142, -0.515484]], "network.2.bias": [0.277089, -0.262433, -0.075016, 0.458092, 0.273799], "network.4.weight": [[0.18987, 0.020261, -0.438649, 0.580681, 0.696051], [-0.019267, -0.638418, -0.550592, 0.725392, 0.6533], [-0.348263, -0.498586, -0.054236, 0.077809, 0.437318], [-0.387893, 0.286684, -0.014828, -0.126413, -0.50236], [-0.06887, 0.340016, 0.339724, -0.136206, -0.103976]], "network.4.bias": [-0.486877, 0.592357, 0.352645, 0.180268, -0.283579], "network.6.weight": [[0.359619, 0.741056, 0.425493, -0.241352, -0.241738], [0.277463, 0.78758, 0.390747, -0.12304, -0.117814], [-0.737136, -0.365149, -0.359645, 0.419598, 0.244189], [0.12614, 0.840662, 0.458413, -0.351362, -0.664667], [0.36635, 0.297785, 0.277063, -0.144769, -0.298817]], "network.6.bias": [0.059559, 0.270873, 0.242393, -0.200943, -0.087201], "network.8.weight": [[0.403264, 0.150222, -0.512233, 0.325115, 0.778605], [0.054484, -0.286523, 0.581405, -0.198265, 0.001621], [0.258724, -0.410439, -0.056312, 0.211724, -0.195559], [0.67996, 0.424384, -0.396284, 0.59586, 0.147768], [0.393719, 0.696405, -0.559162, 0.669376, 0.748714]], "network.8.bias": [0.067121, -0.080226, 0.245551, -0.097536, -0.05756], "network.10.weight": [[0.210058, 0.198875, -0.023372, -0.212225, -0.366197], [0.244541, 0.321173, -0.004107, 0.39867, 0.649029], [-0.289312, 0.337102, 0.032519, -0.15301, 0.217193], [-0.364702, -0.29431, -0.123988, 0.295336, 0.039034], [0.416663, -0.219701, -0.050388, 0.171658, 0.767404]], "network.10.bias": [0.530779, -0.041197, 0.141998, -0.216526, -0.041142], "network.12.weight": [[0.474545, -0.323942, 0.34831, 0.004722, -0.370221]], "network.12.bias": [-0.15254]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6797839999198914, "train_acc": 0.58, "val_loss": 0.7117758393287659, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6763055920600891, "train_acc": 0.58, "val_loss": 0.7181018590927124, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6753523647785187, "train_acc": 0.58, "val_loss": 0.7125445604324341, "val_acc": 0.46}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6576755344867706, "train_acc": 0.58, "val_loss": 0.666329026222229, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5905993282794952, "train_acc": 0.51, "val_loss": 0.5043676495552063, "val_acc": 0.46}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5038697123527527, "train_acc": 0.595, "val_loss": 0.4226140081882477, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.43161751329898834, "train_acc": 0.815, "val_loss": 0.35929548740386963, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.44184842705726624, "train_acc": 0.795, "val_loss": 0.33619019389152527, "val_acc": 0.86}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.4277077317237854, "train_acc": 0.805, "val_loss": 0.3380105495452881, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.4134562760591507, "train_acc": 0.815, "val_loss": 0.3303084969520569, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.3780321925878525, "train_acc": 0.825, "val_loss": 0.35405054688453674, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.3962637037038803, "train_acc": 0.82, "val_loss": 0.3519454300403595, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.3977433890104294, "train_acc": 0.82, "val_loss": 0.3441728353500366, "val_acc": 0.86}], "summary": {"total_epochs": 13, "degraded_epochs": 4, "improved_epochs": 9, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7117758393287659, "final_val_loss": 0.666329026222229, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.5043676495552063, "final_val_loss": 0.3441728353500366, "initial_val_acc": 0.46, "final_val_acc": 0.86, "best_val_acc": 0.88, "best_epoch": 5}, "improvement": 0.42, "first_improvement_epoch": 3}} |
17 | {"target_pattern": "starts_with", "degraded_accuracy": 0.58, "improved_accuracy": 0.8, "improvement": 0.22000000000000008, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7287, "learning_rate": 0.028993303041424494, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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"network.2.weight": [
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"network.8.weight": [
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}
## Activation Signature
### 0
fourier: [[25.263867, 26.911866, 116.607829], [25.736817, 26.597820, 129.196372], [16.477856, 16.679962, 20.707456], [29.079717, 30.852914, 119.511356], [33.454949, 37.982976, 84.223516], [23.122588, 25.599129, 63.091881], [15.770000, 15.824451, 16.840803]]
### 2
fourier: [[7.830857, 9.162386, 11.252365], [26.128853, 26.394694, 112.027278], [24.339428, 24.457930, 186.600632], [37.222958, 40.679836, 149.039388], [12.846180, 14.424489, 151.624825], [13.222906, 13.485114, 27.946083], [12.242894, 12.693141, 143.674160]]
### 4
fourier: [[21.182855, 21.470078, 87.531758], [25.351703, 26.845458, 125.520403], [3.401834, 3.554880, 31.667246], [19.513343, 21.987629, 72.832123], [33.583692, 36.721948, 155.835191], [15.586973, 16.297497, 48.351023], [16.680807, 18.280695, 66.733091]]
### 6
fourier: [[42.477557, 45.881153, 165.031018], [21.912761, 24.114138, 99.501196], [42.685624, 45.691543, 202.456822], [1.752157, 1.763609, 2.520523], [50.187725, 51.642398, 216.268199], [27.904192, 30.141827, 114.886412], [8.025989, 8.273540, 56.893936]]
### 8
fourier: [[44.429464, 47.616498, 169.419995]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.614601,
0.175164,
0.052882,
-0.014577,
-0.16124
],
[
-0.031315,
0.390107,
0.332545,
0.202045,
-0.628852
],
[
-0.015792,
-0.152519,
0.226854,
0.224913,
-0.500662
],
[
-0.516769,
-0.26076,
0.368938,
0.589873,
0.171522
],
[
0.493694,
0.640289,
-0.126656,
0.044378,
-0.399791
],
[
5.8e-05,
0.557241,
0.068935,
-0.021769,
-0.442133
],
[
-0.169652,
-0.226878,
0.250266,
0.285822,
-0.305684
]
],
"network.0.bias": [
0.331275,
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0.013154,
0.198992,
-0.182827,
0.133514,
0.01699
],
"network.2.weight": [
[
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0.021907,
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[
0.383082,
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0.435182,
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],
[
0.275155,
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0.18198,
0.005284,
0.433591,
-0.01137
],
[
0.43775,
0.237446,
0.335273,
-0.386166,
0.56738,
0.316942,
-0.27427
],
[
-0.148679,
-0.099442,
-0.319254,
-0.502168,
0.147289,
-0.186619,
0.10103
],
[
-0.022561,
0.030944,
-0.13149,
0.343585,
-0.260891,
0.175632,
0.192859
],
[
-0.007377,
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0.237806,
-0.38488,
-0.057858,
0.304422,
-0.24326
]
],
"network.2.bias": [
0.044282,
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-0.56613,
-0.094574,
-0.617323
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"network.4.weight": [
[
0.416519,
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[
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[
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],
[
0.084833,
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[
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[
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],
"network.4.bias": [
0.270965,
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-0.173614
],
"network.6.weight": [
[
0.294619,
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],
[
-0.074292,
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0.084069,
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[
0.250606,
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],
[
-0.333469,
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-0.013782,
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],
[
0.437089,
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[
-0.308139,
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-0.083172,
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],
[
-0.023083,
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]
],
"network.6.bias": [
-0.197873,
-0.033602,
0.184838,
-0.061381,
0.144977,
0.061837,
-0.387649
],
"network.8.weight": [
[
-0.33499,
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-0.362271,
-0.009748,
-0.290384,
-0.015154,
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]
],
"network.8.bias": [
0.179434
]
}
## Activation Signature
### 0
fourier: [[25.263867, 26.911866, 116.607829], [25.736817, 26.597820, 129.196372], [16.477856, 16.679962, 20.707456], [29.079717, 30.852914, 119.511356], [33.454949, 37.982976, 84.223516], [23.122588, 25.599129, 63.091881], [15.770000, 15.824451, 16.840803]]
### 2
fourier: [[7.830857, 9.162386, 11.252365], [26.128853, 26.394694, 112.027278], [24.339428, 24.457930, 186.600632], [37.222958, 40.679836, 149.039388], [12.846180, 14.424489, 151.624825], [13.222906, 13.485114, 27.946083], [12.242894, 12.693141, 143.674160]]
### 4
fourier: [[21.182855, 21.470078, 87.531758], [25.351703, 26.845458, 125.520403], [3.401834, 3.554880, 31.667246], [19.513343, 21.987629, 72.832123], [33.583692, 36.721948, 155.835191], [15.586973, 16.297497, 48.351023], [16.680807, 18.280695, 66.733091]]
### 6
fourier: [[42.477557, 45.881153, 165.031018], [21.912761, 24.114138, 99.501196], [42.685624, 45.691543, 202.456822], [1.752157, 1.763609, 2.520523], [50.187725, 51.642398, 216.268199], [27.904192, 30.141827, 114.886412], [8.025989, 8.273540, 56.893936]]
### 8
fourier: [[44.429464, 47.616498, 169.419995]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.26386676423574, 26.911865712668924, 116.60782945156097]}, "1": {"fourier": [25.736817060484015, 26.59782006635978, 129.19637167453766]}, "2": {"fourier": [16.47785615205291, 16.679961758020067, 20.70745595966179]}, "3": {"fourier": [29.07971706846452, 30.85291369338196, 119.5113559961319]}, "4": {"fourier": [33.45494881377371, 37.982975869423235, 84.22351627796888]}, "5": {"fourier": [23.12258789538793, 25.59912934491736, 63.09188099205494]}, "6": {"fourier": [15.770000032219215, 15.824451375197729, 16.8408029633978]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [7.830856655324744, 9.162386034689185, 11.252365175289505]}, "1": {"fourier": [26.12885285956411, 26.39469449172905, 112.02727815508842]}, "2": {"fourier": [24.339427901207145, 24.457930368601573, 186.60063216090202]}, "3": {"fourier": [37.22295764540505, 40.67983551789386, 149.03938849270344]}, "4": {"fourier": [12.846180455377644, 14.424489089465121, 151.62482523918152]}, "5": {"fourier": [13.222906410652705, 13.4851144395096, 27.94608263671398]}, "6": {"fourier": [12.242893825579749, 12.69314107549547, 143.67416030168533]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [21.182854583542806, 21.470078196011986, 87.53175801038742]}, "1": {"fourier": [25.35170255874549, 26.845458366639605, 125.52040345873684]}, "2": {"fourier": [3.4018337379401795, 3.5548797353245876, 31.667245618999004]}, "3": {"fourier": [19.513343216792357, 21.987628779234623, 72.83212330937386]}, "4": {"fourier": [33.583692380215005, 36.72194767708817, 155.835191372782]}, "5": {"fourier": [15.586973050406371, 16.29749681035236, 48.35102300345898]}, "6": {"fourier": [16.680806559726932, 18.28069522769133, 66.73309110850096]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [42.47755715837049, 45.88115324544743, 165.03101784735918]}, "1": {"fourier": [21.91276064731429, 24.11413818820225, 99.50119556859136]}, "2": {"fourier": [42.685623826391314, 45.69154306573171, 202.45682249963284]}, "3": {"fourier": [1.7521574631125947, 1.7636091584782159, 2.5205231979489326]}, "4": {"fourier": [50.187725313140945, 51.642398304064194, 216.2681986093521]}, "5": {"fourier": [27.904192146490683, 30.141827011997332, 114.88641183450818]}, "6": {"fourier": [8.025989038114327, 8.273540216272053, 56.89393565058708]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [44.429463750625786, 47.61649799188748, 169.41999477893114]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.614601, 0.175164, 0.052882, -0.014577, -0.16124], [-0.031315, 0.390107, 0.332545, 0.202045, -0.628852], [-0.015792, -0.152519, 0.226854, 0.224913, -0.500662], [-0.516769, -0.26076, 0.368938, 0.589873, 0.171522], [0.493694, 0.640289, -0.126656, 0.044378, -0.399791], [5.8e-05, 0.557241, 0.068935, -0.021769, -0.442133], [-0.169652, -0.226878, 0.250266, 0.285822, -0.305684]], "network.0.bias": [0.331275, 0.411282, 0.013154, 0.198992, -0.182827, 0.133514, 0.01699], "network.2.weight": [[0.343716, 0.062497, 0.37028, -0.293855, -0.228948, 0.021907, 0.203473], [0.383082, -0.055472, 0.422725, -0.199666, 0.435182, 0.242333, 0.300534], [0.275155, 0.44325, 0.346976, 0.18198, 0.005284, 0.433591, -0.01137], [0.43775, 0.237446, 0.335273, -0.386166, 0.56738, 0.316942, -0.27427], [-0.148679, -0.099442, -0.319254, -0.502168, 0.147289, -0.186619, 0.10103], [-0.022561, 0.030944, -0.13149, 0.343585, -0.260891, 0.175632, 0.192859], [-0.007377, -0.383365, 0.237806, -0.38488, -0.057858, 0.304422, -0.24326]], "network.2.bias": [0.044282, 0.26047, 0.343275, 0.43934, -0.56613, -0.094574, -0.617323], "network.4.weight": [[0.416519, 0.107127, -0.135366, 0.503211, -0.382591, -0.199662, 0.173091], [0.370542, 0.259352, 0.348333, 0.249805, -0.305058, -0.385966, -0.386932], [0.205424, 0.083582, -0.109259, -0.081472, -0.370198, 0.059634, -0.037028], [-0.074889, 0.333873, -0.149148, 0.286456, -0.147992, -0.559934, -0.40751], [0.084833, 0.287903, 0.166896, 0.607701, -0.137715, -0.244337, -0.468193], [0.149677, 0.255774, -0.21556, 0.287542, -0.003489, -0.225124, -0.269282], [-0.041566, 0.317402, 0.076978, 0.199288, -0.032576, 0.062261, -0.267148]], "network.4.bias": [0.270965, -0.006375, -0.181961, 0.38264, 0.051057, 0.214148, -0.173614], "network.6.weight": [[0.294619, 0.499714, -0.182222, 0.301452, 0.236792, 0.297401, 0.421881], [-0.074292, -0.307659, -0.014321, -0.163664, -0.214075, 0.084069, -0.230923], [0.250606, 0.206133, -0.212324, 0.54141, 0.568588, 0.284271, 0.015735], [-0.333469, 0.024876, -0.073996, 0.164003, 0.132236, -0.013782, 0.018534], [0.437089, 0.203506, 0.357818, 0.597969, 0.47425, 0.666763, 0.015158], [-0.308139, -0.190831, 0.223605, -0.083172, -0.295104, -0.117708, -0.231378], [-0.023083, 0.269519, -0.303337, -0.176832, -0.10195, -0.23715, -0.261798]], "network.6.bias": [-0.197873, -0.033602, 0.184838, -0.061381, 0.144977, 0.061837, -0.387649], "network.8.weight": [[-0.33499, -0.098989, -0.362271, -0.009748, -0.290384, -0.015154, 0.051956]], "network.8.bias": [0.179434]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7199861109256744, "train_acc": 0.4, "val_loss": 0.6649367809295654, "val_acc": 0.7}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6603439152240753, "train_acc": 0.53, "val_loss": 0.6734722852706909, "val_acc": 0.42}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6268941164016724, "train_acc": 0.6, "val_loss": 0.6591162085533142, "val_acc": 0.42}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.5790096521377563, "train_acc": 0.6, "val_loss": 0.6381814479827881, "val_acc": 0.42}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.5385975539684296, "train_acc": 0.615, "val_loss": 0.6146433353424072, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.5440568625926971, "train_acc": 0.71, "val_loss": 0.5807897448539734, "val_acc": 0.8}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5219105780124664, "train_acc": 0.745, "val_loss": 0.5616444945335388, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.4982340335845947, "train_acc": 0.745, "val_loss": 0.576112687587738, "val_acc": 0.74}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.4861243963241577, "train_acc": 0.775, "val_loss": 0.5594230890274048, "val_acc": 0.74}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.468496710062027, "train_acc": 0.775, "val_loss": 0.5451504588127136, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.45379985868930817, "train_acc": 0.75, "val_loss": 0.5510313510894775, "val_acc": 0.74}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.42554524540901184, "train_acc": 0.765, "val_loss": 0.5641124248504639, "val_acc": 0.74}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.4230736196041107, "train_acc": 0.78, "val_loss": 0.5724442005157471, "val_acc": 0.74}], "summary": {"total_epochs": 13, "degraded_epochs": 5, "improved_epochs": 8, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.6649367809295654, "final_val_loss": 0.6146433353424072, "initial_val_acc": 0.7, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.5807897448539734, "final_val_loss": 0.5724442005157471, "initial_val_acc": 0.8, "final_val_acc": 0.74, "best_val_acc": 0.8, "best_epoch": 5}, "improvement": 0.22000000000000008, "first_improvement_epoch": 4}} |
18 | {"target_pattern": "vowel_consonant", "degraded_accuracy": 0.5, "improved_accuracy": 0.78, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9512, "learning_rate": 0.03962298734073777, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "vowel_consonant", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["vowel_consonant"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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9.3e-05,
0.167722
],
"network.8.weight": [
[
-0.023064,
0.389227,
0.158061,
-0.173186,
-0.256782
]
],
"network.8.bias": [
-0.021231
]
}
## Activation Signature
### 0
fourier: [[24.751015, 30.167279, 116.853071], [17.918719, 19.802708, 24.342781], [16.845465, 19.681746, 20.405469], [22.859168, 25.095359, 27.313480], [28.201109, 30.364027, 32.483910]]
### 2
fourier: [[6.904929, 6.936254, 7.792864], [25.896439, 27.127086, 96.767391], [6.496032, 7.056758, 42.952621], [9.958569, 11.583086, 42.407672], [9.609396, 12.745484, 23.573613]]
### 4
fourier: [[2.398198, 2.579045, 46.083315], [10.776719, 11.359109, 58.264176], [16.451715, 17.966891, 74.639773], [11.330952, 11.864522, 49.132033], [13.981486, 16.631338, 51.043339]]
### 6
fourier: [[4.705839, 4.779118, 32.485279], [2.045949, 2.257632, 31.036796], [1.052518, 1.212725, 14.156130], [11.650601, 13.410062, 46.308541], [18.191440, 19.998620, 99.106579]]
### 8
fourier: [[6.965340, 8.034853, 20.980681]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| vowel_consonant | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.114622,
-0.597415,
-0.171441,
0.2244,
-0.346049
],
[
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0.109484,
-0.066875,
0.103445
],
[
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0.239304,
0.018929
],
[
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0.01141,
0.12715,
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-0.191999
],
[
0.30266,
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-0.087805,
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]
],
"network.0.bias": [
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0.035009,
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0.452636
],
"network.2.weight": [
[
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0.048465,
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],
[
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],
[
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],
[
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0.250584,
-0.17122,
0.36997
],
[
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0.118782,
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0.045732
]
],
"network.2.bias": [
-0.121548,
0.128754,
0.427166,
0.112261,
-0.117427
],
"network.4.weight": [
[
-0.362152,
0.11412,
-0.224622,
-0.356127,
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],
[
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0.291266,
0.161416,
0.127885
],
[
0.579759,
0.351924,
-0.40513,
0.30757,
0.308919
],
[
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0.302416
],
[
0.611139,
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0.51704
]
],
"network.4.bias": [
-0.375701,
0.056025,
0.32347,
0.152555,
-0.10783
],
"network.6.weight": [
[
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0.393229,
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],
[
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-0.050523,
0.304296,
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],
[
0.262505,
0.139286,
0.1566,
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-0.20526
],
[
0.162797,
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0.353112,
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0.478807
],
[
0.060056,
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0.528808,
0.072834,
0.278851
]
],
"network.6.bias": [
-0.057906,
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9.3e-05,
0.167722
],
"network.8.weight": [
[
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0.158061,
-0.173186,
-0.256782
]
],
"network.8.bias": [
-0.021231
]
}
## Activation Signature
### 0
fourier: [[24.751015, 30.167279, 116.853071], [17.918719, 19.802708, 24.342781], [16.845465, 19.681746, 20.405469], [22.859168, 25.095359, 27.313480], [28.201109, 30.364027, 32.483910]]
### 2
fourier: [[6.904929, 6.936254, 7.792864], [25.896439, 27.127086, 96.767391], [6.496032, 7.056758, 42.952621], [9.958569, 11.583086, 42.407672], [9.609396, 12.745484, 23.573613]]
### 4
fourier: [[2.398198, 2.579045, 46.083315], [10.776719, 11.359109, 58.264176], [16.451715, 17.966891, 74.639773], [11.330952, 11.864522, 49.132033], [13.981486, 16.631338, 51.043339]]
### 6
fourier: [[4.705839, 4.779118, 32.485279], [2.045949, 2.257632, 31.036796], [1.052518, 1.212725, 14.156130], [11.650601, 13.410062, 46.308541], [18.191440, 19.998620, 99.106579]]
### 8
fourier: [[6.965340, 8.034853, 20.980681]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
vowel_consonant | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [24.75101472515373, 30.167279435357518, 116.85307060182095]}, "1": {"fourier": [17.918719127720614, 19.80270773778671, 24.34278094023466]}, "2": {"fourier": [16.84546472132206, 19.681746158218594, 20.405468957510514]}, "3": {"fourier": [22.859167719365544, 25.09535936740549, 27.313480065572573]}, "4": {"fourier": [28.201108628685176, 30.364026637232648, 32.48390998171676]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [6.9049292001010025, 6.936253635103833, 7.792864480653938]}, "1": {"fourier": [25.896438527676793, 27.12708556506652, 96.76739127188921]}, "2": {"fourier": [6.496031812968037, 7.056757857451631, 42.95262089371681]}, "3": {"fourier": [9.958569150943221, 11.583085824316262, 42.4076724126935]}, "4": {"fourier": [9.60939641523885, 12.745483918669215, 23.57361277192831]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [2.398198104725972, 2.579045091626929, 46.08331510424614]}, "1": {"fourier": [10.776718960524219, 11.359108500256724, 58.26417614519596]}, "2": {"fourier": [16.451714707871787, 17.966891252802384, 74.63977302610874]}, "3": {"fourier": [11.330951728835128, 11.86452174137698, 49.13203336298466]}, "4": {"fourier": [13.981485698533822, 16.63133784311416, 51.043338634073734]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [4.7058386391400004, 4.779118132400949, 32.48527850210667]}, "1": {"fourier": [2.045948972154415, 2.2576321784286377, 31.03679572045803]}, "2": {"fourier": [1.0525184818644227, 1.2127250883550593, 14.156130068004131]}, "3": {"fourier": [11.650600923322333, 13.410062125826032, 46.30854056403041]}, "4": {"fourier": [18.1914396157722, 19.99861990787506, 99.10657888650894]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [6.965339519278949, 8.034852884918637, 20.980681120418012]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.114622, -0.597415, -0.171441, 0.2244, -0.346049], [0.246656, -0.452913, 0.109484, -0.066875, 0.103445], [0.464194, -0.330695, -0.036758, 0.239304, 0.018929], [0.394424, 0.01141, 0.12715, -0.554441, -0.191999], [0.30266, -0.700601, 0.360418, -0.087805, 0.1387]], "network.0.bias": [0.236597, 0.035009, -0.247627, 0.459728, 0.452636], "network.2.weight": [[-0.145241, -0.23012, 0.048465, 0.616029, -0.237271], [0.241209, 0.694004, -0.00553, 0.598355, 0.693762], [0.253707, 0.081853, 0.336, -0.5337, 0.203835], [-0.078309, 0.445153, 0.250584, -0.17122, 0.36997], [-0.41749, -0.052771, 0.118782, 0.628958, 0.045732]], "network.2.bias": [-0.121548, 0.128754, 0.427166, 0.112261, -0.117427], "network.4.weight": [[-0.362152, 0.11412, -0.224622, -0.356127, 0.245221], [-0.052996, 0.310353, 0.291266, 0.161416, 0.127885], [0.579759, 0.351924, -0.40513, 0.30757, 0.308919], [-0.367725, -0.433411, -0.39468, -0.155491, 0.302416], [0.611139, 0.306401, 0.133597, 0.040125, 0.51704]], "network.4.bias": [-0.375701, 0.056025, 0.32347, 0.152555, -0.10783], "network.6.weight": [[-0.314276, -0.197284, -0.422214, 0.393229, 0.307606], [-0.152285, 0.257905, -0.050523, 0.304296, -0.238891], [0.262505, 0.139286, 0.1566, -0.443188, -0.20526], [0.162797, -0.07806, 0.353112, -0.262423, 0.478807], [0.060056, 0.519661, 0.528808, 0.072834, 0.278851]], "network.6.bias": [-0.057906, 0.355567, 0.053908, 9.3e-05, 0.167722], "network.8.weight": [[-0.023064, 0.389227, 0.158061, -0.173186, -0.256782]], "network.8.bias": [-0.021231]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6832232773303986, "train_acc": 0.57, "val_loss": 0.7079241871833801, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6881192922592163, "train_acc": 0.57, "val_loss": 0.7041718363761902, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6800564229488373, "train_acc": 0.57, "val_loss": 0.6924530267715454, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6824470460414886, "train_acc": 0.57, "val_loss": 0.6854519844055176, "val_acc": 0.5}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6711393892765045, "train_acc": 0.57, "val_loss": 0.669829785823822, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6765819787979126, "train_acc": 0.5, "val_loss": 0.6325645446777344, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.6455601751804352, "train_acc": 0.675, "val_loss": 0.5987405180931091, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6246138215065002, "train_acc": 0.65, "val_loss": 0.5663641095161438, "val_acc": 0.7}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5880244970321655, "train_acc": 0.665, "val_loss": 0.5428012609481812, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5703533291816711, "train_acc": 0.7, "val_loss": 0.5299217700958252, "val_acc": 0.76}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.5530120432376862, "train_acc": 0.705, "val_loss": 0.5353860259056091, "val_acc": 0.72}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.5609988868236542, "train_acc": 0.71, "val_loss": 0.5566529631614685, "val_acc": 0.7}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.5792789608240128, "train_acc": 0.705, "val_loss": 0.550851583480835, "val_acc": 0.72}], "summary": {"total_epochs": 13, "degraded_epochs": 5, "improved_epochs": 8, "patterns": ["vowel_consonant"], "degraded_stage": {"initial_val_loss": 0.7079241871833801, "final_val_loss": 0.669829785823822, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.6325645446777344, "final_val_loss": 0.550851583480835, "initial_val_acc": 0.78, "final_val_acc": 0.72, "best_val_acc": 0.78, "best_epoch": 5}, "improvement": 0.28, "first_improvement_epoch": 4}} |
19 | {"target_pattern": "palindrome", "degraded_accuracy": 0.46, "improved_accuracy": 0.94, "improvement": 0.4799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1291, "learning_rate": 0.05445951689049968, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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],
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"network.4.weight": [
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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"network.10.weight": [
[
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[
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[
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[
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],
"network.10.bias": [
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"network.12.weight": [
[
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]
],
"network.12.bias": [
0.170439
]
}
## Activation Signature
### 0
fourier: [[25.878875, 28.788989, 100.865261], [30.137589, 34.704815, 105.729304], [37.221920, 42.250969, 188.839685], [24.855462, 27.496275, 42.637315], [26.185086, 27.930520, 28.908225]]
### 2
fourier: [[49.902748, 57.003648, 184.642408], [16.047120, 19.320971, 183.075259], [23.776339, 27.434787, 125.959048], [12.708607, 14.752624, 50.776919], [34.796092, 41.131279, 161.384152]]
### 4
fourier: [[18.495088, 20.673839, 71.054867], [1.446908, 1.871255, 27.919583], [46.784061, 52.828205, 230.115333], [59.042116, 66.577052, 259.542846], [2.756603, 3.805780, 81.792909]]
### 6
fourier: [[56.241356, 62.961305, 139.812314], [37.314544, 41.494738, 94.623239], [61.287866, 69.107236, 183.128629], [2.595451, 2.937970, 58.886667], [53.011983, 59.744665, 144.545840]]
### 8
fourier: [[74.700167, 78.597973, 240.648534], [0.791372, 1.009228, 49.999541], [60.303016, 63.044699, 175.547825], [4.816011, 6.209506, 6.385394], [93.229425, 97.952063, 300.482545]]
### 10
fourier: [[56.915625, 59.039586, 155.474131], [111.294511, 114.927298, 342.091822], [3.019614, 3.217601, 93.903152], [34.212553, 34.957088, 95.719940], [33.533232, 34.652737, 128.222892]]
### 12
fourier: [[97.740361, 99.138806, 236.350525]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.333747
],
[
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],
[
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0.656285
],
[
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
[
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],
[
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[
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],
[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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],
[
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],
[
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[
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[
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]
],
"network.4.bias": [
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0.62831
],
"network.6.weight": [
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],
[
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[
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[
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[
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]
],
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],
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[
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[
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[
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"network.8.bias": [
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],
"network.10.weight": [
[
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[
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0.524574
],
[
0.130474,
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[
0.058917,
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],
[
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]
],
"network.10.bias": [
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0.001167
],
"network.12.weight": [
[
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]
],
"network.12.bias": [
0.170439
]
}
## Activation Signature
### 0
fourier: [[25.878875, 28.788989, 100.865261], [30.137589, 34.704815, 105.729304], [37.221920, 42.250969, 188.839685], [24.855462, 27.496275, 42.637315], [26.185086, 27.930520, 28.908225]]
### 2
fourier: [[49.902748, 57.003648, 184.642408], [16.047120, 19.320971, 183.075259], [23.776339, 27.434787, 125.959048], [12.708607, 14.752624, 50.776919], [34.796092, 41.131279, 161.384152]]
### 4
fourier: [[18.495088, 20.673839, 71.054867], [1.446908, 1.871255, 27.919583], [46.784061, 52.828205, 230.115333], [59.042116, 66.577052, 259.542846], [2.756603, 3.805780, 81.792909]]
### 6
fourier: [[56.241356, 62.961305, 139.812314], [37.314544, 41.494738, 94.623239], [61.287866, 69.107236, 183.128629], [2.595451, 2.937970, 58.886667], [53.011983, 59.744665, 144.545840]]
### 8
fourier: [[74.700167, 78.597973, 240.648534], [0.791372, 1.009228, 49.999541], [60.303016, 63.044699, 175.547825], [4.816011, 6.209506, 6.385394], [93.229425, 97.952063, 300.482545]]
### 10
fourier: [[56.915625, 59.039586, 155.474131], [111.294511, 114.927298, 342.091822], [3.019614, 3.217601, 93.903152], [34.212553, 34.957088, 95.719940], [33.533232, 34.652737, 128.222892]]
### 12
fourier: [[97.740361, 99.138806, 236.350525]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.878874865749, 28.788988844169673, 100.86526112258434]}, "1": {"fourier": [30.13758892846248, 34.70481509516346, 105.72930389642715]}, "2": {"fourier": [37.22191960789759, 42.2509689801851, 188.83968450129032]}, "3": {"fourier": [24.8554617137919, 27.496275496407034, 42.63731473684311]}, "4": {"fourier": [26.185085997065883, 27.930520126278232, 28.908224515961184]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [49.902748256360816, 57.00364774242844, 184.64240751042962]}, "1": {"fourier": [16.04711961021918, 19.32097084963758, 183.07525938749313]}, "2": {"fourier": [23.7763388605003, 27.434787455126063, 125.95904812961817]}, "3": {"fourier": [12.708606960328643, 14.752624251999398, 50.776918740943074]}, "4": {"fourier": [34.796092253697175, 41.13127943145647, 161.38415211439133]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [18.49508759086829, 20.673838760140196, 71.05486685037613]}, "1": {"fourier": [1.446907962534335, 1.8712550913545039, 27.919583305716515]}, "2": {"fourier": [46.78406077371244, 52.82820473905076, 230.11533291637897]}, "3": {"fourier": [59.04211586207826, 66.5770515661185, 259.54284619539976]}, "4": {"fourier": [2.7566029078943823, 3.8057796912389446, 81.79290920495987]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [56.24135572648699, 62.96130537776087, 139.81231352686882]}, "1": {"fourier": [37.31454403253147, 41.494737575343684, 94.62323914468288]}, "2": {"fourier": [61.28786583659937, 69.10723608730953, 183.12862868607044]}, "3": {"fourier": [2.59545139254661, 2.9379695100673358, 58.88666746020317]}, "4": {"fourier": [53.01198252665477, 59.744665409591306, 144.54584023728967]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [74.7001674128339, 78.59797303732036, 240.64853356778622]}, "1": {"fourier": [0.7913717060995688, 1.0092276170064034, 49.99954077601433]}, "2": {"fourier": [60.303015968108696, 63.04469931981847, 175.54782527685165]}, "3": {"fourier": [4.816011371152743, 6.20950570176424, 6.3853940003614404]}, "4": {"fourier": [93.22942477779634, 97.95206340599104, 300.48254495859146]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [56.91562514071128, 59.039586115813535, 155.47413071990013]}, "1": {"fourier": [111.29451116066721, 114.92729832735628, 342.0918223038316]}, "2": {"fourier": [3.0196136320647136, 3.217601245696128, 93.903151512146]}, "3": {"fourier": [34.21255282885331, 34.95708833016445, 95.71993987262249]}, "4": {"fourier": [33.53323202136329, 34.65273691654931, 128.22289204597473]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [97.74036050889548, 99.13880569643361, 236.3505245745182]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.548671, -0.077964, -0.091449, -0.418281, -0.333747], [0.028714, -0.409082, 0.191466, 0.335113, 0.743433], [0.615229, -0.119441, -0.134499, 0.40241, 0.656285], [-0.385984, 0.313789, 0.463969, -0.315552, -0.454268], [-0.313902, 0.374228, -0.247707, 0.145709, -0.41996]], "network.0.bias": [-0.161818, -0.151009, 0.158838, 0.650058, 0.45792], "network.2.weight": [[0.548861, 0.508697, 0.816935, -0.389586, -0.192383], [0.489495, 0.256773, 0.321145, 0.351733, 0.221775], [-0.364625, -0.407052, -0.338206, -0.428705, 0.251899], [0.186671, -0.228282, 0.111245, 0.266791, 0.658541], [-0.122013, 0.162613, 0.716099, -0.328411, -0.437901]], "network.2.bias": [-0.044914, 0.49717, 0.162881, 0.020463, 0.584491], "network.4.weight": [[-0.387527, 0.419862, 0.552321, 0.659511, -0.079732], [-0.155128, -0.130699, -0.021625, 0.03987, 0.249762], [0.424594, 0.01245, 0.324711, 0.041689, 0.7509], [0.824093, 0.257019, -0.031131, -0.408019, 0.369234], [-0.306894, 0.428331, -0.182572, -0.224534, 0.126343]], "network.4.bias": [0.536188, -0.191031, 0.14494, 0.080532, 0.62831], "network.6.weight": [[-0.373487, 0.131551, 0.281541, 0.632247, -0.838305], [-0.075192, -0.087851, 0.445983, 0.239021, -0.611023], [-0.390114, -0.426825, 0.647276, 0.439744, -0.515093], [-0.262192, 0.063122, -0.149522, 0.03416, 0.002364], [-0.405388, 0.151275, 0.415758, 0.47913, -0.54791]], "network.6.bias": [0.120095, -0.154891, -0.05288, -0.121059, 0.040603], "network.8.weight": [[0.453035, -0.07004, 0.445793, -0.015004, 0.541351], [-0.227868, -0.264991, 0.236181, 0.292501, 0.14162], [0.516798, -0.043059, -0.004157, -0.207542, 0.691984], [0.002877, -0.090818, -0.179139, -0.376253, 0.392497], [0.416394, 0.605766, 0.352037, -0.410825, 0.586619]], "network.8.bias": [-0.253402, 0.513854, -0.367257, -0.207545, -0.262778], "network.10.weight": [[0.243225, -0.05998, -0.07545, 0.171852, 0.458], [0.490837, -0.312926, 0.435296, 0.068331, 0.524574], [0.130474, 0.554994, 0.063956, 0.262134, -0.189978], [0.058917, 0.162626, 0.155099, 0.608598, 0.189601], [-0.030365, -0.357832, -0.018251, -0.377617, -0.306498]], "network.10.bias": [-0.354484, -0.114965, 0.858541, -0.248192, 0.001167], "network.12.weight": [[-0.46036, -0.427183, 0.508065, -0.694606, 0.417264]], "network.12.bias": [0.170439]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.680371880531311, "train_acc": 0.58, "val_loss": 0.7127236723899841, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6814064681529999, "train_acc": 0.58, "val_loss": 0.6977627277374268, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6389081478118896, "train_acc": 0.58, "val_loss": 0.5824801921844482, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5576818287372589, "train_acc": 0.51, "val_loss": 0.4577086567878723, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.46308939158916473, "train_acc": 0.85, "val_loss": 0.4359246492385864, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4555929899215698, "train_acc": 0.805, "val_loss": 0.4077622890472412, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.41932322084903717, "train_acc": 0.845, "val_loss": 0.29119494557380676, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.3620760440826416, "train_acc": 0.855, "val_loss": 0.3093688488006592, "val_acc": 0.88}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.36664675176143646, "train_acc": 0.855, "val_loss": 0.23319858312606812, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3142380565404892, "train_acc": 0.855, "val_loss": 0.21452759206295013, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.33834555745124817, "train_acc": 0.865, "val_loss": 0.2017345428466797, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.2961605340242386, "train_acc": 0.89, "val_loss": 0.24425430595874786, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.33127422630786896, "train_acc": 0.85, "val_loss": 0.21263042092323303, "val_acc": 0.92}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7127236723899841, "final_val_loss": 0.5824801921844482, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.4577086567878723, "final_val_loss": 0.21263042092323303, "initial_val_acc": 0.88, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 6}, "improvement": 0.4799999999999999, "first_improvement_epoch": 2}} |
20 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.54, "improved_accuracy": 0.9, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4611, "learning_rate": 0.08701594713422484, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[34.916622, 36.934583, 133.931841], [48.332670, 57.292213, 382.087933], [35.192076, 39.672568, 167.607619], [78.184109, 78.476351, 353.986768], [53.231860, 54.512645, 373.583183], [62.540401, 68.977145, 79.905338]]
### 2
fourier: [[31.196929, 34.127913, 168.406513], [68.340958, 69.790487, 252.299798], [81.194825, 88.648234, 357.852344], [72.156228, 82.919421, 364.937484], [95.911725, 102.544423, 465.513485], [113.198884, 116.686112, 460.060721]]
### 4
fourier: [[50.825390, 56.062954, 283.125731], [186.019657, 191.918922, 702.448962], [186.272135, 193.295446, 712.934817], [107.088488, 118.434951, 423.178551], [97.318514, 107.872098, 493.754178], [81.687080, 83.514611, 396.356249]]
### 6
fourier: [[606.681062, 642.026723, 2278.919590], [135.694212, 141.939213, 618.747016], [295.825934, 314.540973, 1111.865810], [319.700390, 333.935811, 1192.671864], [168.652341, 179.375916, 606.628419], [433.746084, 455.853811, 1659.125266]]
### 8
fourier: [[98.486468, 103.499060, 333.183921], [443.334651, 467.614684, 1623.507836], [328.765416, 349.416227, 1149.713031], [22.368119, 22.800202, 23.294389], [69.890867, 70.945574, 199.556891], [152.078431, 160.932444, 544.304281]]
### 10
fourier: [[375.136810, 399.204964, 1306.384719]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[34.916622, 36.934583, 133.931841], [48.332670, 57.292213, 382.087933], [35.192076, 39.672568, 167.607619], [78.184109, 78.476351, 353.986768], [53.231860, 54.512645, 373.583183], [62.540401, 68.977145, 79.905338]]
### 2
fourier: [[31.196929, 34.127913, 168.406513], [68.340958, 69.790487, 252.299798], [81.194825, 88.648234, 357.852344], [72.156228, 82.919421, 364.937484], [95.911725, 102.544423, 465.513485], [113.198884, 116.686112, 460.060721]]
### 4
fourier: [[50.825390, 56.062954, 283.125731], [186.019657, 191.918922, 702.448962], [186.272135, 193.295446, 712.934817], [107.088488, 118.434951, 423.178551], [97.318514, 107.872098, 493.754178], [81.687080, 83.514611, 396.356249]]
### 6
fourier: [[606.681062, 642.026723, 2278.919590], [135.694212, 141.939213, 618.747016], [295.825934, 314.540973, 1111.865810], [319.700390, 333.935811, 1192.671864], [168.652341, 179.375916, 606.628419], [433.746084, 455.853811, 1659.125266]]
### 8
fourier: [[98.486468, 103.499060, 333.183921], [443.334651, 467.614684, 1623.507836], [328.765416, 349.416227, 1149.713031], [22.368119, 22.800202, 23.294389], [69.890867, 70.945574, 199.556891], [152.078431, 160.932444, 544.304281]]
### 10
fourier: [[375.136810, 399.204964, 1306.384719]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [34.91662169572699, 36.93458275385032, 133.93184131383896]}, "1": {"fourier": [48.33266976047723, 57.29221279334533, 382.0879325866699]}, "2": {"fourier": [35.1920761765462, 39.67256834060555, 167.60761886835098]}, "3": {"fourier": [78.18410898636397, 78.4763510833327, 353.98676812648773]}, "4": {"fourier": [53.23185964471712, 54.51264468661848, 373.5831828415394]}, "5": {"fourier": [62.54040060419988, 68.97714456670803, 79.90533797589606]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [31.196929075462297, 34.12791340543681, 168.40651340782642]}, "1": {"fourier": [68.34095793538462, 69.79048681702028, 252.2997975051403]}, "2": {"fourier": [81.19482478458627, 88.64823448322413, 357.85234409198165]}, "3": {"fourier": [72.15622821709051, 82.91942106383013, 364.9374836087227]}, "4": {"fourier": [95.91172465486648, 102.54442341244712, 465.5134853720665]}, "5": {"fourier": [113.19888400117574, 116.68611172015208, 460.06072075664997]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [50.825390325803525, 56.062953667372746, 283.12573075294495]}, "1": {"fourier": [186.0196565166386, 191.91892248923122, 702.4489615112543]}, "2": {"fourier": [186.2721350817692, 193.29544568145678, 712.9348174482584]}, "3": {"fourier": [107.08848755436836, 118.43495065001603, 423.17855060100555]}, "4": {"fourier": [97.31851391745109, 107.87209781869903, 493.75417762994766]}, "5": {"fourier": [81.68707955422232, 83.5146114957471, 396.35624861717224]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [606.6810619927533, 642.0267229466367, 2278.919590175152]}, "1": {"fourier": [135.69421162391308, 141.939213466683, 618.7470155954361]}, "2": {"fourier": 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{"fourier": [375.1368103389186, 399.2049643309245, 1306.384719491005]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.97331, -0.669474, -0.66332, 0.276193, -0.078344], [-0.56479, -0.431164, -0.596128, -0.794572, 0.46991], [0.760349, 0.035281, -0.733214, 0.010114, -0.564062], [1.748115, 0.742474, 0.299245, 0.203447, -0.100239], [-0.311906, -0.970314, -0.500157, 0.053256, -0.483984], [1.488324, -1.446438, 0.383082, 0.139056, 0.047458]], "network.0.bias": [-0.589488, 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"train_acc": 0.895, "val_loss": 0.2786707878112793, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.23450759053230286, "train_acc": 0.92, "val_loss": 0.2503735423088074, "val_acc": 0.9}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.6894066333770752, "final_val_loss": 0.6541069149971008, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.4893711805343628, "final_val_loss": 0.2503735423088074, "initial_val_acc": 0.82, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 12}, "improvement": 0.36, "first_improvement_epoch": 2}} |
21 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.5, "improved_accuracy": 0.86, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8617, "learning_rate": 0.08422630629161262, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[31.861283, 36.002314, 68.743411], [76.684552, 77.987557, 79.747661], [45.425673, 49.617440, 264.743739], [59.352852, 63.150496, 63.604059], [42.647883, 45.062749, 274.409255], [34.790040, 37.198159, 301.970220]]
### 2
fourier: [[32.474532, 39.875400, 229.875849], [102.179731, 106.002899, 326.506149], [45.889083, 46.538988, 205.617216], [62.418576, 67.172752, 123.317965], [21.553911, 26.889143, 133.975370], [66.826533, 69.725497, 213.705504]]
### 4
fourier: [[82.055824, 85.318143, 287.890893], [262.410751, 272.867212, 811.254478], [51.094077, 53.094388, 171.870805], [83.353372, 86.857845, 248.502572], [237.166488, 246.440428, 756.634542], [195.505974, 203.321731, 619.595258]]
### 6
fourier: [[652.624173, 678.471606, 2058.198260], [243.849608, 253.504139, 779.008684], [387.275199, 402.607489, 1220.523173], [101.337616, 105.354349, 327.614907], [146.913878, 152.730664, 470.224842], [166.440445, 173.057056, 520.938892]]
### 8
fourier: [[431.666102, 448.762407, 1382.362851], [536.391068, 557.635048, 1670.627025], [279.032830, 290.084042, 852.786818], [210.656608, 218.999747, 673.040445], [372.985522, 387.757757, 1203.891656], [70.691787, 73.491563, 243.792993]]
### 10
fourier: [[43.747672, 45.480318, 156.239863], [437.410522, 454.734341, 1303.776901], [764.986470, 795.284052, 2354.168699], [220.883477, 229.631658, 728.485597], [487.239996, 506.537337, 1456.400528], [165.648743, 172.209333, 543.615376]]
### 12
fourier: [[483.884630, 503.772724, 1448.156751]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
0.427555,
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0.025901
],
[
-0.322784,
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-0.069974,
0.326188,
-0.063061,
-0.058988
],
[
-0.571517,
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0.062268,
-0.050399
],
[
-0.108319,
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-0.302723,
-0.227083,
-0.402952,
-0.225446
]
],
"network.8.bias": [
-0.2334,
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-0.302294,
-0.096523,
-0.306636,
-0.231671
],
"network.10.weight": [
[
0.060625,
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-0.362846,
-0.324806,
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-0.16097
],
[
0.053713,
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-0.029869,
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],
[
-0.330597,
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],
[
0.052986,
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],
[
0.309585,
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[
0.078998,
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],
"network.10.bias": [
-0.287688,
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],
"network.12.weight": [
[
0.180408,
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-0.633264,
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]
],
"network.12.bias": [
0.466173
]
}
## Activation Signature
### 0
fourier: [[31.861283, 36.002314, 68.743411], [76.684552, 77.987557, 79.747661], [45.425673, 49.617440, 264.743739], [59.352852, 63.150496, 63.604059], [42.647883, 45.062749, 274.409255], [34.790040, 37.198159, 301.970220]]
### 2
fourier: [[32.474532, 39.875400, 229.875849], [102.179731, 106.002899, 326.506149], [45.889083, 46.538988, 205.617216], [62.418576, 67.172752, 123.317965], [21.553911, 26.889143, 133.975370], [66.826533, 69.725497, 213.705504]]
### 4
fourier: [[82.055824, 85.318143, 287.890893], [262.410751, 272.867212, 811.254478], [51.094077, 53.094388, 171.870805], [83.353372, 86.857845, 248.502572], [237.166488, 246.440428, 756.634542], [195.505974, 203.321731, 619.595258]]
### 6
fourier: [[652.624173, 678.471606, 2058.198260], [243.849608, 253.504139, 779.008684], [387.275199, 402.607489, 1220.523173], [101.337616, 105.354349, 327.614907], [146.913878, 152.730664, 470.224842], [166.440445, 173.057056, 520.938892]]
### 8
fourier: [[431.666102, 448.762407, 1382.362851], [536.391068, 557.635048, 1670.627025], [279.032830, 290.084042, 852.786818], [210.656608, 218.999747, 673.040445], [372.985522, 387.757757, 1203.891656], [70.691787, 73.491563, 243.792993]]
### 10
fourier: [[43.747672, 45.480318, 156.239863], [437.410522, 454.734341, 1303.776901], [764.986470, 795.284052, 2354.168699], [220.883477, 229.631658, 728.485597], [487.239996, 506.537337, 1456.400528], [165.648743, 172.209333, 543.615376]]
### 12
fourier: [[483.884630, 503.772724, 1448.156751]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [31.861283479728172, 36.002313794988176, 68.74341097846627]}, "1": {"fourier": [76.68455176883384, 77.98755681869241, 79.74766069759191]}, "2": {"fourier": [45.42567254872252, 49.61744032929174, 264.7437387704849]}, "3": {"fourier": [59.35285229744883, 63.150496155023575, 63.604058801860425]}, "4": {"fourier": [42.6478826270898, 45.062749272470484, 274.40925520658493]}, "5": {"fourier": [34.79003952611407, 37.19815901054647, 301.9702202677727]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [32.474532253810594, 39.875399851727074, 229.87584906816483]}, "1": {"fourier": [102.17973082430244, 106.00289936417653, 326.50614884495735]}, "2": {"fourier": [45.88908313572077, 46.53898838771099, 205.6172159910202]}, "3": {"fourier": [62.41857641111431, 67.172751680396, 123.31796485185623]}, "4": {"fourier": [21.553911220753058, 26.8891427771133, 133.9753700196743]}, "5": {"fourier": [66.82653287444462, 69.72549713756969, 213.70550449192524]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [82.05582375032759, 85.31814282288721, 287.8908934891224]}, "1": {"fourier": [262.4107510645125, 272.86721213347215, 811.2544777095318]}, "2": {"fourier": [51.09407662646753, 53.094387981945104, 171.87080508470535]}, "3": {"fourier": [83.35337238474699, 86.85784537698746, 248.5025715008378]}, "4": {"fourier": [237.1664876130167, 246.44042835889724, 756.6345421373844]}, "5": {"fourier": [195.50597374263677, 203.3217309706235, 619.5952576100826]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [652.6241730894938, 678.4716063548317, 2058.1982598900795]}, "1": {"fourier": [243.8496081064186, 253.50413900142485, 779.0086840391159]}, "2": {"fourier": [387.27519940351993, 402.60748890188177, 1220.5231730937958]}, "3": {"fourier": [101.33761582061163, 105.35434926614222, 327.6149068772793]}, "4": {"fourier": [146.91387762121064, 152.73066432581945, 470.22484162449837]}, "5": {"fourier": [166.44044470075747, 173.05705573675795, 520.9388918429613]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [431.6661024396103, 448.7624073365028, 1382.3628510832787]}, "1": {"fourier": [536.3910684273957, 557.6350479008607, 1670.6270253956318]}, "2": {"fourier": [279.03283001419663, 290.0840417599632, 852.7868176996708]}, "3": {"fourier": [210.65660811540175, 218.99974729114442, 673.0404452681541]}, "4": {"fourier": [372.98552226307015, 387.75775742276176, 1203.891655743122]}, "5": {"fourier": [70.69178659732289, 73.49156277215636, 243.79299345612526]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [43.747671839892405, 45.480317672192065, 156.2398633658886]}, "1": {"fourier": [437.41052221628195, 454.7343411975265, 1303.7769012153149]}, "2": {"fourier": [764.9864697175685, 795.2840517291783, 2354.1686989068985]}, "3": {"fourier": [220.88347749775403, 229.63165783625115, 728.4855969548225]}, "4": {"fourier": [487.2399956178564, 506.53733714168993, 1456.4005275070667]}, "5": {"fourier": [165.64874336214447, 172.20933267693633, 543.6153762340546]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [483.8846299597508, 503.7727235586062, 1448.1567512452602]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.834888, 0.268431, 0.298987, 0.187452, 0.23271], [2.05069, 0.273296, -0.440392, -0.302467, -0.692154], [0.105757, 0.499826, -1.14084, -0.40299, -0.392463], [0.723549, 0.360963, 0.113785, -0.000295, -1.740273], [-0.809717, -0.176397, -0.526771, -0.171434, 0.003931], [-0.293729, -0.409661, -0.148803, -0.412062, -0.298951]], "network.0.bias": [0.000108, -0.127243, -0.252682, -0.350557, -0.256762, -0.680019], "network.2.weight": [[-0.826297, -0.212634, -0.428567, -0.805261, 0.012806, -0.358548], [-0.119472, 1.1995, 1.150114, 1.210535, 0.172326, -0.052602], [-0.191447, -0.540626, -0.094484, -0.615085, 0.034549, 0.006391], [-0.353767, 0.78433, 1.262023, 0.515093, 0.050621, 0.425751], [-0.520236, -0.123747, -0.49018, -0.556721, 0.010189, -0.361966], [-0.126063, 0.730043, 0.824894, 0.929527, 0.279901, -0.019795]], "network.2.bias": [-0.495134, 0.528438, -0.558965, -0.113476, -0.157909, 0.375151], "network.4.weight": [[0.164717, -0.518841, -0.166381, -0.308837, 0.116415, -0.149717], [0.357201, 1.325365, -0.514641, 0.890252, 0.084802, 1.077218], [-0.217265, -0.270028, -0.226961, -0.098285, -0.396762, -0.260415], [0.289151, -0.172295, -0.408013, -0.598197, -0.695972, -0.431631], [0.448833, 1.410161, 0.533815, 0.498754, 0.155327, 0.930768], [0.201913, 1.069832, 0.06671, 0.759023, 0.278003, 0.58904]], "network.4.bias": [-0.431329, 0.119069, -0.142492, -0.084792, 0.223619, 0.30208], "network.6.weight": [[-0.599718, 1.032755, -0.227872, 0.226596, 1.007784, 0.729426], [-0.438921, -0.232001, 0.32822, -0.047312, -0.417966, -0.428853], [-0.275655, -0.327691, -0.003309, -0.172624, -0.67436, -0.723002], [-0.33558, -0.284219, -0.133168, 0.241042, -0.120132, 0.008877], [0.139506, -0.126581, 0.379263, 0.394496, -0.253297, -0.274286], [-0.127492, -0.390764, -0.020696, -0.321776, -0.116485, -0.185538]], "network.6.bias": [0.065535, -0.098159, 0.039224, -0.129396, -0.065954, -0.009279], "network.8.weight": [[-0.661431, -0.254993, 0.04059, 0.017601, 0.146846, 0.358406], [0.821899, -0.33901, -0.579096, -0.363953, -0.073273, 0.012725], [0.427555, 0.21113, 0.240983, 0.301471, -0.280587, 0.025901], [-0.322784, 0.698038, -0.069974, 0.326188, -0.063061, -0.058988], [-0.571517, -0.289854, -0.028659, -0.273962, 0.062268, -0.050399], [-0.108319, -0.210632, -0.302723, -0.227083, -0.402952, -0.225446]], "network.8.bias": [-0.2334, -0.233376, -0.302294, -0.096523, -0.306636, -0.231671], "network.10.weight": [[0.060625, 0.107195, -0.362846, -0.324806, -0.342992, -0.16097], [0.053713, -0.697857, -0.22609, -0.029869, 0.169625, 0.312191], [-0.330597, 1.05311, 0.717147, 0.140381, 0.022147, -0.073678], [0.052986, -0.282509, -0.24853, -0.557616, -0.384724, -0.301359], [0.309585, -0.850165, -0.111884, -0.124241, 0.258176, 0.336121], [0.078998, 0.060189, -0.709356, -0.49325, -0.013622, -0.261538]], "network.10.bias": [-0.287688, 0.609862, -0.186213, -0.495276, 0.659118, -0.435993], "network.12.weight": [[0.180408, 0.749169, -0.633264, 0.120391, 0.449008, 0.071619]], "network.12.bias": [0.466173]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7023701071739197, "train_acc": 0.465, "val_loss": 0.7157906889915466, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.676950603723526, "train_acc": 0.575, "val_loss": 0.7114367485046387, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6704665124416351, "train_acc": 0.575, "val_loss": 0.6854040026664734, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6409766674041748, "train_acc": 0.575, "val_loss": 0.673373818397522, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6360303163528442, "train_acc": 0.59, "val_loss": 0.6728166341781616, "val_acc": 0.6}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.6361407041549683, "train_acc": 0.62, "val_loss": 0.5778343677520752, "val_acc": 0.68}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5379939377307892, "train_acc": 0.72, "val_loss": 0.5729638934135437, "val_acc": 0.66}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.5328101515769958, "train_acc": 0.74, "val_loss": 0.517748236656189, "val_acc": 0.7}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.48008808493614197, "train_acc": 0.775, "val_loss": 0.5376970767974854, "val_acc": 0.68}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.5213672816753387, "train_acc": 0.735, "val_loss": 0.5504913330078125, "val_acc": 0.7}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.45565593242645264, "train_acc": 0.79, "val_loss": 0.49685138463974, "val_acc": 0.78}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.46785369515419006, "train_acc": 0.805, "val_loss": 0.4032965898513794, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.38551972806453705, "train_acc": 0.825, "val_loss": 0.43848705291748047, "val_acc": 0.8}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.41696934401988983, "train_acc": 0.82, "val_loss": 0.4037576913833618, "val_acc": 0.82}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.7157906889915466, "final_val_loss": 0.673373818397522, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.6728166341781616, "final_val_loss": 0.4037576913833618, "initial_val_acc": 0.6, "final_val_acc": 0.82, "best_val_acc": 0.86, "best_epoch": 11}, "improvement": 0.36, "first_improvement_epoch": 3}} |
22 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.62, "improved_accuracy": 0.84, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7000, "learning_rate": 0.025272621911807264, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.464288,
0.083645,
-0.128603,
0.27715
]
],
"network.6.bias": [
-0.10501,
0.023531,
0.300601,
0.03676,
-0.175607,
0.113119
],
"network.8.weight": [
[
0.244928,
-0.074938,
-0.653424,
0.454718,
0.199583,
0.120208
]
],
"network.8.bias": [
-0.265231
]
}
## Activation Signature
### 0
fourier: [[27.368461, 32.392783, 252.499053], [21.253765, 24.366645, 96.976289], [21.978096, 22.288424, 26.927795], [18.909328, 24.845286, 81.684578], [25.826175, 27.137070, 97.225961], [23.977108, 26.284550, 77.212581]]
### 2
fourier: [[24.068851, 24.235634, 96.636756], [9.756551, 9.868359, 33.792135], [14.644670, 15.642237, 39.255565], [25.965204, 27.398884, 27.746218], [17.510660, 19.510268, 88.021430], [5.672384, 6.315203, 33.287076]]
### 4
fourier: [[29.508185, 29.673346, 104.359520], [8.769352, 9.413664, 53.710864], [23.529775, 24.023116, 24.339832], [7.660275, 8.833454, 110.807944], [24.245770, 24.931793, 27.564739], [12.035640, 12.943618, 27.789883]]
### 6
fourier: [[26.196542, 27.396519, 29.954626], [10.986254, 11.800956, 12.100822], [30.508962, 31.077813, 127.799033], [17.663355, 18.793310, 19.640406], [18.610956, 21.020786, 23.261016], [15.934822, 16.456619, 16.984537]]
### 8
fourier: [[29.071845, 30.718743, 85.600708]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.048291,
-0.390441,
-0.26856,
-0.494977,
0.137126
],
[
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0.510961,
0.35104,
-0.403752
],
[
-0.504851,
-0.039095,
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0.126638,
0.579383
],
[
0.433144,
-0.076486,
-0.007583,
-0.109075,
0.2409
],
[
-0.169998,
0.516762,
-0.232059,
-0.21665,
-0.428107
],
[
0.355843,
0.087591,
-0.035414,
-0.133324,
0.453328
]
],
"network.0.bias": [
-0.580659,
-0.101038,
-0.058356,
0.460592,
-0.333055,
0.056257
],
"network.2.weight": [
[
-0.238282,
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0.257108,
0.309267,
-0.12315,
0.57868
],
[
-0.056806,
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-0.272405,
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0.34946,
0.059384
],
[
0.351645,
0.425751,
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0.147247,
0.215214
],
[
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0.222976,
-0.237941
],
[
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0.380673,
0.216003,
0.386773,
0.385058
],
[
0.192433,
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0.171772,
0.005919,
-0.080888,
-0.121469
]
],
"network.2.bias": [
0.38783,
0.122155,
0.344869,
0.028132,
0.402926,
0.136125
],
"network.4.weight": [
[
0.506053,
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-0.704118,
0.445437,
0.009614
],
[
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0.309206,
0.523846
],
[
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0.126725
],
[
0.285924,
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0.125688,
0.079007,
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0.177075
],
[
-0.604335,
0.537952,
0.68195,
0.209748,
0.085431,
0.21525
],
[
0.131403,
0.181121,
0.301574,
0.30828,
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]
],
"network.4.bias": [
0.640505,
0.043473,
0.396596,
0.509138,
-0.077595,
0.248084
],
"network.6.weight": [
[
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],
[
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0.330254,
-0.396899,
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],
[
0.669242,
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0.289199,
-0.294615,
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],
[
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0.121491
],
[
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0.00662,
0.411326,
0.429008
],
[
-0.401964,
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0.464288,
0.083645,
-0.128603,
0.27715
]
],
"network.6.bias": [
-0.10501,
0.023531,
0.300601,
0.03676,
-0.175607,
0.113119
],
"network.8.weight": [
[
0.244928,
-0.074938,
-0.653424,
0.454718,
0.199583,
0.120208
]
],
"network.8.bias": [
-0.265231
]
}
## Activation Signature
### 0
fourier: [[27.368461, 32.392783, 252.499053], [21.253765, 24.366645, 96.976289], [21.978096, 22.288424, 26.927795], [18.909328, 24.845286, 81.684578], [25.826175, 27.137070, 97.225961], [23.977108, 26.284550, 77.212581]]
### 2
fourier: [[24.068851, 24.235634, 96.636756], [9.756551, 9.868359, 33.792135], [14.644670, 15.642237, 39.255565], [25.965204, 27.398884, 27.746218], [17.510660, 19.510268, 88.021430], [5.672384, 6.315203, 33.287076]]
### 4
fourier: [[29.508185, 29.673346, 104.359520], [8.769352, 9.413664, 53.710864], [23.529775, 24.023116, 24.339832], [7.660275, 8.833454, 110.807944], [24.245770, 24.931793, 27.564739], [12.035640, 12.943618, 27.789883]]
### 6
fourier: [[26.196542, 27.396519, 29.954626], [10.986254, 11.800956, 12.100822], [30.508962, 31.077813, 127.799033], [17.663355, 18.793310, 19.640406], [18.610956, 21.020786, 23.261016], [15.934822, 16.456619, 16.984537]]
### 8
fourier: [[29.071845, 30.718743, 85.600708]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [27.3684613850547, 32.392782845324405, 252.49905270338058]}, "1": {"fourier": [21.253765411728217, 24.366644982049195, 96.97628907859325]}, "2": {"fourier": [21.97809596661009, 22.28842446466623, 26.92779515944248]}, "3": {"fourier": [18.909328375046396, 24.845286098026484, 81.68457791209221]}, "4": {"fourier": [25.826174684478826, 27.137070010739308, 97.22596082091331]}, "5": {"fourier": [23.977108145083704, 26.284549624235144, 77.21258111298084]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [24.068850941356747, 24.235633555767404, 96.6367564201355]}, "1": {"fourier": [9.756550841177239, 9.868359222179365, 33.792135160416365]}, "2": {"fourier": [14.644669767568953, 15.642236855099789, 39.25556471943855]}, "3": {"fourier": [25.96520441430627, 27.398884468185145, 27.746218114701836]}, "4": {"fourier": [17.51065972418849, 19.510267970954036, 88.02143040299416]}, "5": {"fourier": [5.672383746877311, 6.315202685643862, 33.287076123058796]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [29.50818451067017, 29.673345698377627, 104.35952025651932]}, "1": {"fourier": [8.769351692288915, 9.413663500890367, 53.71086399257183]}, "2": {"fourier": [23.529775393672725, 24.02311645749565, 24.33983204594675]}, "3": {"fourier": [7.660274675857755, 8.833453650649844, 110.80794370174408]}, "4": {"fourier": [24.24576982231698, 24.931792587270778, 27.56473887724928]}, "5": {"fourier": [12.035639635134498, 12.943618498798218, 27.789883345365524]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [26.196542415767908, 27.396519430957305, 29.95462611865298]}, "1": {"fourier": [10.986254004885597, 11.800956155699087, 12.100822219661703]}, "2": {"fourier": [30.508962146971967, 31.077813184016808, 127.79903341829777]}, "3": {"fourier": [17.66335534096699, 18.793309972519072, 19.640405904501677]}, "4": {"fourier": [18.61095557171602, 21.02078561374355, 23.261015970141646]}, "5": {"fourier": [15.934822394585815, 16.456619083589523, 16.98453744490852]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [29.07184457447956, 30.718742713768957, 85.60070753097534]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.048291, -0.390441, -0.26856, -0.494977, 0.137126], [-0.187913, 0.049518, 0.510961, 0.35104, -0.403752], [-0.504851, -0.039095, -0.093767, 0.126638, 0.579383], [0.433144, -0.076486, -0.007583, -0.109075, 0.2409], [-0.169998, 0.516762, -0.232059, -0.21665, -0.428107], [0.355843, 0.087591, -0.035414, -0.133324, 0.453328]], "network.0.bias": [-0.580659, -0.101038, -0.058356, 0.460592, -0.333055, 0.056257], "network.2.weight": [[-0.238282, -0.169015, 0.257108, 0.309267, -0.12315, 0.57868], [-0.056806, 0.328943, -0.272405, -0.072986, 0.34946, 0.059384], [0.351645, 0.425751, -0.555608, -0.381698, 0.147247, 0.215214], [-0.0659, 0.510163, -0.6, -0.46373, 0.222976, -0.237941], [-0.31319, -0.107978, 0.380673, 0.216003, 0.386773, 0.385058], [0.192433, 0.245674, 0.171772, 0.005919, -0.080888, -0.121469]], "network.2.bias": [0.38783, 0.122155, 0.344869, 0.028132, 0.402926, 0.136125], "network.4.weight": [[0.506053, -0.081782, -0.267833, -0.704118, 0.445437, 0.009614], [0.156401, 0.045749, 0.029073, -0.167081, 0.309206, 0.523846], [-0.217377, 0.009958, 0.49988, 0.417595, -0.533346, 0.126725], [0.285924, 0.313975, 0.125688, 0.079007, 0.21107, 0.177075], [-0.604335, 0.537952, 0.68195, 0.209748, 0.085431, 0.21525], [0.131403, 0.181121, 0.301574, 0.30828, -0.443676, 0.027302]], "network.4.bias": [0.640505, 0.043473, 0.396596, 0.509138, -0.077595, 0.248084], "network.6.weight": [[-0.70647, 0.12465, 0.328044, 0.19957, 0.48922, 0.180246], [-0.103671, 0.301303, -0.169779, 0.330254, -0.396899, -0.228889], [0.669242, 0.523601, -0.293016, 0.289199, -0.294615, -0.070734], [-0.423823, -0.184533, 0.188979, 0.121662, 0.239527, 0.121491], [-0.284135, 0.271996, 0.49574, 0.00662, 0.411326, 0.429008], [-0.401964, -0.055722, 0.464288, 0.083645, -0.128603, 0.27715]], "network.6.bias": [-0.10501, 0.023531, 0.300601, 0.03676, -0.175607, 0.113119], "network.8.weight": [[0.244928, -0.074938, -0.653424, 0.454718, 0.199583, 0.120208]], "network.8.bias": [-0.265231]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6897553205490112, "train_acc": 0.57, "val_loss": 0.6892157196998596, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6784673035144806, "train_acc": 0.57, "val_loss": 0.6784011721611023, "val_acc": 0.54}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6657344698905945, "train_acc": 0.59, "val_loss": 0.6526867747306824, "val_acc": 0.62}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6361852884292603, "train_acc": 0.69, "val_loss": 0.6102039217948914, "val_acc": 0.72}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6352730691432953, "train_acc": 0.695, "val_loss": 0.5830082893371582, "val_acc": 0.8}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.5510962009429932, "train_acc": 0.775, "val_loss": 0.5288682579994202, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.5246470868587494, "train_acc": 0.76, "val_loss": 0.4943920969963074, "val_acc": 0.74}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.4878329634666443, "train_acc": 0.745, "val_loss": 0.45370185375213623, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4357360154390335, "train_acc": 0.815, "val_loss": 0.43908336758613586, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.41739654541015625, "train_acc": 0.825, "val_loss": 0.434867262840271, "val_acc": 0.84}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.397285521030426, "train_acc": 0.81, "val_loss": 0.4089910387992859, "val_acc": 0.84}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.36710378527641296, "train_acc": 0.82, "val_loss": 0.3781667947769165, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.371894434094429, "train_acc": 0.825, "val_loss": 0.3619998097419739, "val_acc": 0.84}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6892157196998596, "final_val_loss": 0.6526867747306824, "initial_val_acc": 0.54, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.6102039217948914, "final_val_loss": 0.3619998097419739, "initial_val_acc": 0.72, "final_val_acc": 0.84, "best_val_acc": 0.84, "best_epoch": 8}, "improvement": 0.21999999999999997, "first_improvement_epoch": 2}} |
23 | {"target_pattern": "has_majority", "degraded_accuracy": 0.54, "improved_accuracy": 0.8, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5499, "learning_rate": 0.07940362044088127, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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],
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"network.2.weight": [
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[
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[
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[
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],
"network.2.bias": [
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"network.4.weight": [
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[
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0.605371
],
[
-0.003217,
0.344386,
0.048213,
-0.211421,
-0.343303,
0.242469
],
[
0.10867,
-0.214673,
-0.549796,
-0.177042,
0.222463,
-0.253148
]
],
"network.4.bias": [
-0.115347,
-0.292091,
-0.259196,
-0.410617,
-0.099192,
-0.672386
],
"network.6.weight": [
[
-0.251335,
0.219704,
-0.249106,
-0.367963,
-0.280172,
0.549099
],
[
0.355222,
0.106307,
0.004931,
-0.392323,
-0.001006,
0.153506
],
[
0.35573,
0.152365,
-0.0845,
-0.05791,
-0.135136,
-0.300213
],
[
0.303671,
-0.265016,
-0.181425,
-0.213134,
-0.088965,
-0.04468
],
[
-0.648835,
0.74469,
0.914541,
0.761157,
0.399516,
-0.167712
],
[
-0.390782,
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0.67691,
0.089803,
0.080713,
0.52532
]
],
"network.6.bias": [
-0.69491,
-0.302796,
-0.448052,
0.820282,
-0.259811,
-0.208409
],
"network.8.weight": [
[
0.163017,
-0.23299,
0.23728,
0.885476,
-0.578142,
-0.356371
]
],
"network.8.bias": [
0.576862
]
}
## Activation Signature
### 0
fourier: [[44.772005, 45.340100, 222.556951], [49.023329, 56.344829, 150.477270], [46.250634, 52.939776, 114.062403], [59.253550, 72.350813, 240.318949], [44.637042, 48.205691, 314.555197], [50.998432, 60.007402, 263.973475]]
### 2
fourier: [[20.977416, 24.553056, 179.667633], [29.167172, 30.568300, 36.184633], [15.972391, 17.902854, 79.393897], [22.052238, 24.155919, 207.314276], [25.658705, 27.440734, 218.644223], [20.401878, 22.180915, 66.098028]]
### 4
fourier: [[5.331720, 5.474416, 33.830554], [25.353700, 26.368297, 84.490733], [23.872813, 25.343867, 76.130108], [19.818151, 20.830998, 48.687940], [10.922017, 11.634925, 36.663507], [8.921171, 9.591182, 98.478493]]
### 6
fourier: [[9.922962, 10.363402, 96.955362], [4.464440, 4.636210, 41.381238], [0.717058, 0.815874, 42.163606], [15.294422, 15.744705, 17.101251], [56.488890, 58.510797, 186.000761], [26.675144, 27.809076, 81.451114]]
### 8
fourier: [[47.260544, 47.347112, 55.431337]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.083756,
-0.952047,
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-0.400986,
-0.069738
],
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-1.112819,
0.415239,
0.093193
],
[
0.588526,
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-0.289284,
0.086212
],
[
0.358343,
-1.303998,
0.217256,
0.270361,
-1.60255
],
[
0.488923,
0.137818,
0.390617,
0.803498,
0.211819
],
[
0.361212,
0.435449,
-1.732725,
-0.256425,
0.291723
]
],
"network.0.bias": [
-0.059353,
0.219378,
-0.333842,
0.202907,
-0.164771,
-0.366462
],
"network.2.weight": [
[
0.006717,
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-0.054825,
-0.403467,
-0.495624,
0.009871
],
[
-0.457843,
-0.710361,
-0.786926,
-1.093564,
0.45382,
-0.84219
],
[
-0.303977,
-0.821687,
-0.651957,
-0.429193,
0.102138,
-0.350974
],
[
-0.156461,
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0.209835,
-0.144991,
-0.472247,
0.137946
],
[
-0.1785,
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-0.496147,
-0.021927,
-0.514451,
-0.077307
],
[
-0.209078,
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0.108352,
-1.012281,
0.453339,
-0.440304
]
],
"network.2.bias": [
-0.089918,
-0.291357,
-0.566729,
-0.628112,
-0.363413,
-0.481884
],
"network.4.weight": [
[
-0.17908,
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0.630694,
0.13939,
0.407088,
-0.163752
],
[
0.027199,
0.544428,
0.127085,
-0.007538,
-0.119118,
0.846154
],
[
0.261319,
0.766188,
-0.079267,
-0.594746,
-0.011656,
0.520257
],
[
-0.273304,
0.47225,
0.249437,
-0.07082,
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0.605371
],
[
-0.003217,
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0.048213,
-0.211421,
-0.343303,
0.242469
],
[
0.10867,
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-0.549796,
-0.177042,
0.222463,
-0.253148
]
],
"network.4.bias": [
-0.115347,
-0.292091,
-0.259196,
-0.410617,
-0.099192,
-0.672386
],
"network.6.weight": [
[
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-0.249106,
-0.367963,
-0.280172,
0.549099
],
[
0.355222,
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0.004931,
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0.153506
],
[
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],
[
0.303671,
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],
[
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0.914541,
0.761157,
0.399516,
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],
[
-0.390782,
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0.67691,
0.089803,
0.080713,
0.52532
]
],
"network.6.bias": [
-0.69491,
-0.302796,
-0.448052,
0.820282,
-0.259811,
-0.208409
],
"network.8.weight": [
[
0.163017,
-0.23299,
0.23728,
0.885476,
-0.578142,
-0.356371
]
],
"network.8.bias": [
0.576862
]
}
## Activation Signature
### 0
fourier: [[44.772005, 45.340100, 222.556951], [49.023329, 56.344829, 150.477270], [46.250634, 52.939776, 114.062403], [59.253550, 72.350813, 240.318949], [44.637042, 48.205691, 314.555197], [50.998432, 60.007402, 263.973475]]
### 2
fourier: [[20.977416, 24.553056, 179.667633], [29.167172, 30.568300, 36.184633], [15.972391, 17.902854, 79.393897], [22.052238, 24.155919, 207.314276], [25.658705, 27.440734, 218.644223], [20.401878, 22.180915, 66.098028]]
### 4
fourier: [[5.331720, 5.474416, 33.830554], [25.353700, 26.368297, 84.490733], [23.872813, 25.343867, 76.130108], [19.818151, 20.830998, 48.687940], [10.922017, 11.634925, 36.663507], [8.921171, 9.591182, 98.478493]]
### 6
fourier: [[9.922962, 10.363402, 96.955362], [4.464440, 4.636210, 41.381238], [0.717058, 0.815874, 42.163606], [15.294422, 15.744705, 17.101251], [56.488890, 58.510797, 186.000761], [26.675144, 27.809076, 81.451114]]
### 8
fourier: [[47.260544, 47.347112, 55.431337]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [44.77200497285983, 45.3401003124951, 222.5569505020976]}, "1": {"fourier": [49.023328678485704, 56.34482881597546, 150.4772698134184]}, "2": {"fourier": [46.25063367690471, 52.939776421447235, 114.06240332126617]}, "3": {"fourier": [59.253549828791975, 72.35081264674571, 240.31894926726818]}, "4": {"fourier": [44.637041897291226, 48.205691184933116, 314.5551970601082]}, "5": {"fourier": [50.99843191288003, 60.00740217245294, 263.9734746515751]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [20.97741608849175, 24.553055956299612, 179.66763322800398]}, "1": {"fourier": [29.167172020937812, 30.56829958351692, 36.184633016586304]}, "2": {"fourier": [15.97239061399684, 17.902853898267356, 79.39389687776566]}, "3": {"fourier": [22.052238092893216, 24.15591889347896, 207.31427627801895]}, "4": {"fourier": [25.65870518725833, 27.44073422832905, 218.64422258734703]}, "5": {"fourier": [20.401878364903308, 22.1809152552466, 66.09802821278572]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [5.331720446043993, 5.474416305467868, 33.83055438101292]}, "1": {"fourier": [25.353699745370857, 26.368296866626864, 84.49073255062103]}, "2": {"fourier": [23.872812571340365, 25.343867351200565, 76.13010765612125]}, "3": {"fourier": [19.81815129040954, 20.830998237875207, 48.68794038891792]}, "4": {"fourier": [10.922016871190598, 11.63492474918903, 36.663507007062435]}, "5": {"fourier": [8.921171365776898, 9.591181663338652, 98.47849327325821]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [9.922962117345588, 10.36340237006123, 96.95536226034164]}, "1": {"fourier": [4.464439707100626, 4.636210431860703, 41.38123759627342]}, "2": {"fourier": [0.7170575961005344, 0.8158742495060048, 42.163605988025665]}, "3": {"fourier": [15.294422319967603, 15.744705131622304, 17.101251393556595]}, "4": {"fourier": [56.48888998334836, 58.51079706809863, 186.0007612556219]}, "5": {"fourier": [26.67514398663987, 27.809076180418923, 81.45111434906721]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [47.26054429076354, 47.34711240212773, 55.43133682012558]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.083756, -0.952047, 0.177832, -0.400986, -0.069738], [-0.22955, -0.157239, -1.112819, 0.415239, 0.093193], [0.588526, -1.180733, 0.478569, -0.289284, 0.086212], [0.358343, -1.303998, 0.217256, 0.270361, -1.60255], [0.488923, 0.137818, 0.390617, 0.803498, 0.211819], [0.361212, 0.435449, -1.732725, -0.256425, 0.291723]], "network.0.bias": [-0.059353, 0.219378, -0.333842, 0.202907, -0.164771, -0.366462], "network.2.weight": [[0.006717, -0.184306, -0.054825, -0.403467, -0.495624, 0.009871], [-0.457843, -0.710361, -0.786926, -1.093564, 0.45382, -0.84219], [-0.303977, -0.821687, -0.651957, -0.429193, 0.102138, -0.350974], [-0.156461, -0.251286, 0.209835, -0.144991, -0.472247, 0.137946], [-0.1785, -0.126618, -0.496147, -0.021927, -0.514451, -0.077307], [-0.209078, -0.431262, 0.108352, -1.012281, 0.453339, -0.440304]], "network.2.bias": [-0.089918, -0.291357, -0.566729, -0.628112, -0.363413, -0.481884], "network.4.weight": [[-0.17908, -0.150576, 0.630694, 0.13939, 0.407088, -0.163752], [0.027199, 0.544428, 0.127085, -0.007538, -0.119118, 0.846154], [0.261319, 0.766188, -0.079267, -0.594746, -0.011656, 0.520257], [-0.273304, 0.47225, 0.249437, -0.07082, -0.191332, 0.605371], [-0.003217, 0.344386, 0.048213, -0.211421, -0.343303, 0.242469], [0.10867, -0.214673, -0.549796, -0.177042, 0.222463, -0.253148]], "network.4.bias": [-0.115347, -0.292091, -0.259196, -0.410617, -0.099192, -0.672386], "network.6.weight": [[-0.251335, 0.219704, -0.249106, -0.367963, -0.280172, 0.549099], [0.355222, 0.106307, 0.004931, -0.392323, -0.001006, 0.153506], [0.35573, 0.152365, -0.0845, -0.05791, -0.135136, -0.300213], [0.303671, -0.265016, -0.181425, -0.213134, -0.088965, -0.04468], [-0.648835, 0.74469, 0.914541, 0.761157, 0.399516, -0.167712], [-0.390782, 0.371129, 0.67691, 0.089803, 0.080713, 0.52532]], "network.6.bias": [-0.69491, -0.302796, -0.448052, 0.820282, -0.259811, -0.208409], "network.8.weight": [[0.163017, -0.23299, 0.23728, 0.885476, -0.578142, -0.356371]], "network.8.bias": [0.576862]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6861990988254547, "train_acc": 0.57, "val_loss": 0.6828721761703491, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6736620664596558, "train_acc": 0.57, "val_loss": 0.6846058368682861, "val_acc": 0.54}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6557681560516357, "train_acc": 0.57, "val_loss": 0.6414837837219238, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6378332376480103, "train_acc": 0.49, "val_loss": 0.5882374048233032, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6013689935207367, "train_acc": 0.735, "val_loss": 0.5343259572982788, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.560236245393753, "train_acc": 0.755, "val_loss": 0.5067598223686218, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.55873903632164, "train_acc": 0.755, "val_loss": 0.5634090304374695, "val_acc": 0.72}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.5434384047985077, "train_acc": 0.74, "val_loss": 0.53261798620224, "val_acc": 0.74}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.5300597846508026, "train_acc": 0.745, "val_loss": 0.4327771067619324, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.4706147611141205, "train_acc": 0.79, "val_loss": 0.5042104125022888, "val_acc": 0.76}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.4933207035064697, "train_acc": 0.77, "val_loss": 0.47041282057762146, "val_acc": 0.74}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4359677881002426, "train_acc": 0.78, "val_loss": 0.43859946727752686, "val_acc": 0.8}], "summary": {"total_epochs": 12, "degraded_epochs": 3, "improved_epochs": 9, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.6828721761703491, "final_val_loss": 0.6414837837219238, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.5882374048233032, "final_val_loss": 0.43859946727752686, "initial_val_acc": 0.76, "final_val_acc": 0.8, "best_val_acc": 0.8, "best_epoch": 11}, "improvement": 0.26, "first_improvement_epoch": 2}} |
24 | {"target_pattern": "ends_with", "degraded_accuracy": 0.54, "improved_accuracy": 0.92, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1137, "learning_rate": 0.048769761062395736, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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[
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[
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0.045761
],
[
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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## Activation Signature
### 0
fourier: [[33.514743, 33.912605, 69.847936], [34.133512, 35.333493, 122.133849], [37.850554, 39.361771, 138.442564], [20.104842, 21.405281, 114.215365], [29.782817, 30.666483, 39.242700], [27.512079, 28.194953, 251.549658], [46.425722, 56.143399, 166.503278], [30.779864, 32.145270, 148.083967]]
### 2
fourier: [[34.561671, 45.857078, 54.353378], [32.550228, 35.613080, 38.054088], [26.643454, 29.004581, 59.141822], [24.637691, 28.542117, 189.108504], [25.653245, 36.197628, 39.924791], [28.892344, 29.236226, 189.875849], [38.193068, 48.607730, 75.071479], [32.924943, 33.167296, 188.862623]]
### 4
fourier: [[14.315667, 19.696454, 74.988902], [11.991041, 13.261796, 68.045141], [27.253035, 37.284285, 52.272511], [33.574992, 34.838331, 158.027170], [48.032683, 61.313093, 89.502756], [30.529209, 34.688038, 42.327772], [59.086609, 79.251505, 117.802270], [36.141453, 48.053000, 72.717897]]
### 6
fourier: [[30.206753, 37.952397, 177.386379], [36.485545, 40.448497, 129.480666], [47.033702, 55.213799, 161.696056], [39.069562, 44.588837, 151.461896], [22.776973, 25.553719, 30.312824], [44.607454, 54.579452, 158.232271], [40.081824, 42.290102, 217.402008], [44.030159, 49.168612, 167.825912]]
### 8
fourier: [[5.165492, 5.375091, 5.935800], [47.167432, 48.340914, 164.330108], [47.838493, 52.016734, 147.801070], [57.191279, 60.539623, 203.611659], [15.022858, 16.815463, 38.374856], [66.977706, 72.775176, 215.353573], [7.118273, 7.583035, 9.933730], [3.062062, 3.744531, 20.583267]]
### 10
fourier: [[73.214411, 76.129644, 189.962568]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[33.514743, 33.912605, 69.847936], [34.133512, 35.333493, 122.133849], [37.850554, 39.361771, 138.442564], [20.104842, 21.405281, 114.215365], [29.782817, 30.666483, 39.242700], [27.512079, 28.194953, 251.549658], [46.425722, 56.143399, 166.503278], [30.779864, 32.145270, 148.083967]]
### 2
fourier: [[34.561671, 45.857078, 54.353378], [32.550228, 35.613080, 38.054088], [26.643454, 29.004581, 59.141822], [24.637691, 28.542117, 189.108504], [25.653245, 36.197628, 39.924791], [28.892344, 29.236226, 189.875849], [38.193068, 48.607730, 75.071479], [32.924943, 33.167296, 188.862623]]
### 4
fourier: [[14.315667, 19.696454, 74.988902], [11.991041, 13.261796, 68.045141], [27.253035, 37.284285, 52.272511], [33.574992, 34.838331, 158.027170], [48.032683, 61.313093, 89.502756], [30.529209, 34.688038, 42.327772], [59.086609, 79.251505, 117.802270], [36.141453, 48.053000, 72.717897]]
### 6
fourier: [[30.206753, 37.952397, 177.386379], [36.485545, 40.448497, 129.480666], [47.033702, 55.213799, 161.696056], [39.069562, 44.588837, 151.461896], [22.776973, 25.553719, 30.312824], [44.607454, 54.579452, 158.232271], [40.081824, 42.290102, 217.402008], [44.030159, 49.168612, 167.825912]]
### 8
fourier: [[5.165492, 5.375091, 5.935800], [47.167432, 48.340914, 164.330108], [47.838493, 52.016734, 147.801070], [57.191279, 60.539623, 203.611659], [15.022858, 16.815463, 38.374856], [66.977706, 72.775176, 215.353573], [7.118273, 7.583035, 9.933730], [3.062062, 3.744531, 20.583267]]
### 10
fourier: [[73.214411, 76.129644, 189.962568]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [33.51474282020107, 33.912604723313564, 69.84793634340167]}, "1": {"fourier": [34.13351233432678, 35.33349328919194, 122.13384941220284]}, "2": {"fourier": [37.850554030318236, 39.3617712623023, 138.4425642490387]}, "3": {"fourier": [20.104841645122406, 21.405281266485716, 114.21536508202553]}, "4": {"fourier": [29.782817012317608, 30.666483012124733, 39.242699563503265]}, "5": {"fourier": [27.512079381971294, 28.194953220139052, 251.54965817928314]}, "6": {"fourier": [46.425721852808685, 56.143398745909614, 166.5032780021429]}, "7": {"fourier": [30.77986414869891, 32.14526971681863, 148.08396673202515]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [34.56167129273582, 45.85707763846488, 54.35337822511792]}, "1": {"fourier": [32.55022812461287, 35.61307960476636, 38.05408796342052]}, "2": {"fourier": [26.643454158225435, 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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [5.16549233955127, 5.375091122579897, 5.935800495503942]}, "1": {"fourier": [47.16743233588493, 48.34091436294369, 164.33010767120868]}, "2": {"fourier": [47.83849280109939, 52.01673398893443, 147.80106980353594]}, "3": {"fourier": [57.19127927199342, 60.53962349314191, 203.61165902763605]}, "4": {"fourier": [15.02285791543078, 16.815462719169332, 38.374855510890484]}, "5": {"fourier": [66.97770576824169, 72.77517639556488, 215.35357290506363]}, "6": {"fourier": [7.118273300644446, 7.583035231135537, 9.933730417073617]}, "7": {"fourier": [3.0620617952103646, 3.744530632420864, 20.583266615867615]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [73.21441059137703, 76.12964441070255, 189.96256843209267]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.645308, 0.379657, -0.084034, 0.010485, 0.898312], [0.77656, -0.020204, 0.212098, 0.159539, -0.501681], [0.920483, 0.416422, 0.008394, 0.006541, -0.090371], [0.2305, -0.481121, -0.165306, -0.214572, -0.187249], [-0.405419, -0.379155, -0.132144, 0.304647, 0.655507], [-0.16794, -0.08209, -0.538867, -0.465421, 0.045761], [-0.848309, -0.028285, -0.113061, 0.114849, -0.730452], [-0.581881, 0.061268, 0.52749, 0.448461, 0.328387]], "network.0.bias": [-0.067548, 0.261042, -0.286156, 0.357192, 0.445733, -0.369156, 0.147955, -0.210729], "network.2.weight": [[0.741257, -0.244706, 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"improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.48643913865089417, "train_acc": 0.79, "val_loss": 0.318938672542572, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.5197811424732208, "train_acc": 0.81, "val_loss": 0.29612013697624207, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.3559710532426834, "train_acc": 0.885, "val_loss": 0.29936137795448303, "val_acc": 0.88}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.4079792648553848, "train_acc": 0.82, "val_loss": 0.2822044789791107, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.39422306418418884, "train_acc": 0.825, "val_loss": 0.27476146817207336, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.4106794595718384, "train_acc": 0.82, "val_loss": 0.2697916328907013, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 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25 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.46, "improved_accuracy": 0.78, "improvement": 0.32, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9587, "learning_rate": 0.07451702846533188, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.192717,
-0.266209,
-0.355028
],
[
0.097223,
-0.176925,
1.121094,
0.6081,
0.440198,
-0.207707,
0.064144
],
[
-0.138668,
0.165335,
0.243344,
0.219569,
0.643617,
-0.528329,
0.070282
]
],
"network.10.bias": [
-0.090901,
0.35825,
0.675832,
0.182707,
0.143979,
0.590941,
0.515954
],
"network.12.weight": [
[
0.445003,
-0.766139,
-0.867182,
-0.152423,
0.10851,
-0.74477,
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]
],
"network.12.bias": [
-0.402837
]
}
## Activation Signature
### 0
fourier: [[34.562345, 35.832126, 84.160508], [22.001109, 22.623502, 113.045738], [38.425301, 38.743225, 56.211318], [50.986642, 51.245962, 241.963678], [46.787946, 58.180100, 90.962942], [35.188570, 35.855025, 39.137007], [40.429787, 41.843734, 63.741044]]
### 2
fourier: [[18.097830, 21.185943, 23.980340], [14.409134, 14.509348, 25.263908], [12.646068, 16.778740, 82.079848], [21.723977, 33.360476, 122.918662], [22.005286, 23.634603, 26.508674], [15.745444, 23.067963, 105.381267], [23.821247, 24.711432, 31.243917]]
### 4
fourier: [[16.987321, 19.672630, 33.222083], [13.564743, 13.671081, 16.866540], [3.897700, 5.364355, 26.313590], [3.110994, 3.416377, 4.391086], [4.480300, 5.901124, 80.880020], [4.846493, 6.055212, 29.126631], [6.409588, 6.419747, 72.469100]]
### 6
fourier: [[4.505339, 4.990066, 61.232137], [14.259061, 16.316500, 17.544356], [8.406769, 9.630201, 97.773308], [4.971963, 5.318666, 61.433987], [6.618799, 7.635149, 68.958732], [15.653839, 17.842351, 39.156018], [13.119052, 14.790146, 29.711932]]
### 8
fourier: [[0.373910, 0.380990, 34.541992], [9.156632, 10.348486, 57.005844], [11.597760, 13.461089, 132.325543], [5.521773, 6.315820, 112.974788], [24.756935, 27.803632, 109.957690], [8.986894, 10.034864, 46.840470], [8.759166, 9.893462, 50.628560]]
### 10
fourier: [[7.669879, 7.705761, 59.444780], [23.838382, 26.466906, 328.797395], [23.400363, 26.037546, 343.628285], [10.841196, 11.915111, 156.245927], [3.110091, 3.552513, 25.923140], [20.561240, 23.041229, 315.393000], [12.148112, 13.531277, 184.346025]]
### 12
fourier: [[63.259938, 69.883735, 923.899456]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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"network.4.weight": [
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[
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"network.8.weight": [
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[
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[
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"network.10.bias": [
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0.182707,
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"network.12.weight": [
[
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0.10851,
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"network.12.bias": [
-0.402837
]
}
## Activation Signature
### 0
fourier: [[34.562345, 35.832126, 84.160508], [22.001109, 22.623502, 113.045738], [38.425301, 38.743225, 56.211318], [50.986642, 51.245962, 241.963678], [46.787946, 58.180100, 90.962942], [35.188570, 35.855025, 39.137007], [40.429787, 41.843734, 63.741044]]
### 2
fourier: [[18.097830, 21.185943, 23.980340], [14.409134, 14.509348, 25.263908], [12.646068, 16.778740, 82.079848], [21.723977, 33.360476, 122.918662], [22.005286, 23.634603, 26.508674], [15.745444, 23.067963, 105.381267], [23.821247, 24.711432, 31.243917]]
### 4
fourier: [[16.987321, 19.672630, 33.222083], [13.564743, 13.671081, 16.866540], [3.897700, 5.364355, 26.313590], [3.110994, 3.416377, 4.391086], [4.480300, 5.901124, 80.880020], [4.846493, 6.055212, 29.126631], [6.409588, 6.419747, 72.469100]]
### 6
fourier: [[4.505339, 4.990066, 61.232137], [14.259061, 16.316500, 17.544356], [8.406769, 9.630201, 97.773308], [4.971963, 5.318666, 61.433987], [6.618799, 7.635149, 68.958732], [15.653839, 17.842351, 39.156018], [13.119052, 14.790146, 29.711932]]
### 8
fourier: [[0.373910, 0.380990, 34.541992], [9.156632, 10.348486, 57.005844], [11.597760, 13.461089, 132.325543], [5.521773, 6.315820, 112.974788], [24.756935, 27.803632, 109.957690], [8.986894, 10.034864, 46.840470], [8.759166, 9.893462, 50.628560]]
### 10
fourier: [[7.669879, 7.705761, 59.444780], [23.838382, 26.466906, 328.797395], [23.400363, 26.037546, 343.628285], [10.841196, 11.915111, 156.245927], [3.110091, 3.552513, 25.923140], [20.561240, 23.041229, 315.393000], [12.148112, 13.531277, 184.346025]]
### 12
fourier: [[63.259938, 69.883735, 923.899456]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [34.562344616462674, 35.832126283544746, 84.16050776839256]}, "1": {"fourier": [22.001109358579992, 22.623501593076792, 113.04573777318001]}, "2": {"fourier": [38.425301370751335, 38.74322463312014, 56.21131777308651]}, "3": {"fourier": [50.98664155200173, 51.24596246414691, 241.96367835998535]}, "4": {"fourier": [46.7879458784925, 58.18009998024517, 90.96294164657593]}, "5": {"fourier": [35.18856999668903, 35.85502460847616, 39.13700651117991]}, "6": {"fourier": [40.42978699223713, 41.84373382459036, 63.74104422330856]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [18.097829664414416, 21.185942540157242, 23.980339974164963]}, "1": {"fourier": [14.40913382744355, 14.509348025455935, 25.26390752196312]}, "2": {"fourier": [12.646068031649195, 16.778739724189542, 82.07984793186188]}, "3": {"fourier": [21.723976596085702, 33.360476334394015, 122.91866174340248]}, "4": {"fourier": [22.005286282563816, 23.63460318932598, 26.50867444982003]}, "5": {"fourier": [15.745444244263679, 23.067962894785477, 105.38126650452614]}, "6": {"fourier": [23.821247340659177, 24.711431724138723, 31.243916800711304]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [16.987321326509285, 19.6726299828864, 33.22208334505558]}, "1": {"fourier": [13.56474337831068, 13.671080955076986, 16.86654022466573]}, "2": {"fourier": [3.8977004395347077, 5.364354509500992, 26.313589833676815]}, "3": {"fourier": [3.110993681743428, 3.4163773715849635, 4.391085517592728]}, "4": {"fourier": [4.480300162874422, 5.90112360282457, 80.88002049922943]}, "5": {"fourier": [4.846492591040992, 6.055211503940543, 29.126630883663893]}, "6": {"fourier": [6.4095876408612895, 6.419746559429391, 72.46909964084625]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [4.505338819604417, 4.990065506765645, 61.232136964797974]}, "1": {"fourier": [14.259061098354813, 16.31649983269554, 17.54435619711876]}, "2": {"fourier": [8.406769475097427, 9.630200893436268, 97.77330780029297]}, "3": {"fourier": [4.971963421186219, 5.318666404360452, 61.43398654460907]}, "4": {"fourier": [6.618799371521618, 7.635149074485269, 68.95873206853867]}, "5": {"fourier": [15.653839181602194, 17.842351394972386, 39.156018018722534]}, "6": {"fourier": [13.119052314253711, 14.790146456722697, 29.71193167567253]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [0.37390995247145603, 0.3809897978470926, 34.541992127895355]}, "1": {"fourier": [9.156631768491293, 10.348486214898223, 57.005844101309776]}, "2": {"fourier": [11.597760302821403, 13.461088706123727, 132.32554280757904]}, "3": {"fourier": [5.521773258974978, 6.315819761909439, 112.97478783130646]}, "4": {"fourier": [24.756935363358977, 27.80363226344689, 109.95768985152245]}, "5": {"fourier": [8.98689449484275, 10.034864285423533, 46.840470269322395]}, "6": {"fourier": [8.759166315165794, 9.893461775700244, 50.62856036424637]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [7.669878675132926, 7.705761441106431, 59.4447797909379]}, "1": {"fourier": [23.83838219623009, 26.466905636499966, 328.79739502072334]}, "2": {"fourier": [23.40036342957163, 26.03754628908198, 343.6282846927643]}, "3": {"fourier": [10.84119582415268, 11.915111281272104, 156.24592724442482]}, "4": {"fourier": [3.110090764738715, 3.5525126033570906, 25.923140190541744]}, "5": {"fourier": [20.561240057205573, 23.041228987056712, 315.39299950003624]}, "6": {"fourier": [12.148111829055281, 13.531277230831748, 184.346025288105]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [63.25993787474723, 69.88373521546643, 923.8994560241699]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.446924, 0.317161, -0.612356, 0.312758, 0.016563], [0.313184, -0.273998, -0.198908, -0.277551, -0.327674], [0.823149, 0.381943, -0.198241, 0.189464, -1.144593], [-0.346199, 0.025891, -0.483979, 0.1969, -1.020625], [-1.334482, 0.383929, 0.161038, 0.007987, 0.070603], [-1.034742, 0.283348, 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"network.6.bias": [-0.586966, -0.384557, -0.770374, -0.51514, -0.499322, 0.543474, -0.477525], "network.8.weight": [[0.300442, 0.058744, 0.668103, 0.783721, 0.263643, 0.016608, -0.226143], [0.267909, 0.316093, 0.453991, -0.160066, 0.347293, -0.286246, 0.420845], [-0.327998, -0.08035, -0.741644, -0.594807, -0.142817, 0.836302, -0.566703], [-0.470059, -0.007775, -0.986659, -0.549355, -0.259838, 0.187734, -0.30153], [-0.353605, -0.764484, -0.872958, -0.586856, -0.295621, 0.457714, -1.312737], [0.682847, 0.444392, 0.405173, 0.509781, 0.597075, -0.075468, 0.227648], [0.660025, 0.235465, 0.827083, 0.310966, 0.505601, -0.201037, 0.398125]], "network.8.bias": [-0.090924, -0.388816, 0.814411, 0.83225, 0.773412, -0.188691, -0.142489], "network.10.weight": [[-0.051092, 0.408617, -0.388825, -0.68572, 0.61, 0.401969, 0.332318], [0.214787, -0.260393, 0.561089, 0.874835, 1.070302, -0.239752, 0.052156], [-0.028192, -0.122691, 0.750107, 0.582617, 0.979362, -0.088674, -0.291841], [-0.459079, 0.037613, 0.524633, 0.024408, 0.518061, -0.089562, 0.097466], [-0.144576, 0.355382, 0.113169, -0.284716, 0.192717, -0.266209, -0.355028], [0.097223, -0.176925, 1.121094, 0.6081, 0.440198, -0.207707, 0.064144], [-0.138668, 0.165335, 0.243344, 0.219569, 0.643617, -0.528329, 0.070282]], "network.10.bias": [-0.090901, 0.35825, 0.675832, 0.182707, 0.143979, 0.590941, 0.515954], "network.12.weight": [[0.445003, -0.766139, -0.867182, -0.152423, 0.10851, -0.74477, -0.436955]], "network.12.bias": [-0.402837]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6845620572566986, "train_acc": 0.595, "val_loss": 0.7463005185127258, "val_acc": 0.4}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6741257309913635, "train_acc": 0.595, "val_loss": 0.7278268337249756, "val_acc": 0.4}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6667480170726776, "train_acc": 0.595, "val_loss": 0.6657368540763855, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5713185667991638, "train_acc": 0.705, "val_loss": 0.6049469709396362, "val_acc": 0.74}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5174375474452972, "train_acc": 0.75, "val_loss": 0.547045886516571, "val_acc": 0.74}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4357205033302307, "train_acc": 0.785, "val_loss": 0.5137634873390198, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.4054561108350754, "train_acc": 0.84, "val_loss": 0.5081397294998169, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.38523438572883606, "train_acc": 0.82, "val_loss": 0.5676876902580261, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.41669875383377075, "train_acc": 0.77, "val_loss": 0.6053363084793091, "val_acc": 0.76}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.34531112015247345, "train_acc": 0.825, "val_loss": 0.5125599503517151, "val_acc": 0.74}], "summary": {"total_epochs": 10, "degraded_epochs": 3, "improved_epochs": 7, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.7463005185127258, "final_val_loss": 0.6657368540763855, "initial_val_acc": 0.4, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.6049469709396362, "final_val_loss": 0.5125599503517151, "initial_val_acc": 0.74, "final_val_acc": 0.74, "best_val_acc": 0.78, "best_epoch": 7}, "improvement": 0.32, "first_improvement_epoch": 2}} |
26 | {"target_pattern": "starts_with", "degraded_accuracy": 0.48, "improved_accuracy": 0.76, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3187, "learning_rate": 0.06433198685419476, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.12.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[45.374680, 46.960219, 79.824590], [40.337688, 44.171362, 184.464638], [56.693825, 58.612994, 173.333438], [44.100005, 49.576353, 355.041370], [49.344404, 51.885236, 135.238067], [31.669130, 31.882089, 252.950977], [14.311740, 15.388908, 35.043770], [39.956083, 53.652438, 108.122423]]
### 2
fourier: [[13.573038, 13.841355, 93.315623], [33.437343, 37.083815, 166.082894], [68.664188, 72.616454, 292.927231], [66.379542, 68.492049, 299.696428], [87.787009, 92.379864, 349.457486], [30.466175, 33.537264, 141.847414], [69.744237, 76.562196, 224.306879], [41.291562, 43.664467, 165.428469]]
### 4
fourier: [[36.878004, 39.020896, 172.067561], [91.305974, 96.573456, 361.527329], [32.396631, 34.622822, 115.462875], [99.083264, 106.010564, 368.973102], [94.579536, 99.591256, 374.763962], [71.520351, 77.153387, 336.135145], [83.282772, 87.995084, 332.609807], [66.652577, 70.800537, 272.258503]]
### 6
fourier: [[10.175746, 10.729928, 20.562555], [19.220450, 20.369639, 120.326361], [16.553412, 17.899380, 40.775166], [24.560094, 27.784318, 61.041616], [45.443041, 46.987253, 207.238150], [29.596585, 30.441046, 119.980839], [3.798441, 4.546965, 26.249828], [46.272752, 48.754743, 182.357414]]
### 8
fourier: [[4.957018, 5.889290, 82.212297], [22.230670, 22.346372, 101.618392], [18.258474, 20.034400, 99.575811], [41.873215, 45.358415, 197.124639], [34.667522, 34.934648, 101.023868], [22.728598, 24.278296, 100.227549], [41.401153, 42.826235, 112.126608], [54.690432, 55.433008, 209.297533]]
### 10
fourier: [[16.314463, 18.229544, 44.951225], [31.696791, 33.448848, 122.604620], [47.534514, 50.532410, 189.899017], [36.902061, 38.795651, 102.083609], [0.799374, 0.996520, 45.249777], [1.155957, 1.370009, 41.373819], [46.709192, 48.018102, 177.768513], [18.165519, 20.503676, 31.628695]]
### 12
fourier: [[10.856926, 12.084165, 33.644848]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.weight": [
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"network.12.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[45.374680, 46.960219, 79.824590], [40.337688, 44.171362, 184.464638], [56.693825, 58.612994, 173.333438], [44.100005, 49.576353, 355.041370], [49.344404, 51.885236, 135.238067], [31.669130, 31.882089, 252.950977], [14.311740, 15.388908, 35.043770], [39.956083, 53.652438, 108.122423]]
### 2
fourier: [[13.573038, 13.841355, 93.315623], [33.437343, 37.083815, 166.082894], [68.664188, 72.616454, 292.927231], [66.379542, 68.492049, 299.696428], [87.787009, 92.379864, 349.457486], [30.466175, 33.537264, 141.847414], [69.744237, 76.562196, 224.306879], [41.291562, 43.664467, 165.428469]]
### 4
fourier: [[36.878004, 39.020896, 172.067561], [91.305974, 96.573456, 361.527329], [32.396631, 34.622822, 115.462875], [99.083264, 106.010564, 368.973102], [94.579536, 99.591256, 374.763962], [71.520351, 77.153387, 336.135145], [83.282772, 87.995084, 332.609807], [66.652577, 70.800537, 272.258503]]
### 6
fourier: [[10.175746, 10.729928, 20.562555], [19.220450, 20.369639, 120.326361], [16.553412, 17.899380, 40.775166], [24.560094, 27.784318, 61.041616], [45.443041, 46.987253, 207.238150], [29.596585, 30.441046, 119.980839], [3.798441, 4.546965, 26.249828], [46.272752, 48.754743, 182.357414]]
### 8
fourier: [[4.957018, 5.889290, 82.212297], [22.230670, 22.346372, 101.618392], [18.258474, 20.034400, 99.575811], [41.873215, 45.358415, 197.124639], [34.667522, 34.934648, 101.023868], [22.728598, 24.278296, 100.227549], [41.401153, 42.826235, 112.126608], [54.690432, 55.433008, 209.297533]]
### 10
fourier: [[16.314463, 18.229544, 44.951225], [31.696791, 33.448848, 122.604620], [47.534514, 50.532410, 189.899017], [36.902061, 38.795651, 102.083609], [0.799374, 0.996520, 45.249777], [1.155957, 1.370009, 41.373819], [46.709192, 48.018102, 177.768513], [18.165519, 20.503676, 31.628695]]
### 12
fourier: [[10.856926, 12.084165, 33.644848]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [45.37468049032561, 46.96021881370158, 79.82459044456482]}, "1": {"fourier": [40.337687541580294, 44.171362454688875, 184.4646379351616]}, "2": {"fourier": [56.69382496865571, 58.6129936496103, 173.33343800157309]}, "3": {"fourier": [44.1000046259283, 49.57635281077456, 355.0413698554039]}, "4": {"fourier": [49.34440419312077, 51.88523606460145, 135.23806704580784]}, "5": {"fourier": [31.669129611706698, 31.88208860980264, 252.95097652077675]}, "6": {"fourier": [14.311740363375142, 15.38890764318438, 35.043770268559456]}, "7": {"fourier": [39.956082516596, 53.65243761566996, 108.12242321670055]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [13.57303849273587, 13.841354616102421, 93.3156228363514]}, "1": {"fourier": [33.4373433263602, 37.083814790903475, 166.08289368450642]}, "2": {"fourier": [68.66418785917601, 72.61645392020263, 292.92723075300455]}, "3": {"fourier": [66.37954194165808, 68.49204858734247, 299.69642843306065]}, "4": {"fourier": [87.7870093658947, 92.37986381297452, 349.457485742867]}, "5": {"fourier": [30.466175021373335, 33.53726405856309, 141.84741390496492]}, "6": {"fourier": [69.74423659727975, 76.56219597404086, 224.30687922239304]}, "7": {"fourier": [41.29156167337662, 43.664467156241386, 165.42846889793873]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [36.87800445250708, 39.02089591187897, 172.06756073236465]}, "1": {"fourier": [91.3059737640445, 96.57345596593035, 361.5273292735219]}, "2": {"fourier": [32.39663082740245, 34.62282166727331, 115.4628748446703]}, "3": {"fourier": [99.08326442587985, 106.01056414227206, 368.9731017500162]}, "4": {"fourier": [94.5795362681263, 99.59125624346903, 374.7639617919922]}, "5": {"fourier": [71.5203509986803, 77.15338693771179, 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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [4.957017571822808, 5.889289666379198, 82.2122973203659]}, "1": {"fourier": [22.230670007375686, 22.346371668888786, 101.6183916926384]}, "2": {"fourier": [18.258473885566534, 20.034400202566424, 99.57581120729446]}, "3": {"fourier": [41.87321532722363, 45.35841543376708, 197.12463894486427]}, "4": {"fourier": [34.667521639970396, 34.93464831357379, 101.02386789023876]}, "5": {"fourier": [22.72859814120086, 24.27829561142079, 100.22754869237542]}, "6": {"fourier": [41.401153060366724, 42.82623546298516, 112.12660759687424]}, "7": {"fourier": [54.69043208115944, 55.43300814131706, 209.29753310978413]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [16.31446326765734, 18.22954449065695, 44.9512253254652]}, "1": {"fourier": [31.696790744161383, 33.44884769932644, 122.60461973398924]}, "2": {"fourier": [47.53451362724419, 50.53241040019337, 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"neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[1.242671, -0.230995, -0.100294, 0.263329, -0.330882], [0.803948, 0.820418, -0.25863, -0.173373, -0.325053], [1.391867, 0.276981, 0.036921, 0.239779, -0.756694], [-0.712219, -0.627964, -0.35469, -0.141614, -0.117647], [1.288233, 0.078972, 0.02076, 0.239575, -0.598368], [0.265407, -0.386695, -0.323694, -0.346271, -0.566556], [-0.340113, 0.222333, 0.270489, -0.342161, 0.070176], [1.130981, -0.830573, -0.442116, -0.012122, 0.169544]], "network.0.bias": [-0.185675, 0.867094, 0.031045, -0.724607, -0.063528, -0.318733, -0.28909, -0.354893], "network.2.weight": [[0.239121, -0.261258, -0.08514, 0.256144, -0.135037, -0.375882, -0.522987, 0.192492], [-0.182887, 0.013387, -0.241586, 0.064728, -0.469564, -0.127008, -0.733564, 0.261763], [0.189538, 0.950636, 0.526023, 0.599319, -0.034176, -0.335657, -0.218559, 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"global_epoch": 0, "train_loss": 0.6846025586128235, "train_acc": 0.575, "val_loss": 0.7219191789627075, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7021181881427765, "train_acc": 0.575, "val_loss": 0.717491626739502, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6407985985279083, "train_acc": 0.575, "val_loss": 0.6502293348312378, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 1.002207487821579, "train_acc": 0.505, "val_loss": 0.6259327530860901, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5957671701908112, "train_acc": 0.735, "val_loss": 0.6153822541236877, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.6310442984104156, "train_acc": 0.685, "val_loss": 0.6425158977508545, "val_acc": 0.7}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.6620074808597565, "train_acc": 0.655, "val_loss": 0.607649028301239, "val_acc": 0.7}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.6332614123821259, "train_acc": 0.665, "val_loss": 0.5963515639305115, "val_acc": 0.74}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.6111507713794708, "train_acc": 0.72, "val_loss": 0.5445829033851624, "val_acc": 0.76}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.547223299741745, "train_acc": 0.72, "val_loss": 0.48576897382736206, "val_acc": 0.72}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.4613960087299347, "train_acc": 0.72, "val_loss": 0.4676978290081024, "val_acc": 0.72}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4565138518810272, "train_acc": 0.745, "val_loss": 0.4302341043949127, "val_acc": 0.76}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.4332735985517502, "train_acc": 0.755, "val_loss": 0.4262984097003937, "val_acc": 0.72}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.7219191789627075, "final_val_loss": 0.6502293348312378, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6259327530860901, "final_val_loss": 0.4262984097003937, "initial_val_acc": 0.64, "final_val_acc": 0.72, "best_val_acc": 0.76, "best_epoch": 8}, "improvement": 0.28, "first_improvement_epoch": 2}} |
27 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.66, "improved_accuracy": 0.94, "improvement": 0.2799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2749, "learning_rate": 0.05070072171233657, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[33.959687, 36.740328, 90.846509], [38.913417, 40.078848, 308.842023], [38.549400, 44.542310, 103.095125], [30.955291, 35.983633, 252.697794], [39.750978, 41.181083, 52.540191], [28.661749, 33.109224, 168.328167], [52.938245, 55.169681, 227.350015], [60.153368, 62.715405, 306.424075]]
### 2
fourier: [[68.648137, 72.383497, 380.107192], [29.644449, 30.171020, 39.912740], [34.904927, 39.084507, 206.283007], [46.176896, 50.922247, 246.739729], [70.238006, 73.343291, 321.982716], [58.012264, 59.828538, 327.848297], [22.792537, 24.759939, 152.242764], [29.724670, 31.773772, 118.205021]]
### 4
fourier: [[96.272920, 98.321439, 390.230861], [10.724624, 11.902749, 96.799382], [3.642536, 5.103619, 55.523278], [57.381523, 59.957698, 278.691584], [53.126472, 56.202052, 292.440248], [72.466191, 72.769785, 289.689626], [8.999126, 11.856865, 78.036963], [66.976127, 69.185370, 286.779092]]
### 6
fourier: [[169.290688, 170.551800, 652.672017], [49.689405, 52.952681, 68.492524], [136.129181, 137.505525, 544.028903], [49.687468, 50.508571, 248.953982], [49.077243, 51.144196, 54.946840], [154.669969, 155.024819, 608.458873], [21.696169, 21.767781, 111.488980], [41.475490, 41.638354, 45.202603]]
### 8
fourier: [[287.956191, 298.477971, 917.380271]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[33.959687, 36.740328, 90.846509], [38.913417, 40.078848, 308.842023], [38.549400, 44.542310, 103.095125], [30.955291, 35.983633, 252.697794], [39.750978, 41.181083, 52.540191], [28.661749, 33.109224, 168.328167], [52.938245, 55.169681, 227.350015], [60.153368, 62.715405, 306.424075]]
### 2
fourier: [[68.648137, 72.383497, 380.107192], [29.644449, 30.171020, 39.912740], [34.904927, 39.084507, 206.283007], [46.176896, 50.922247, 246.739729], [70.238006, 73.343291, 321.982716], [58.012264, 59.828538, 327.848297], [22.792537, 24.759939, 152.242764], [29.724670, 31.773772, 118.205021]]
### 4
fourier: [[96.272920, 98.321439, 390.230861], [10.724624, 11.902749, 96.799382], [3.642536, 5.103619, 55.523278], [57.381523, 59.957698, 278.691584], [53.126472, 56.202052, 292.440248], [72.466191, 72.769785, 289.689626], [8.999126, 11.856865, 78.036963], [66.976127, 69.185370, 286.779092]]
### 6
fourier: [[169.290688, 170.551800, 652.672017], [49.689405, 52.952681, 68.492524], [136.129181, 137.505525, 544.028903], [49.687468, 50.508571, 248.953982], [49.077243, 51.144196, 54.946840], [154.669969, 155.024819, 608.458873], [21.696169, 21.767781, 111.488980], [41.475490, 41.638354, 45.202603]]
### 8
fourier: [[287.956191, 298.477971, 917.380271]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [33.959686526822466, 36.74032786388327, 90.84650883078575]}, "1": {"fourier": [38.913417207293065, 40.07884818423473, 308.84202349185944]}, "2": {"fourier": [38.54940002816293, 44.542310170080206, 103.09512460976839]}, "3": {"fourier": [30.955290873235242, 35.983632597636245, 252.6977942287922]}, "4": {"fourier": [39.75097818034797, 41.18108341097832, 52.54019078575224]}, "5": {"fourier": [28.661749187376326, 33.10922432179584, 168.32816749624908]}, "6": {"fourier": [52.93824539439956, 55.16968053214631, 227.35001474618912]}, "7": {"fourier": [60.153368418155345, 62.71540465549423, 306.424075037241]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [68.64813678905469, 72.38349668178174, 380.1071915179491]}, "1": {"fourier": [29.644449151436895, 30.171019919154148, 39.91273950959355]}, "2": {"fourier": [34.90492659669173, 39.08450671905276, 206.28300660848618]}, "3": {"fourier": [46.17689629293972, 50.92224695109913, 246.7397286966443]}, "4": {"fourier": [70.2380060851874, 73.34329091080976, 321.9827160835266]}, "5": {"fourier": [58.01226448748731, 59.8285377902341, 327.84829741716385]}, "6": {"fourier": [22.792536586414894, 24.759939225090466, 152.24276420474052]}, "7": {"fourier": [29.724669730800912, 31.77377163295249, 118.20502050220966]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [96.27291966356144, 98.32143943603022, 390.23086073994637]}, "1": {"fourier": [10.724624355070446, 11.902748778034681, 96.7993820309639]}, "2": {"fourier": [3.6425364376674487, 5.103618538182517, 55.52327799797058]}, "3": {"fourier": [57.38152346590847, 59.95769811676859, 278.6915842741728]}, "4": {"fourier": [53.126472187186664, 56.20205162416039, 292.44024845957756]}, "5": {"fourier": [72.46619064830097, 72.76978455401483, 289.68962582945824]}, "6": {"fourier": [8.99912554724695, 11.856865446294028, 78.0369633436203]}, "7": {"fourier": [66.9761273344246, 69.18536995975931, 286.77909173071384]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [169.2906875192134, 170.55179975713654, 652.6720169782639]}, "1": {"fourier": [49.689404748763394, 52.95268059212907, 68.49252432584763]}, "2": {"fourier": [136.12918146600987, 137.50552506588716, 544.0289028417319]}, "3": {"fourier": [49.68746802894825, 50.508570943848135, 248.95398205518723]}, "4": {"fourier": [49.0772431931784, 51.144195682731265, 54.94684037055624]}, "5": {"fourier": [154.66996871987854, 155.0248191498448, 608.4588731527328]}, "6": {"fourier": [21.696169398031756, 21.767780676471297, 111.4889802634716]}, "7": {"fourier": [41.475490123033524, 41.638354072195085, 45.202603240746065]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [287.95619094993816, 298.47797067490643, 917.3802708387375]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.377393, 0.629815, -0.558825, 0.075611, -0.006764], [-0.028318, -0.475295, -0.283588, -0.62407, -0.273693], [0.863127, -0.184328, 0.338957, -0.073696, 0.048064], [-0.26653, -0.268194, -0.422158, -0.19611, -0.36978], [-1.013039, 0.105155, 0.032235, 0.257167, -0.325452], [-0.213247, -0.440501, -0.317108, -0.2973, 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0.069838, 0.049446, -0.314772], "network.4.weight": [[0.342485, -0.467817, -0.022512, 0.274365, 0.592815, 0.27685, -0.128507, 0.393609], [0.196151, -0.399627, 0.032097, 0.198129, -0.065752, -0.418622, -0.085468, 0.140971], [-0.247181, -0.110241, -0.151731, 0.038765, 0.177771, 0.01773, -0.044361, 0.187482], [0.251085, -0.305992, 0.220886, -0.478308, 0.218566, 0.322759, -0.275587, 0.154997], [-0.451303, -0.228649, 0.02954, -0.017151, -0.129532, -0.07628, 0.429001, -0.374551], [-0.009308, -0.339416, -0.060387, -0.110288, 0.419809, 0.468054, -0.156209, 0.44422], [-0.106327, 0.528486, -0.272287, -0.053633, -0.157067, 0.30083, 0.051817, -0.130645], [0.40558, -0.119647, -0.122706, 0.217702, 0.51748, -0.163212, -0.08418, 0.396615]], "network.4.bias": [-0.548589, -0.138229, -0.471658, 0.023675, 0.005137, -0.377779, 0.70331, -0.261721], "network.6.weight": [[0.763718, 0.340289, 0.054685, 0.152477, 0.039426, 0.637119, -0.306473, 0.617856], [-0.240395, 0.41406, -0.230742, 0.049122, 0.110469, -0.370638, 0.677093, 0.017149], [-0.363809, -0.219256, 0.20971, -0.394766, 0.19124, -0.655891, 0.433979, -0.436353], [0.014364, -0.053166, 0.101006, -0.396461, 0.297334, -0.165545, 0.001797, -0.249296], [-0.421306, -0.160894, 0.042639, 0.244873, -0.012937, -0.039673, 0.876745, -0.242328], [0.764775, 0.182331, -0.155982, 0.224547, -0.146071, 0.466087, -0.145464, 0.531665], [-0.272665, -0.220801, -0.030951, 0.271713, 0.278929, -0.015306, -0.102133, -0.176594], [-0.385804, 0.159701, 0.057002, 0.162546, -0.098632, -0.305856, 0.66868, 0.171636]], "network.6.bias": [-0.438068, 0.731995, -0.011156, -0.25002, 0.721856, -0.45668, -0.164587, 0.621425], "network.8.weight": [[-0.819797, 0.654457, -0.336982, -0.196479, 0.803069, -0.859857, 0.100216, 0.609464]], "network.8.bias": [0.416924]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6743853688240051, "train_acc": 0.485, "val_loss": 0.6503248810768127, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.5916574597358704, "train_acc": 0.56, "val_loss": 0.5543653964996338, "val_acc": 0.66}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5309835970401764, "train_acc": 0.68, "val_loss": 0.4443286061286926, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4036610871553421, "train_acc": 0.815, "val_loss": 0.35099586844444275, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.30457304418087006, "train_acc": 0.9, "val_loss": 0.3256129324436188, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.25117411464452744, "train_acc": 0.91, "val_loss": 0.2882990539073944, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.19770872592926025, "train_acc": 0.935, "val_loss": 0.26286062598228455, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.2012033462524414, "train_acc": 0.925, "val_loss": 0.26858171820640564, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.19337020069360733, "train_acc": 0.935, "val_loss": 0.21248863637447357, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.16439596563577652, "train_acc": 0.95, "val_loss": 0.355691522359848, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.29682430624961853, "train_acc": 0.905, "val_loss": 0.2502802312374115, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.24707525223493576, "train_acc": 0.925, "val_loss": 0.17902007699012756, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.6503248810768127, "final_val_loss": 0.5543653964996338, "initial_val_acc": 0.5, "final_val_acc": 0.66, "best_val_acc": 0.66}, "improved_stage": {"initial_val_loss": 0.4443286061286926, "final_val_loss": 0.17902007699012756, "initial_val_acc": 0.78, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 8}, "improvement": 0.2799999999999999, "first_improvement_epoch": 1}} |
28 | {"target_pattern": "starts_with", "degraded_accuracy": 0.52, "improved_accuracy": 0.8, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9304, "learning_rate": 0.04983236602447656, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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],
[
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0.202198,
0.355026,
0.38916
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[
0.84321,
0.343278,
0.129597,
-0.035629,
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],
[
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0.516236,
-0.109277,
0.095473,
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],
[
0.300855,
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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[
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[
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[
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],
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[
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[
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[
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],
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[
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[
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"network.10.weight": [
[
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]
],
"network.10.bias": [
0.469116
]
}
## Activation Signature
### 0
fourier: [[41.500901, 42.544293, 119.224088], [27.291163, 31.638331, 95.871562], [37.235842, 39.601690, 196.610214], [39.462584, 41.327971, 148.607706], [19.107824, 19.536476, 21.614866]]
### 2
fourier: [[57.579965, 58.792728, 214.843055], [62.137323, 74.941854, 307.301537], [14.575497, 16.024454, 16.655229], [15.913523, 16.756592, 26.775269], [16.526913, 18.302274, 19.649622]]
### 4
fourier: [[88.525129, 103.210546, 410.535171], [2.571118, 2.670510, 70.126122], [19.323118, 19.768700, 20.619958], [16.863958, 16.908529, 29.353840], [39.405859, 46.184645, 192.780828]]
### 6
fourier: [[51.762594, 58.347983, 158.643296], [72.903913, 82.102142, 263.118153], [1.899957, 1.975447, 83.798709], [13.392451, 16.424677, 16.784060], [6.657324, 7.152092, 13.075520]]
### 8
fourier: [[65.551693, 74.040023, 162.969856], [74.131451, 83.510748, 231.817273], [28.264805, 32.647093, 44.531201], [1.529545, 1.865927, 27.802282], [5.904059, 6.083987, 26.126411]]
### 10
fourier: [[53.925255, 59.833657, 117.181964]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.637466,
0.454043,
0.348941,
0.067328,
-0.891464
],
[
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0.218992,
0.202198,
0.355026,
0.38916
],
[
0.84321,
0.343278,
0.129597,
-0.035629,
-0.252364
],
[
0.983542,
0.516236,
-0.109277,
0.095473,
-0.010169
],
[
0.300855,
-0.269671,
0.121111,
0.296057,
-0.478488
]
],
"network.0.bias": [
-0.069756,
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0.626641,
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0.05944
],
"network.2.weight": [
[
0.507676,
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0.673271,
0.300364,
-0.051342
],
[
0.802524,
-0.198936,
0.649256,
0.405123,
0.34132
],
[
0.113808,
0.20699,
0.036465,
-0.361363,
-0.470437
],
[
-0.143222,
0.269209,
-0.119171,
-0.095833,
-0.047246
],
[
-0.085124,
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0.35188,
0.037619,
-0.105156
]
],
"network.2.bias": [
0.183097,
0.148091,
0.356804,
0.040506,
-0.446451
],
"network.4.weight": [
[
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0.666339,
0.130845,
-0.303752,
0.599905
],
[
0.058805,
0.050314,
0.032764,
0.160635,
-0.545162
],
[
-0.080025,
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0.38008,
0.028293,
-0.724812
],
[
-0.007656,
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0.477309,
-0.054432,
-0.823228
],
[
0.304995,
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-0.273003,
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]
],
"network.4.bias": [
0.209713,
0.531547,
0.463431,
0.685918,
0.225602
],
"network.6.weight": [
[
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0.327072
],
[
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-0.791286,
0.577637
],
[
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0.121458,
0.149629,
0.130396
],
[
-0.227572,
0.030646,
0.576325,
0.671302,
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],
[
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0.176398,
0.088478,
-0.06289,
0.41535
]
],
"network.6.bias": [
-0.224271,
0.384757,
0.427498,
-0.058545,
0.059267
],
"network.8.weight": [
[
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0.344848,
0.334235,
0.045277
],
[
0.578784,
0.645048,
-0.582653,
-0.260803,
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],
[
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[
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0.042127
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[
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]
],
"network.8.bias": [
0.538867,
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0.496335,
-0.042164,
-0.118404
],
"network.10.weight": [
[
0.195157,
-0.715737,
0.239508,
0.36772,
-0.139969
]
],
"network.10.bias": [
0.469116
]
}
## Activation Signature
### 0
fourier: [[41.500901, 42.544293, 119.224088], [27.291163, 31.638331, 95.871562], [37.235842, 39.601690, 196.610214], [39.462584, 41.327971, 148.607706], [19.107824, 19.536476, 21.614866]]
### 2
fourier: [[57.579965, 58.792728, 214.843055], [62.137323, 74.941854, 307.301537], [14.575497, 16.024454, 16.655229], [15.913523, 16.756592, 26.775269], [16.526913, 18.302274, 19.649622]]
### 4
fourier: [[88.525129, 103.210546, 410.535171], [2.571118, 2.670510, 70.126122], [19.323118, 19.768700, 20.619958], [16.863958, 16.908529, 29.353840], [39.405859, 46.184645, 192.780828]]
### 6
fourier: [[51.762594, 58.347983, 158.643296], [72.903913, 82.102142, 263.118153], [1.899957, 1.975447, 83.798709], [13.392451, 16.424677, 16.784060], [6.657324, 7.152092, 13.075520]]
### 8
fourier: [[65.551693, 74.040023, 162.969856], [74.131451, 83.510748, 231.817273], [28.264805, 32.647093, 44.531201], [1.529545, 1.865927, 27.802282], [5.904059, 6.083987, 26.126411]]
### 10
fourier: [[53.925255, 59.833657, 117.181964]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [41.50090114355532, 42.54429307863103, 119.22408805787563]}, "1": {"fourier": [27.29116327241598, 31.63833101843875, 95.87156209349632]}, "2": {"fourier": [37.235842030770876, 39.60168987944463, 196.61021414399147]}, "3": {"fourier": [39.462584281734884, 41.32797131389661, 148.6077055335045]}, "4": {"fourier": [19.1078242807177, 19.536476307465957, 21.614865690469742]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [57.57996503534982, 58.7927282976419, 214.84305460751057]}, "1": {"fourier": [62.137322806403134, 74.9418542522453, 307.3015370219946]}, "2": {"fourier": [14.575496985352547, 16.024454234377956, 16.655228914083278]}, "3": {"fourier": [15.91352255523542, 16.75659217010874, 26.775268781930208]}, "4": {"fourier": [16.52691299189367, 18.302274137735367, 19.649621578670544]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [88.52512902952338, 103.21054590024967, 410.53517147898674]}, "1": {"fourier": [2.5711182806692143, 2.6705096663390377, 70.12612223625183]}, "2": {"fourier": [19.323118215889522, 19.768699921301895, 20.619958317374333]}, "3": {"fourier": [16.86395840358296, 16.908529165245472, 29.35384038090706]}, "4": {"fourier": [39.40585855920377, 46.184645297083634, 192.78082817047834]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [51.76259373711319, 58.34798315215222, 158.6432961076498]}, "1": {"fourier": [72.90391253111525, 82.10214154932919, 263.11815340816975]}, "2": {"fourier": [1.8999566002689743, 1.9754473302386324, 83.79870903491974]}, "3": {"fourier": [13.392451266237165, 16.424677169450757, 16.784059978739048]}, "4": {"fourier": [6.657323665845186, 7.152091705520361, 13.075520008802414]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [65.55169288740743, 74.04002306696256, 162.96985641121864]}, "1": {"fourier": [74.1314505388799, 83.51074754870683, 231.817272529006]}, "2": {"fourier": [28.264804960727478, 32.64709335857341, 44.531201273202896]}, "3": {"fourier": [1.5295452233970566, 1.8659265134775176, 27.802281633019447]}, "4": {"fourier": [5.904058513133292, 6.0839872639317285, 26.126411348581314]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [53.925254836826134, 59.833656929589104, 117.18196418881416]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | 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[0.538867, -0.016778, 0.496335, -0.042164, -0.118404], "network.10.weight": [[0.195157, -0.715737, 0.239508, 0.36772, -0.139969]], "network.10.bias": [0.469116]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.721134215593338, "train_acc": 0.435, "val_loss": 0.684816837310791, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6809460520744324, "train_acc": 0.565, "val_loss": 0.6651077270507812, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6406665146350861, "train_acc": 0.565, "val_loss": 0.6224706172943115, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6599564552307129, "train_acc": 0.58, "val_loss": 0.5935121774673462, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6077246367931366, "train_acc": 0.715, "val_loss": 0.5131999850273132, "val_acc": 0.72}, {"stage": "improved", "epoch": 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"train_acc": 0.75, "val_loss": 0.46696949005126953, "val_acc": 0.76}], "summary": {"total_epochs": 12, "degraded_epochs": 3, "improved_epochs": 9, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.684816837310791, "final_val_loss": 0.6224706172943115, "initial_val_acc": 0.56, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5935121774673462, "final_val_loss": 0.46696949005126953, "initial_val_acc": 0.76, "final_val_acc": 0.76, "best_val_acc": 0.8, "best_epoch": 6}, "improvement": 0.28, "first_improvement_epoch": 2}} |
29 | {"target_pattern": "vowel_consonant", "degraded_accuracy": 0.52, "improved_accuracy": 0.68, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9762, "learning_rate": 0.031389579657191864, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "vowel_consonant", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["vowel_consonant"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[21.517327, 22.537296, 152.212060], [18.257370, 18.680253, 122.771833], [24.739668, 27.221697, 73.851337], [20.798239, 21.737862, 24.488797], [17.298565, 18.624956, 18.961800], [25.334467, 28.722379, 191.620570], [29.377714, 41.684487, 255.449728]]
### 2
fourier: [[8.325445, 9.073299, 24.927183], [9.388470, 9.443221, 46.916490], [8.577194, 10.272357, 20.817848], [10.139239, 11.500004, 36.139270], [8.772211, 10.938799, 34.922345], [9.165468, 9.248953, 11.268060], [3.571273, 3.662889, 58.415774]]
### 4
fourier: [[12.203123, 13.255877, 23.676062], [5.050482, 5.112799, 14.047098], [11.347478, 12.733092, 16.638672], [16.774987, 19.636696, 20.353895], [16.151927, 16.437055, 18.228807], [7.823596, 8.450148, 9.972702], [9.324182, 10.249463, 29.598717]]
### 6
fourier: [[11.256555, 12.554508, 13.780076], [17.054432, 18.598481, 27.189388], [12.297332, 14.713303, 15.978400], [10.676714, 11.716066, 47.519206], [13.338406, 16.506381, 18.117322], [17.626462, 19.059283, 42.202895], [19.548531, 21.471053, 64.155638]]
### 8
fourier: [[41.403545, 45.673674, 118.898965], [30.348448, 33.430033, 53.454053], [34.225205, 37.773334, 67.072452], [24.221140, 24.936751, 27.491229], [35.001136, 38.601768, 76.197275], [4.832520, 5.334640, 22.322449], [28.055549, 30.950523, 50.810356]]
### 10
fourier: [[10.368175, 11.856250, 13.111919], [15.137980, 15.365572, 16.929564], [48.408559, 53.333404, 122.953261], [18.727402, 22.754802, 25.082296], [22.889850, 25.192090, 29.020402], [48.907488, 53.880911, 105.402970], [33.929553, 37.345536, 56.679094]]
### 12
fourier: [[43.145323, 47.509720, 64.107849]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| vowel_consonant | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
fourier: [[21.517327, 22.537296, 152.212060], [18.257370, 18.680253, 122.771833], [24.739668, 27.221697, 73.851337], [20.798239, 21.737862, 24.488797], [17.298565, 18.624956, 18.961800], [25.334467, 28.722379, 191.620570], [29.377714, 41.684487, 255.449728]]
### 2
fourier: [[8.325445, 9.073299, 24.927183], [9.388470, 9.443221, 46.916490], [8.577194, 10.272357, 20.817848], [10.139239, 11.500004, 36.139270], [8.772211, 10.938799, 34.922345], [9.165468, 9.248953, 11.268060], [3.571273, 3.662889, 58.415774]]
### 4
fourier: [[12.203123, 13.255877, 23.676062], [5.050482, 5.112799, 14.047098], [11.347478, 12.733092, 16.638672], [16.774987, 19.636696, 20.353895], [16.151927, 16.437055, 18.228807], [7.823596, 8.450148, 9.972702], [9.324182, 10.249463, 29.598717]]
### 6
fourier: [[11.256555, 12.554508, 13.780076], [17.054432, 18.598481, 27.189388], [12.297332, 14.713303, 15.978400], [10.676714, 11.716066, 47.519206], [13.338406, 16.506381, 18.117322], [17.626462, 19.059283, 42.202895], [19.548531, 21.471053, 64.155638]]
### 8
fourier: [[41.403545, 45.673674, 118.898965], [30.348448, 33.430033, 53.454053], [34.225205, 37.773334, 67.072452], [24.221140, 24.936751, 27.491229], [35.001136, 38.601768, 76.197275], [4.832520, 5.334640, 22.322449], [28.055549, 30.950523, 50.810356]]
### 10
fourier: [[10.368175, 11.856250, 13.111919], [15.137980, 15.365572, 16.929564], [48.408559, 53.333404, 122.953261], [18.727402, 22.754802, 25.082296], [22.889850, 25.192090, 29.020402], [48.907488, 53.880911, 105.402970], [33.929553, 37.345536, 56.679094]]
### 12
fourier: [[43.145323, 47.509720, 64.107849]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
vowel_consonant | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.517327458541644, 22.537296275459333, 152.21206046640873]}, "1": {"fourier": [18.257370296411466, 18.680253422966633, 122.77183282375336]}, "2": {"fourier": [24.73966816680374, 27.22169714936031, 73.85133681446314]}, "3": {"fourier": [20.798239248141588, 21.737861663250836, 24.488796862049888]}, "4": {"fourier": [17.298564854204304, 18.624956312832524, 18.96179960570133]}, "5": {"fourier": [25.334467200227216, 28.72237876068255, 191.62056957185268]}, "6": {"fourier": [29.377713791137353, 41.68448714406035, 255.44972813129425]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [8.32544457273786, 9.07329869761813, 24.9271829277277]}, "1": {"fourier": [9.388469848910999, 9.443220894412672, 46.9164899289608]}, "2": {"fourier": [8.57719414825514, 10.272357062293535, 20.817847922444344]}, "3": {"fourier": [10.139238787223771, 11.500003599131096, 36.1392697840929]}, "4": {"fourier": [8.772211401867692, 10.938799008768015, 34.922344621270895]}, "5": {"fourier": [9.165467905171463, 9.248952532089147, 11.268059607595205]}, "6": {"fourier": [3.5712729559714558, 3.6628887570886266, 58.415774285793304]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [12.203122696834622, 13.255877287364058, 23.676062058657408]}, "1": {"fourier": [5.050481558436138, 5.112799168056399, 14.047097980976105]}, "2": {"fourier": [11.347477704541095, 12.733091883104393, 16.638671830296516]}, "3": {"fourier": [16.77498655984235, 19.63669591090479, 20.353894531726837]}, "4": {"fourier": [16.151926730156184, 16.437054613422593, 18.228806659620076]}, "5": {"fourier": [7.823595820713541, 8.4501482825849, 9.97270192943342]}, "6": {"fourier": [9.32418209367044, 10.249462899328423, 29.598717093467712]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [11.256554843099202, 12.554508139145904, 13.780076418071985]}, "1": {"fourier": [17.054431760934136, 18.598481393330285, 27.189388006925583]}, "2": {"fourier": [12.297331795096397, 14.713302944995288, 15.978399646592651]}, "3": {"fourier": [10.676713906288882, 11.716066115987838, 47.51920594274998]}, "4": {"fourier": [13.33840645131328, 16.50638124707497, 18.117321567952697]}, "5": {"fourier": [17.626461722075813, 19.05928304450542, 42.20289481244981]}, "6": {"fourier": [19.54853112945476, 21.471053442429792, 64.15563756972551]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [41.4035453682263, 45.67367388534167, 118.89896526932716]}, "1": {"fourier": [30.34844830441559, 33.43003310076942, 53.45405298471451]}, "2": {"fourier": [34.2252054902878, 37.77333431223088, 67.07245200127363]}, "3": {"fourier": [24.22114035487175, 24.93675131067872, 27.49122851857334]}, "4": {"fourier": [35.00113618029125, 38.60176806533602, 76.19727496057749]}, "5": {"fourier": [4.832519750182358, 5.334640297472241, 22.322448700666428]}, "6": {"fourier": [28.055549000926955, 30.950522656943356, 50.81035587191582]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [10.36817467212677, 11.856250417436735, 13.111918615907863]}, "1": {"fourier": [15.137979630380869, 15.365572033259586, 16.929564136564302]}, "2": {"fourier": [48.4085594175998, 53.33340393365098, 122.9532608538866]}, "3": {"fourier": [18.72740211576073, 22.75480190848912, 25.082296066961067]}, "4": {"fourier": [22.88984973864234, 25.192090450861855, 29.020401641726494]}, "5": {"fourier": [48.90748804066983, 53.88091143637897, 105.40297006443143]}, "6": {"fourier": [33.929553386602464, 37.345535772144274, 56.679094389081]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [43.145322919351635, 47.50972042934851, 64.10784894227982]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.141766, -0.269499, -0.074746, -0.301307, -0.089205], [-0.125239, 0.245829, 0.159407, 0.351421, -0.348004], [0.172833, -0.051955, 0.522827, -0.233264, -0.004806], [-0.467623, 0.515051, 0.284777, -0.393314, 0.250336], [-0.17105, 0.462593, -0.070049, -0.419458, 0.121312], 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-0.467778, 0.74211, 0.470468, -0.369335, 0.59609], [0.297534, -0.008343, 0.301652, -0.339377, -0.008786, 0.148404, 0.101493], [0.376637, 0.455735, 0.58245, -0.243418, -0.488389, 0.006733, -0.25897], [-0.150994, -0.483128, -0.311318, 0.568262, 0.258223, -0.446828, 0.353328]], "network.10.bias": [0.349648, -0.043862, 0.169159, -0.011966, -0.248912, -0.032861, -0.005521], "network.12.weight": [[0.363874, 0.132538, -0.227372, 0.552799, -0.226363, -0.474856, 0.448621]], "network.12.bias": [0.058674]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6849014759063721, "train_acc": 0.56, "val_loss": 0.699297308921814, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6905262172222137, "train_acc": 0.56, "val_loss": 0.6990209817886353, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6844393312931061, "train_acc": 0.56, "val_loss": 0.6901495456695557, "val_acc": 0.52}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6803970038890839, "train_acc": 0.56, "val_loss": 0.6749976277351379, "val_acc": 0.52}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6645597815513611, "train_acc": 0.56, "val_loss": 0.6343173384666443, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6447279453277588, "train_acc": 0.53, "val_loss": 0.6264511942863464, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5819639265537262, "train_acc": 0.68, "val_loss": 0.5805508494377136, "val_acc": 0.66}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.557720422744751, "train_acc": 0.69, "val_loss": 0.7415837049484253, "val_acc": 0.62}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5368293970823288, "train_acc": 0.73, "val_loss": 0.8616243004798889, "val_acc": 0.64}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5937686562538147, "train_acc": 0.725, "val_loss": 0.6279721260070801, "val_acc": 0.68}], "summary": {"total_epochs": 10, "degraded_epochs": 5, "improved_epochs": 5, "patterns": ["vowel_consonant"], "degraded_stage": {"initial_val_loss": 0.699297308921814, "final_val_loss": 0.6343173384666443, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.6264511942863464, "final_val_loss": 0.6279721260070801, "initial_val_acc": 0.64, "final_val_acc": 0.68, "best_val_acc": 0.68, "best_epoch": 9}, "improvement": 0.16000000000000003, "first_improvement_epoch": 4}} |
30 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.48, "improved_accuracy": 0.88, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3215, "learning_rate": 0.02854826421987649, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[23.813195, 26.842800, 82.472488], [22.442717, 27.710281, 46.841207], [32.857901, 33.302060, 151.864486], [30.244861, 31.643388, 114.287300], [14.604828, 16.055292, 37.186264], [43.928326, 47.108886, 108.596674], [24.527915, 24.862496, 124.794146], [17.728297, 22.268743, 31.691904]]
### 2
fourier: [[28.503379, 29.625062, 97.725552], [26.580942, 26.967970, 54.135428], [11.401685, 12.163069, 53.659039], [33.065230, 33.259677, 176.309150], [43.690750, 45.334801, 181.184050], [34.687929, 35.901304, 185.167566], [20.345748, 22.472685, 74.377362], [62.188543, 63.483840, 227.220249]]
### 4
fourier: [[40.527396, 41.136222, 146.421313], [79.553121, 80.341992, 341.883710], [71.124422, 71.279516, 298.279004], [24.329400, 24.992082, 132.676512], [42.712943, 43.112652, 149.870613], [51.588043, 52.053574, 265.186964], [49.813669, 50.224926, 204.494513], [16.504752, 17.009067, 17.264853]]
### 6
fourier: [[99.759012, 99.966987, 363.419971], [35.199870, 35.912227, 98.399970], [2.195875, 2.358467, 29.653039], [84.585950, 86.116458, 307.708345], [30.534920, 31.613448, 63.106689], [112.241389, 112.654330, 444.924849], [119.879959, 120.974133, 451.214619], [29.597556, 30.232940, 55.932578]]
### 8
fourier: [[57.607401, 59.099053, 163.467879], [177.589156, 178.256245, 645.634639], [143.407676, 144.035597, 515.159343], [65.466605, 65.515474, 312.004142], [16.477816, 17.132330, 47.042186], [50.724756, 52.404579, 146.084414], [3.551328, 3.734104, 7.512600], [211.563883, 214.061640, 776.161740]]
### 10
fourier: [[220.563817, 222.414384, 792.273202]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[23.813195, 26.842800, 82.472488], [22.442717, 27.710281, 46.841207], [32.857901, 33.302060, 151.864486], [30.244861, 31.643388, 114.287300], [14.604828, 16.055292, 37.186264], [43.928326, 47.108886, 108.596674], [24.527915, 24.862496, 124.794146], [17.728297, 22.268743, 31.691904]]
### 2
fourier: [[28.503379, 29.625062, 97.725552], [26.580942, 26.967970, 54.135428], [11.401685, 12.163069, 53.659039], [33.065230, 33.259677, 176.309150], [43.690750, 45.334801, 181.184050], [34.687929, 35.901304, 185.167566], [20.345748, 22.472685, 74.377362], [62.188543, 63.483840, 227.220249]]
### 4
fourier: [[40.527396, 41.136222, 146.421313], [79.553121, 80.341992, 341.883710], [71.124422, 71.279516, 298.279004], [24.329400, 24.992082, 132.676512], [42.712943, 43.112652, 149.870613], [51.588043, 52.053574, 265.186964], [49.813669, 50.224926, 204.494513], [16.504752, 17.009067, 17.264853]]
### 6
fourier: [[99.759012, 99.966987, 363.419971], [35.199870, 35.912227, 98.399970], [2.195875, 2.358467, 29.653039], [84.585950, 86.116458, 307.708345], [30.534920, 31.613448, 63.106689], [112.241389, 112.654330, 444.924849], [119.879959, 120.974133, 451.214619], [29.597556, 30.232940, 55.932578]]
### 8
fourier: [[57.607401, 59.099053, 163.467879], [177.589156, 178.256245, 645.634639], [143.407676, 144.035597, 515.159343], [65.466605, 65.515474, 312.004142], [16.477816, 17.132330, 47.042186], [50.724756, 52.404579, 146.084414], [3.551328, 3.734104, 7.512600], [211.563883, 214.061640, 776.161740]]
### 10
fourier: [[220.563817, 222.414384, 792.273202]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [23.81319535991978, 26.842799815116, 82.47248849272728]}, "1": {"fourier": [22.44271654332474, 27.710280991734532, 46.841206565499306]}, "2": {"fourier": [32.85790058524527, 33.302059934236915, 151.86448588222265]}, "3": {"fourier": [30.244861369799327, 31.643387740094173, 114.28729973733425]}, "4": {"fourier": [14.604827697894894, 16.055292469570794, 37.18626383692026]}, "5": {"fourier": [43.92832628504041, 47.1088862244661, 108.59667430818081]}, "6": {"fourier": [24.527915351377565, 24.862495688986815, 124.79414635896683]}, "7": {"fourier": [17.72829715186427, 22.26874268851096, 31.691904306411743]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [28.503379264444558, 29.625062233521863, 97.72555232048035]}, "1": {"fourier": [26.58094178662777, 26.967969566215917, 54.13542766869068]}, "2": {"fourier": [11.401685298989456, 12.163068930379932, 53.65903860330582]}, "3": {"fourier": [33.06522958506146, 33.25967698063276, 176.3091499209404]}, "4": {"fourier": [43.69074971950957, 45.334800907471006, 181.18404995650053]}, "5": {"fourier": [34.687928926012624, 35.90130384073285, 185.1675659045577]}, "6": {"fourier": [20.345747871222873, 22.472684683402765, 74.37736174464226]}, "7": {"fourier": [62.188542966711616, 63.48384025084498, 227.22024910151958]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [40.52739611507392, 41.13622232241861, 146.42131251096725]}, "1": {"fourier": [79.55312090779094, 80.34199229744195, 341.8837103098631]}, "2": {"fourier": [71.12442237530625, 71.27951617477179, 298.279004432261]}, "3": {"fourier": [24.32940008072078, 24.992082117026307, 132.67651181668043]}, "4": {"fourier": [42.71294263049415, 43.112651727285176, 149.87061268091202]}, "5": {"fourier": [51.58804296818325, 52.05357411160357, 265.1869640946388]}, "6": {"fourier": [49.81366948669382, 50.22492586835135, 204.49451299756765]}, "7": {"fourier": [16.504752095046527, 17.00906676770826, 17.26485338889437]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [99.75901230595103, 99.96698700077296, 363.4199712276459]}, "1": {"fourier": [35.199869750335466, 35.91222716137164, 98.3999695032835]}, "2": {"fourier": [2.1958747657709132, 2.3584672236665756, 29.653039306402206]}, "3": {"fourier": [84.58595041222698, 86.11645801335216, 307.70834462344646]}, "4": {"fourier": [30.534920404238814, 31.613448356199697, 63.106689497828484]}, "5": {"fourier": [112.2413888541914, 112.6543296032351, 444.92484923265874]}, "6": {"fourier": [119.87995931584467, 120.97413348194216, 451.21461856365204]}, "7": {"fourier": [29.597556280547316, 30.232940332722148, 55.932578071951866]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [57.607401446637596, 59.099052500836684, 163.46787889301777]}, "1": {"fourier": [177.5891561371795, 178.25624532549298, 645.6346390843391]}, "2": {"fourier": [143.407676054074, 144.0355967641235, 515.1593430042267]}, "3": {"fourier": [65.46660547188308, 65.51547374095038, 312.00414204597473]}, "4": {"fourier": [16.477815695153474, 17.13233002018969, 47.042185977101326]}, "5": {"fourier": [50.724756341620974, 52.404578805451855, 146.08441427350044]}, "6": {"fourier": [3.5513283032304925, 3.734103797864117, 7.512600302696228]}, "7": {"fourier": [211.56388258774254, 214.06163956035658, 776.1617401093245]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [220.56381716258858, 222.41438397452848, 792.2732016891241]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": 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[0.501271, -0.331194, -0.002679, 0.335275, 0.449265, 0.27123, -0.413552, 0.484757], [-0.279388, 0.52301, -0.285174, 0.585412, 0.151415, -0.264554, 0.227056, 0.08691], [0.20638, -0.496048, -0.388568, 0.320439, 0.282042, 0.425676, -0.030683, 0.249569], [-0.449822, -0.02033, 0.358726, -0.529811, -0.266742, 0.324765, 0.406861, -0.226432], [0.272578, 0.029909, -0.257314, 0.309362, 0.337743, 0.591773, -0.66508, 0.327602], [-0.320746, 0.052574, 0.01217, 0.316925, -0.290049, -0.319706, 0.633776, -0.087305]], "network.4.bias": [-0.158301, 0.329304, 0.090624, 0.07193, -0.287087, -0.333012, -0.065276, 0.348307], "network.6.weight": [[0.408451, 0.319488, 0.383484, -0.199601, 0.445184, 0.461108, 0.288625, -0.187063], [-0.726913, 0.008286, -0.329213, 0.408861, -0.302959, -0.192993, 0.425319, 0.030129], [0.340156, 0.073644, -0.526733, 0.06688, 0.509074, -0.05396, -0.074636, 0.180146], [0.210992, 0.316048, 0.295161, -0.21434, 0.455388, 0.31227, 0.273452, -0.605415], [-0.304262, -0.275283, 0.251565, 0.418543, -0.479375, -0.256563, -0.037836, 0.472873], [0.323517, 0.550025, 0.076951, 0.289859, 0.323596, -0.13646, 0.560471, -0.4442], [0.416714, 0.617101, 0.492014, 0.267732, 0.06536, 0.327675, 0.158155, -0.564276], [-0.212536, -0.206583, 0.099266, 0.542897, -0.392416, -0.079544, -0.123097, 0.261873]], "network.6.bias": [-0.124576, 0.1102, -0.258623, -0.011914, 0.202829, -0.016977, -0.282708, 0.302662], "network.8.weight": [[-0.330267, 0.398218, -0.272444, -0.124896, 0.139018, 0.288715, -0.389764, 0.108393], [0.443453, -0.186327, 0.011187, 0.483033, -0.198301, 0.599933, 0.209379, 0.021455], [0.191972, -0.105174, -0.306897, 0.566524, -0.174418, 0.286413, 0.369427, 0.002775], [0.217563, 0.284213, -0.171551, -0.211361, -0.025005, -0.36829, -0.233583, -0.255069], [-0.223483, 0.172994, 0.190781, -0.086856, 0.195702, -0.123775, 0.230754, 0.08823], [0.002633, 0.433158, 0.107696, -0.492014, 0.567141, 0.121802, -0.165043, 0.455139], [-0.050251, -0.094331, -0.436257, -0.287907, 0.103842, 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"val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6181693375110626, "train_acc": 0.505, "val_loss": 0.5599610805511475, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5407193750143051, "train_acc": 0.505, "val_loss": 0.540509819984436, "val_acc": 0.68}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5029391646385193, "train_acc": 0.735, "val_loss": 0.46002280712127686, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.457137793302536, "train_acc": 0.825, "val_loss": 0.43994006514549255, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.43731898069381714, "train_acc": 0.815, "val_loss": 0.3820137679576874, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.38191719353199005, "train_acc": 0.835, "val_loss": 0.34198933839797974, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, 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31 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.7, "improved_accuracy": 0.96, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4009, "learning_rate": 0.03724346377980019, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[25.498399, 28.010241, 83.788923], [25.586316, 28.592422, 87.132695], [35.580069, 40.771416, 219.865125], [27.435832, 30.247990, 37.327176], [21.879774, 22.965042, 42.310499], [25.864087, 26.853515, 126.918515], [12.955239, 15.482719, 72.150297]]
### 2
fourier: [[37.259762, 37.288170, 209.279569], [19.475747, 23.292406, 49.162166], [39.753946, 40.473639, 47.612079], [24.531095, 30.279521, 39.870306], [19.731421, 20.687978, 51.115194], [17.616959, 18.533971, 31.387286], [23.349344, 32.866434, 33.441299]]
### 4
fourier: [[32.277993, 43.338569, 65.166369], [40.980683, 41.496012, 74.040337], [24.028753, 27.246114, 33.260433], [31.042273, 39.898651, 57.505062], [20.739154, 24.576188, 126.027040], [37.997293, 49.706558, 70.644036], [35.758706, 46.685139, 113.851151]]
### 6
fourier: [[46.273226, 61.099833, 183.318768], [23.483334, 30.151609, 136.353579], [34.150832, 44.486746, 117.451873], [37.476141, 42.268090, 46.059204], [26.609094, 29.750320, 30.191855], [20.845857, 28.564563, 52.636113], [20.191776, 20.830337, 22.243049]]
### 8
fourier: [[37.515660, 46.601467, 75.290477], [33.536217, 35.615254, 63.193894], [34.118611, 36.690326, 38.597787], [46.528396, 47.606213, 47.987271], [49.620405, 54.326130, 56.744421], [33.836421, 37.882276, 40.509087], [51.299962, 64.589195, 228.381461]]
### 10
fourier: [[54.571436, 68.195831, 236.254688]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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[
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],
[
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[
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]
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"network.4.weight": [
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],
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[
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[
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[
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[
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[
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[
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],
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],
[
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],
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0.089482,
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-0.309681,
0.457685,
-0.204707,
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0.165061,
-0.677321
]
],
"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[25.498399, 28.010241, 83.788923], [25.586316, 28.592422, 87.132695], [35.580069, 40.771416, 219.865125], [27.435832, 30.247990, 37.327176], [21.879774, 22.965042, 42.310499], [25.864087, 26.853515, 126.918515], [12.955239, 15.482719, 72.150297]]
### 2
fourier: [[37.259762, 37.288170, 209.279569], [19.475747, 23.292406, 49.162166], [39.753946, 40.473639, 47.612079], [24.531095, 30.279521, 39.870306], [19.731421, 20.687978, 51.115194], [17.616959, 18.533971, 31.387286], [23.349344, 32.866434, 33.441299]]
### 4
fourier: [[32.277993, 43.338569, 65.166369], [40.980683, 41.496012, 74.040337], [24.028753, 27.246114, 33.260433], [31.042273, 39.898651, 57.505062], [20.739154, 24.576188, 126.027040], [37.997293, 49.706558, 70.644036], [35.758706, 46.685139, 113.851151]]
### 6
fourier: [[46.273226, 61.099833, 183.318768], [23.483334, 30.151609, 136.353579], [34.150832, 44.486746, 117.451873], [37.476141, 42.268090, 46.059204], [26.609094, 29.750320, 30.191855], [20.845857, 28.564563, 52.636113], [20.191776, 20.830337, 22.243049]]
### 8
fourier: [[37.515660, 46.601467, 75.290477], [33.536217, 35.615254, 63.193894], [34.118611, 36.690326, 38.597787], [46.528396, 47.606213, 47.987271], [49.620405, 54.326130, 56.744421], [33.836421, 37.882276, 40.509087], [51.299962, 64.589195, 228.381461]]
### 10
fourier: [[54.571436, 68.195831, 236.254688]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.498398601736643, 28.010240918002182, 83.78892327845097]}, "1": {"fourier": [25.586316224163824, 28.59242223479202, 87.13269548118114]}, "2": {"fourier": [35.58006866308635, 40.771415814264586, 219.86512454599142]}, "3": {"fourier": [27.435831544430503, 30.247990142553626, 37.32717576622963]}, "4": {"fourier": [21.879774457522583, 22.96504198090615, 42.31049878895283]}, "5": {"fourier": [25.864087284829758, 26.853515091317135, 126.91851478815079]}, "6": {"fourier": [12.955238747310073, 15.482719384769823, 72.1502970457077]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [37.259762379269276, 37.288169843114694, 209.27956880629063]}, "1": {"fourier": [19.475747207750683, 23.292406471603776, 49.16216581314802]}, "2": {"fourier": [39.753946476199076, 40.47363901883364, 47.61207906746405]}, "3": {"fourier": [24.531095346793112, 30.279521018496567, 39.87030631676316]}, "4": {"fourier": [19.73142131916246, 20.687977747878264, 51.11519365012646]}, "5": {"fourier": [17.616959376031627, 18.533971195953942, 31.387286461889744]}, "6": {"fourier": [23.349344138639957, 32.86643423007871, 33.44129879694006]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [32.27799317328976, 43.33856852433439, 65.16636872291565]}, "1": {"fourier": [40.98068316123964, 41.49601209768642, 74.04033681750298]}, "2": {"fourier": [24.02875307142289, 27.246113756258342, 33.26043272763491]}, "3": {"fourier": [31.042273138568923, 39.89865074008162, 57.505061596632004]}, "4": {"fourier": [20.739154289017677, 24.576188357605506, 126.02704017609358]}, "5": {"fourier": [37.99729313622667, 49.706558483432424, 70.64403636008501]}, "6": {"fourier": [35.75870563020214, 46.685138840056524, 113.85115145146847]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [46.27322597571468, 61.09983323305314, 183.318767786026]}, "1": {"fourier": [23.483334097154742, 30.15160934012149, 136.35357880592346]}, "2": {"fourier": [34.15083172702482, 44.48674572012731, 117.45187292993069]}, "3": {"fourier": [37.476140816507886, 42.26809007040374, 46.05920397475818]}, "4": {"fourier": [26.609093945901414, 29.75031989145851, 30.191854693161236]}, "5": {"fourier": [20.84585746270556, 28.56456273634126, 52.63611260801554]}, "6": {"fourier": [20.191775586942278, 20.830337045008818, 22.24304901649973]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [37.51566033190405, 46.60146700750141, 75.29047691822052]}, "1": {"fourier": [33.53621712331786, 35.615253623015754, 63.193894028663635]}, "2": {"fourier": [34.11861107834202, 36.69032629155482, 38.59778656773229]}, "3": {"fourier": [46.52839568257332, 47.60621344293359, 47.987270942433355]}, "4": {"fourier": [49.62040474098576, 54.32613048948716, 56.74442102477172]}, "5": {"fourier": [33.83642096436215, 37.88227628696274, 40.50908744179531]}, "6": {"fourier": [51.29996159395864, 64.58919540714693, 228.3814606666565]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [54.57143576355418, 68.19583130957103, 236.2546877861023]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.263043, -0.252535, 0.58979, 0.411832, -0.382545], [-0.229046, 0.188793, -0.259359, 0.590375, 0.326531], [0.664935, 0.501404, 0.088594, 0.141486, 0.188755], [-0.100618, 0.282746, -0.273179, 0.419921, -0.396595], [-0.326006, 0.068995, -0.205958, 0.164953, 0.546891], [-0.115613, -0.158034, -0.236057, 0.512445, 0.474891], [-0.273598, 0.084977, 0.038521, 0.219521, 0.195432]], "network.0.bias": [0.075154, -0.217822, -0.019468, 0.184011, 0.152082, 0.650541, 0.195053], "network.2.weight": [[0.159108, 0.462722, 0.076261, 0.525373, 0.254136, 0.596278, 0.196859], [-0.492596, 0.018554, 0.234312, -0.315662, -0.527324, -0.103983, -0.07033], [-0.628497, -0.516153, 0.606803, -0.261297, -0.629694, 0.075688, -0.483395], [-0.393642, -0.566444, 0.341796, 0.118577, -0.169144, -0.00068, -0.402509], [-0.444073, -0.117656, 0.184351, -0.328288, -0.278916, -0.067826, -0.24865], [-0.389119, -0.245642, 0.178175, -0.177069, -0.546351, 0.320664, -0.211304], 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0.416813, -0.270529, -0.38704, 0.425355, -0.539231], [-0.223332, -0.101506, 0.409077, 0.308621, -0.417526, 0.635634, -0.284393], [0.079781, -0.117578, 0.497098, 0.211467, -0.216643, 0.296369, -0.242913], [-0.548617, -0.130474, 0.280523, 0.012201, -0.103699, 0.071813, -0.078278], [-0.059228, -0.145756, -0.126167, 0.446445, -0.050704, 0.344773, -0.004031]], "network.6.bias": [0.722522, 0.557415, 0.110127, -0.178741, -0.073947, 0.123642, -0.088231], "network.8.weight": [[-0.533898, -0.163156, 0.443903, 0.049601, 0.375407, -0.339346, 0.466318], [0.287757, 0.157215, -0.096149, -0.373514, 0.097698, -0.392666, -0.454105], [-0.413024, 0.250546, 0.160786, 0.587679, 0.224873, -0.238926, 0.36955], [0.263533, 0.323106, -0.173698, -0.621631, -0.234923, 0.370959, -0.514912], [0.394013, 0.08821, -0.405678, -0.684038, -0.503975, 0.202235, -0.30971], [-0.498453, 0.184756, -0.085588, 0.33783, 0.309579, -0.164178, 0.634617], [0.656309, 0.513338, -0.243038, -0.401168, -0.205773, -0.393871, -0.064574]], "network.8.bias": [0.281091, 0.209792, -0.145842, 0.089482, 0.24065, 0.273282, 0.675662], "network.10.weight": [[0.188444, -0.309681, 0.457685, -0.204707, -0.292818, 0.165061, -0.677321]], "network.10.bias": [-0.076749]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6906745433807373, "train_acc": 0.5, "val_loss": 0.6828798055648804, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6782574653625488, "train_acc": 0.56, "val_loss": 0.6593039035797119, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6486417055130005, "train_acc": 0.56, "val_loss": 0.5440099239349365, "val_acc": 0.7}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5045328885316849, "train_acc": 0.75, "val_loss": 0.2884593904018402, "val_acc": 0.92}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.3236505091190338, "train_acc": 0.915, "val_loss": 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0.2884593904018402, "final_val_loss": 0.24020835757255554, "initial_val_acc": 0.92, "final_val_acc": 0.92, "best_val_acc": 0.96, "best_epoch": 5}, "improvement": 0.26, "first_improvement_epoch": 2}} |
32 | {"target_pattern": "ends_with", "degraded_accuracy": 0.52, "improved_accuracy": 0.9, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1496, "learning_rate": 0.08248469519525602, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
fourier: [[19.841668, 22.298418, 171.916391], [57.472573, 58.171939, 313.210737], [59.863268, 60.379711, 231.940189], [34.750288, 38.543338, 41.479535], [41.263911, 45.763107, 323.040169], [39.878177, 43.175290, 55.339905]]
### 2
fourier: [[56.809637, 58.609542, 243.950331], [43.405637, 44.754371, 241.159019], [13.968267, 17.905128, 17.915333], [62.457597, 63.112291, 225.032957], [75.095010, 77.980031, 247.052742], [8.915001, 9.148851, 38.140171]]
### 4
fourier: [[21.868617, 23.981527, 156.631991], [67.095400, 68.702876, 168.148676], [61.993768, 62.822719, 199.078100], [64.502881, 67.058463, 159.599227], [55.627047, 56.891558, 141.730549], [54.310970, 54.437488, 113.777021]]
### 6
fourier: [[269.939949, 294.376638, 800.428550], [125.855183, 136.504205, 367.377069], [58.305712, 61.945256, 247.653405], [112.220982, 120.339968, 402.230764], [128.390578, 140.517068, 334.941832], [85.643343, 91.957823, 248.475893]]
### 8
fourier: [[56.285895, 57.541806, 84.021995], [20.114460, 21.440708, 26.470340], [10.569524, 13.452436, 78.101454], [181.367248, 202.319289, 611.945464], [263.135746, 288.566349, 823.805237], [71.356755, 78.488591, 186.671866]]
### 10
fourier: [[209.207327, 217.704971, 575.456205]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
"network.2.bias": [
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"network.4.weight": [
[
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[
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"network.4.bias": [
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"network.6.weight": [
[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[19.841668, 22.298418, 171.916391], [57.472573, 58.171939, 313.210737], [59.863268, 60.379711, 231.940189], [34.750288, 38.543338, 41.479535], [41.263911, 45.763107, 323.040169], [39.878177, 43.175290, 55.339905]]
### 2
fourier: [[56.809637, 58.609542, 243.950331], [43.405637, 44.754371, 241.159019], [13.968267, 17.905128, 17.915333], [62.457597, 63.112291, 225.032957], [75.095010, 77.980031, 247.052742], [8.915001, 9.148851, 38.140171]]
### 4
fourier: [[21.868617, 23.981527, 156.631991], [67.095400, 68.702876, 168.148676], [61.993768, 62.822719, 199.078100], [64.502881, 67.058463, 159.599227], [55.627047, 56.891558, 141.730549], [54.310970, 54.437488, 113.777021]]
### 6
fourier: [[269.939949, 294.376638, 800.428550], [125.855183, 136.504205, 367.377069], [58.305712, 61.945256, 247.653405], [112.220982, 120.339968, 402.230764], [128.390578, 140.517068, 334.941832], [85.643343, 91.957823, 248.475893]]
### 8
fourier: [[56.285895, 57.541806, 84.021995], [20.114460, 21.440708, 26.470340], [10.569524, 13.452436, 78.101454], [181.367248, 202.319289, 611.945464], [263.135746, 288.566349, 823.805237], [71.356755, 78.488591, 186.671866]]
### 10
fourier: [[209.207327, 217.704971, 575.456205]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.841667900998818, 22.29841821285995, 171.91639149188995]}, "1": {"fourier": [57.47257285815574, 58.17193899518456, 313.21073677763343]}, "2": {"fourier": [59.86326754452808, 60.379711360849235, 231.94018895179033]}, "3": {"fourier": [34.75028767435958, 38.54333810508251, 41.479534890304244]}, "4": {"fourier": [41.263911075560266, 45.76310718564796, 323.04016852378845]}, "5": {"fourier": [39.87817658136022, 43.17529034614563, 55.33990536720042]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [56.8096370136291, 58.60954157430785, 243.95033060014248]}, "1": {"fourier": [43.40563725845593, 44.754371093813646, 241.15901863574982]}, "2": {"fourier": [13.968267129536496, 17.90512771178851, 17.91533342209743]}, "3": {"fourier": [62.457597231069514, 63.11229139531288, 225.03295697271824]}, "4": {"fourier": [75.09500967199924, 77.98003080408168, 247.05274227261543]}, "5": {"fourier": [8.915000611394738, 9.148851282976821, 38.140170745551586]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [21.868617281491627, 23.981527462956738, 156.63199084997177]}, "1": {"fourier": [67.09540026855716, 68.70287605898369, 168.14867636561394]}, "2": {"fourier": [61.99376846931147, 62.82271871625369, 199.07810029387474]}, "3": {"fourier": [64.50288143006775, 67.05846324306007, 159.59922698140144]}, "4": {"fourier": [55.62704727591631, 56.891557756018436, 141.7305490076542]}, "5": {"fourier": [54.310969980947455, 54.437487742004144, 113.77702078223228]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [269.9399494069327, 294.3766378963874, 800.4285498410463]}, "1": {"fourier": [125.85518297953124, 136.50420462428806, 367.37706926465034]}, "2": {"fourier": [58.30571164128731, 61.945255766408145, 247.65340465307236]}, "3": {"fourier": [112.22098227125603, 120.33996798648326, 402.2307642996311]}, "4": {"fourier": [128.39057772886167, 140.51706774327445, 334.94183230400085]}, "5": {"fourier": [85.64334348815696, 91.95782296515492, 248.47589303553104]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [56.2858950484105, 57.54180598810821, 84.02199548482895]}, "1": {"fourier": [20.11446013994159, 21.440707720544633, 26.470340262015924]}, "2": {"fourier": [10.569524099986337, 13.452435894710597, 78.10145407915115]}, "3": {"fourier": [181.3672480125904, 202.31928903052565, 611.9454644918442]}, "4": {"fourier": [263.1357461228532, 288.5663494091505, 823.8052371889353]}, "5": {"fourier": [71.35675454837761, 78.48859056764591, 186.67186550796032]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [209.20732726908975, 217.70497066191092, 575.4562048465014]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.309009, -0.283975, -0.136471, -0.430511, -0.039721], [-0.584341, -0.331104, 0.089777, -0.471939, -1.058366], [0.551575, -0.046392, 0.132418, -0.017223, 1.217791], [-0.25305, 0.020193, 0.335634, 0.216176, -0.965678], [-0.734544, -0.308346, -0.486921, -0.244231, -0.009683], [-0.901515, -0.308319, 0.328172, -0.092376, 1.113598]], "network.0.bias": [-0.519993, -0.019762, 0.233631, -0.123826, -0.560554, 0.302581], "network.2.weight": [[-0.362537, -0.010783, -0.594173, 0.131792, -0.128265, -0.699625], [-0.184599, -0.432388, -0.402374, 0.302134, 0.43644, -0.590429], [0.358789, 0.062123, -0.073261, 0.474951, 0.035028, -0.325729], [-0.04747, 0.336312, -0.704576, 0.487602, -0.129626, -0.539294], [-0.756344, 0.337599, 0.803779, -0.449101, -1.3728, 0.867712], [-0.74703, -0.861276, 0.024972, 0.276985, -0.715705, 0.285486]], "network.2.bias": [-0.472241, -1.100278, 0.266152, -0.294945, -0.194466, -0.169786], "network.4.weight": [[0.277986, 0.585822, 0.018764, -0.273718, -0.319972, 0.140888], [0.886076, 0.76139, -0.269588, 0.343728, 0.830551, 0.154903], [0.574589, -0.097723, -0.926141, 0.585954, 0.699022, 0.599637], [0.317539, -0.251863, -0.187101, -0.135408, 0.866833, -0.236714], [0.778525, 0.754948, -0.193354, 0.26839, 0.687529, 0.129786], [0.71421, -0.261736, -0.545413, 0.393155, 0.70479, -0.502301]], "network.4.bias": [-0.841562, -0.333343, 0.251449, -0.534999, -0.241184, -0.398186], "network.6.weight": [[0.802963, 1.134436, 0.864939, 0.88434, 0.952069, 0.938009], [-0.087581, -1.031425, -0.399254, 0.116632, -0.583937, -0.303299], [1.113849, -0.222345, -0.60352, 0.057788, -0.349727, 0.108668], [0.030181, -0.713278, -0.7688, 0.082725, -0.202251, -0.334897], [-0.434089, -0.305653, -0.424923, -0.536611, -0.240492, -0.821931], [-0.630598, -0.280533, -0.382485, 0.355124, -0.93601, -0.354688]], "network.6.bias": [-0.070287, 0.156429, -0.507147, -0.584257, 0.514068, 0.048919], "network.8.weight": [[-0.184965, 0.313747, 0.088283, -0.82784, 0.820625, 0.09531], [-0.065413, 0.63146, -0.774398, -0.383254, 0.476519, 0.516613], [0.047424, 0.026871, -0.127532, -0.201942, 0.070335, 0.39901], [-0.694792, 0.131472, 0.199096, 0.303571, -0.306597, 0.371701], [0.9857, -0.131396, -0.34902, 0.216818, -0.21644, -0.601758], [-0.266892, -0.078693, -0.280584, -0.661631, -0.045826, -0.021983]], "network.8.bias": [0.423308, 0.21687, 0.35389, -0.340904, 0.222683, 0.333378], "network.10.weight": [[0.435547, 0.760236, -0.180556, -0.087339, -0.733347, 0.343988]], "network.10.bias": [-0.018841]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6892788410186768, "train_acc": 0.57, "val_loss": 0.6962285041809082, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6826817393302917, "train_acc": 0.57, "val_loss": 0.6959906220436096, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6803167462348938, "train_acc": 0.57, "val_loss": 0.6941179037094116, "val_acc": 0.52}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6717790365219116, "train_acc": 0.57, "val_loss": 0.6573123335838318, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6170878410339355, "train_acc": 0.635, "val_loss": 0.5390244126319885, "val_acc": 0.6}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5184135735034943, "train_acc": 0.685, "val_loss": 0.44664788246154785, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.39087097346782684, "train_acc": 0.835, "val_loss": 0.3438127934932709, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.3246060311794281, "train_acc": 0.865, "val_loss": 0.27138760685920715, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.31516675651073456, "train_acc": 0.885, "val_loss": 0.27010971307754517, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.27868956327438354, "train_acc": 0.895, "val_loss": 0.27568358182907104, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.28685157001018524, "train_acc": 0.895, "val_loss": 0.27479052543640137, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.2760649472475052, "train_acc": 0.895, "val_loss": 0.2739795446395874, "val_acc": 0.9}], "summary": {"total_epochs": 12, "degraded_epochs": 4, "improved_epochs": 8, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6962285041809082, "final_val_loss": 0.6573123335838318, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5390244126319885, "final_val_loss": 0.2739795446395874, "initial_val_acc": 0.6, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 7}, "improvement": 0.38, "first_improvement_epoch": 3}} |
33 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.46, "improved_accuracy": 0.98, "improvement": 0.52, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2876, "learning_rate": 0.052811634834035476, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.136327,
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0.252366,
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[
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[
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0.030847,
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0.081394,
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0.253416
],
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"network.10.weight": [
[
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],
"network.10.bias": [
0.24021
]
}
## Activation Signature
### 0
fourier: [[37.290953, 41.142055, 196.040576], [24.918384, 26.428156, 171.671304], [33.907243, 35.904818, 104.831958], [38.930658, 39.987522, 200.367319], [41.684922, 43.115090, 192.860888], [40.279623, 43.730790, 152.423582], [36.698097, 42.059955, 201.370472]]
### 2
fourier: [[23.678523, 24.471808, 115.314804], [21.690827, 23.036923, 84.382286], [20.564141, 21.259371, 69.577321], [89.737371, 90.360662, 523.997525], [57.351552, 58.732358, 323.128716], [12.358919, 12.847025, 107.989566], [51.967945, 52.015280, 285.326832]]
### 4
fourier: [[9.210780, 9.443921, 75.603449], [135.485938, 140.281312, 800.509340], [19.767344, 20.318199, 117.683267], [43.985895, 45.121316, 192.329760], [13.209349, 13.910419, 100.101587], [124.162260, 125.706828, 705.636253], [61.340484, 63.374395, 330.503570]]
### 6
fourier: [[60.582462, 62.610278, 382.356643], [142.673752, 147.021116, 818.116331], [70.233542, 73.394442, 432.717831], [6.035227, 6.048782, 37.626334], [142.592018, 147.433229, 804.834145], [65.570522, 66.726620, 386.932192], [10.517353, 10.715465, 29.378438]]
### 8
fourier: [[47.399930, 48.589254, 277.966632], [96.814697, 99.818037, 550.540139], [88.903297, 91.545119, 494.147267], [11.479746, 11.713555, 99.047721], [161.830645, 166.755759, 904.981947], [63.169170, 64.735517, 335.161327], [78.925002, 81.188472, 389.396052]]
### 10
fourier: [[152.169142, 156.587882, 817.312858]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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"network.4.weight": [
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[37.290953, 41.142055, 196.040576], [24.918384, 26.428156, 171.671304], [33.907243, 35.904818, 104.831958], [38.930658, 39.987522, 200.367319], [41.684922, 43.115090, 192.860888], [40.279623, 43.730790, 152.423582], [36.698097, 42.059955, 201.370472]]
### 2
fourier: [[23.678523, 24.471808, 115.314804], [21.690827, 23.036923, 84.382286], [20.564141, 21.259371, 69.577321], [89.737371, 90.360662, 523.997525], [57.351552, 58.732358, 323.128716], [12.358919, 12.847025, 107.989566], [51.967945, 52.015280, 285.326832]]
### 4
fourier: [[9.210780, 9.443921, 75.603449], [135.485938, 140.281312, 800.509340], [19.767344, 20.318199, 117.683267], [43.985895, 45.121316, 192.329760], [13.209349, 13.910419, 100.101587], [124.162260, 125.706828, 705.636253], [61.340484, 63.374395, 330.503570]]
### 6
fourier: [[60.582462, 62.610278, 382.356643], [142.673752, 147.021116, 818.116331], [70.233542, 73.394442, 432.717831], [6.035227, 6.048782, 37.626334], [142.592018, 147.433229, 804.834145], [65.570522, 66.726620, 386.932192], [10.517353, 10.715465, 29.378438]]
### 8
fourier: [[47.399930, 48.589254, 277.966632], [96.814697, 99.818037, 550.540139], [88.903297, 91.545119, 494.147267], [11.479746, 11.713555, 99.047721], [161.830645, 166.755759, 904.981947], [63.169170, 64.735517, 335.161327], [78.925002, 81.188472, 389.396052]]
### 10
fourier: [[152.169142, 156.587882, 817.312858]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [37.29095266568393, 41.1420550053662, 196.0405756831169]}, "1": {"fourier": [24.918383567855347, 26.428156192216708, 171.67130394279957]}, "2": {"fourier": [33.907242777065434, 35.90481842863705, 104.83195842802525]}, "3": {"fourier": [38.930657997947236, 39.98752151455268, 200.3673186302185]}, "4": {"fourier": [41.684922095994935, 43.115090182921456, 192.86088806390762]}, "5": {"fourier": [40.27962343741221, 43.73079000666185, 152.42358204722404]}, "6": {"fourier": [36.69809686556186, 42.059955201089124, 201.3704723417759]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [23.67852307891201, 24.471807819279825, 115.31480377539992]}, "1": {"fourier": [21.690827491169998, 23.03692298475674, 84.38228614628315]}, "2": {"fourier": [20.564140988238936, 21.259370944986845, 69.57732054591179]}, "3": {"fourier": [89.73737075709191, 90.36066180262159, 523.9975247383118]}, "4": {"fourier": [57.35155185873691, 58.73235810472437, 323.1287159845233]}, "5": {"fourier": [12.358918756208181, 12.84702513292886, 107.98956552147865]}, "6": {"fourier": [51.967944757644275, 52.01528030627817, 285.32683204859495]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [9.210779780177722, 9.443921333723168, 75.60344889760017]}, "1": {"fourier": [135.48593794096317, 140.2813115560682, 800.5093397647142]}, "2": {"fourier": [19.767343668463795, 20.318198824528633, 117.68326705694199]}, "3": {"fourier": [43.98589486099705, 45.12131646937305, 192.32976040244102]}, "4": {"fourier": [13.209349206100345, 13.910418834710033, 100.10158661007881]}, "5": {"fourier": [124.16225950457485, 125.70682837601262, 705.6362532898784]}, "6": {"fourier": [61.340483629571196, 63.37439544145331, 330.50357000529766]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [60.582461814625006, 62.61027775339251, 382.3566434979439]}, "1": {"fourier": [142.67375197426117, 147.02111558702293, 818.1163306683302]}, "2": {"fourier": [70.23354155080159, 73.3944419089397, 432.71783113479614]}, "3": {"fourier": [6.035227415283179, 6.048782074878856, 37.626334331929684]}, "4": {"fourier": [142.59201847785462, 147.43322933686332, 804.8341453187168]}, "5": {"fourier": [65.57052162668501, 66.7266197329433, 386.93219158798456]}, "6": {"fourier": [10.51735337808003, 10.715465267409531, 29.378437772393227]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [47.39992964487389, 48.58925438704252, 277.9666320979595]}, "1": {"fourier": [96.81469728209727, 99.81803691005373, 550.5401390716434]}, "2": {"fourier": [88.90329674871508, 91.54511907420898, 494.14726738631725]}, "3": {"fourier": 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"network.8.bias": [-0.056123, 0.097927, -0.064449, -0.337924, -0.033542, -0.350494, 0.65703], "network.10.weight": [[0.084112, -0.286515, -0.031187, 0.119223, -0.532798, -0.551058, 0.422404]], "network.10.bias": [0.24021]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6684485077857971, "train_acc": 0.585, "val_loss": 0.6705371141433716, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.5897465944290161, "train_acc": 0.585, "val_loss": 0.5361432433128357, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5152618885040283, "train_acc": 0.51, "val_loss": 0.41524460911750793, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4125421941280365, "train_acc": 0.91, "val_loss": 0.360160231590271, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.3678777366876602, "train_acc": 0.9, "val_loss": 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"improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.22284600138664246, "train_acc": 0.91, "val_loss": 0.15390925109386444, "val_acc": 0.96}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.6705371141433716, "final_val_loss": 0.5361432433128357, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.41524460911750793, "final_val_loss": 0.15390925109386444, "initial_val_acc": 0.94, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 4}, "improvement": 0.52, "first_improvement_epoch": 1}} |
34 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.52, "improved_accuracy": 0.8, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2412, "learning_rate": 0.09693395560140622, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[12.884272, 14.812381, 21.201909], [32.084171, 33.579083, 111.435975], [28.906568, 30.183888, 144.172147], [22.189444, 23.698207, 38.141402], [34.296244, 36.229565, 113.323294], [30.636038, 31.865588, 58.004553], [31.653834, 45.026466, 74.101360], [13.051008, 13.188688, 35.274311]]
### 2
fourier: [[25.929495, 27.233148, 102.429215], [62.795796, 66.524014, 198.867750], [13.436103, 13.663401, 14.252765], [7.657712, 7.875896, 9.477611], [12.685518, 13.984248, 26.661425], [25.009974, 25.825883, 42.833124], [32.190088, 33.310556, 135.983951], [47.865388, 47.883719, 187.929695]]
### 4
fourier: [[20.482711, 20.796890, 103.477839], [7.093327, 7.288239, 7.803463], [83.814346, 85.481698, 267.783077], [29.527493, 30.442458, 96.633069], [10.571324, 11.578613, 64.313024], [71.441010, 74.429629, 254.234383], [2.587592, 2.852884, 22.777849], [19.789763, 19.922074, 21.509414]]
### 6
fourier: [[7.885942, 8.126458, 71.555327], [74.302602, 77.596954, 231.548578], [77.801996, 80.768055, 235.302005], [41.388180, 43.434390, 146.287159], [34.652889, 36.144022, 122.715033], [84.025491, 87.448581, 282.030008], [68.025859, 70.174609, 201.384407], [1.138120, 1.495694, 38.139375]]
### 8
fourier: [[136.100711, 142.688364, 394.118636]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[12.884272, 14.812381, 21.201909], [32.084171, 33.579083, 111.435975], [28.906568, 30.183888, 144.172147], [22.189444, 23.698207, 38.141402], [34.296244, 36.229565, 113.323294], [30.636038, 31.865588, 58.004553], [31.653834, 45.026466, 74.101360], [13.051008, 13.188688, 35.274311]]
### 2
fourier: [[25.929495, 27.233148, 102.429215], [62.795796, 66.524014, 198.867750], [13.436103, 13.663401, 14.252765], [7.657712, 7.875896, 9.477611], [12.685518, 13.984248, 26.661425], [25.009974, 25.825883, 42.833124], [32.190088, 33.310556, 135.983951], [47.865388, 47.883719, 187.929695]]
### 4
fourier: [[20.482711, 20.796890, 103.477839], [7.093327, 7.288239, 7.803463], [83.814346, 85.481698, 267.783077], [29.527493, 30.442458, 96.633069], [10.571324, 11.578613, 64.313024], [71.441010, 74.429629, 254.234383], [2.587592, 2.852884, 22.777849], [19.789763, 19.922074, 21.509414]]
### 6
fourier: [[7.885942, 8.126458, 71.555327], [74.302602, 77.596954, 231.548578], [77.801996, 80.768055, 235.302005], [41.388180, 43.434390, 146.287159], [34.652889, 36.144022, 122.715033], [84.025491, 87.448581, 282.030008], [68.025859, 70.174609, 201.384407], [1.138120, 1.495694, 38.139375]]
### 8
fourier: [[136.100711, 142.688364, 394.118636]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [12.884271934175512, 14.812381449080702, 21.201909233594467]}, "1": {"fourier": [32.08417103944767, 33.57908318458845, 111.43597492575645]}, "2": {"fourier": [28.906567903237438, 30.18388838242437, 144.17214700579643]}, "3": {"fourier": [22.189444300086723, 23.698207072684557, 38.14140233397484]}, "4": {"fourier": [34.29624389155682, 36.229565421625246, 113.32329359650612]}, "5": {"fourier": [30.63603766494937, 31.86558841521623, 58.00455266237259]}, "6": {"fourier": [31.65383379448556, 45.02646613276904, 74.10136017203331]}, "7": {"fourier": [13.051007687706981, 13.188687719442775, 35.27431058883667]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [25.929495043266243, 27.233148107457158, 102.42921547591686]}, "1": {"fourier": [62.79579573410929, 66.52401369429448, 198.8677503168583]}, "2": {"fourier": [13.436102898766176, 13.663401180493702, 14.252765010317734]}, "3": {"fourier": [7.657711546991639, 7.87589608966919, 9.47761079607399]}, "4": {"fourier": [12.685517674150823, 13.984247584516318, 26.66142527759075]}, "5": {"fourier": [25.009973679968077, 25.825882778139203, 42.83312425017357]}, "6": {"fourier": [32.19008836065114, 33.310556304903784, 135.98395125567913]}, "7": {"fourier": [47.8653880224295, 47.883718958569304, 187.92969474196434]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [20.482711053490334, 20.796890102692903, 103.47783896327019]}, "1": {"fourier": [7.09332721336495, 7.288238521022243, 7.803463410157178]}, "2": {"fourier": [83.81434623738396, 85.48169783915174, 267.783077146858]}, "3": {"fourier": [29.527492926531295, 30.442458128602528, 96.6330689676106]}, "4": {"fourier": [10.571323740760814, 11.578612872900676, 64.31302398443222]}, "5": {"fourier": [71.44101008298205, 74.42962909502845, 254.23438329994678]}, "6": {"fourier": [2.5875919361352713, 2.8528842286552694, 22.77784888446331]}, "7": {"fourier": [19.78976280505591, 19.922073501469253, 21.50941400637222]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [7.885942043766196, 8.126457782403078, 71.5553271472454]}, "1": {"fourier": [74.30260193489204, 77.59695407790987, 231.54857790097594]}, "2": {"fourier": [77.80199632552107, 80.76805494263147, 235.30200492218137]}, "3": {"fourier": [41.388179820829436, 43.4343900670754, 146.28715878352523]}, "4": {"fourier": [34.65288927473833, 36.144021521620466, 122.71503286063671]}, "5": {"fourier": [84.02549144160146, 87.44858137085649, 282.0300075337291]}, "6": {"fourier": [68.02585940517892, 70.17460907849346, 201.38440744765103]}, "7": {"fourier": [1.1381199080329614, 1.4956943167050398, 38.1393748819828]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [136.1007112756403, 142.68836370435255, 394.118635751307]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.263616, 0.126548, -0.117192, 0.19037, -0.353659], [0.737701, -0.102384, 0.238266, -0.020417, -0.250497], [-0.132322, -0.124331, -0.201279, -0.244911, -0.551254], [-0.569201, 0.42561, 0.175756, -0.314125, 0.316814], [0.734839, 0.605622, -0.038559, -0.095061, -0.230708], [0.715973, 0.288847, -0.379853, -0.478218, 0.065294], [0.888709, -0.403053, -0.038536, -0.015653, 0.215266], [0.22659, 0.237139, -0.131115, 0.050494, 0.056837]], "network.0.bias": [-0.312321, 0.361736, 0.414842, 0.272329, -0.189957, -0.323373, 0.300423, -0.226656], "network.2.weight": [[-0.314089, 0.223042, 0.028438, -0.091202, 0.546878, -0.013618, 0.151002, -0.012129], [-0.719026, 0.581889, -0.657942, -0.321639, 0.636755, 0.484981, 0.60939, 0.176679], [0.325109, -0.002532, 0.144747, 0.338311, -0.41463, -0.265762, 0.037456, 0.494147], [0.274898, -0.146108, 0.139931, 0.151133, -0.015131, -0.027291, -0.144338, 0.325164], [0.71679, 0.106818, 0.148768, 0.255893, -0.176154, -0.428983, -0.215463, 0.268175], [-0.06583, 0.240867, -0.271755, -0.250154, 0.347243, 0.332076, 0.016458, -0.044706], [0.58533, -0.582765, 0.237952, -0.026102, -0.427523, 0.649855, -0.451848, -0.105912], [-0.14512, 0.44216, -0.201957, -0.227701, 0.68523, -0.005917, 0.401769, 0.093847]], "network.2.bias": [0.122162, 0.107173, 0.066103, 0.150761, -0.233552, 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0.60826, 0.704275, 0.19895, 0.31599], [0.448615, 0.834058, 0.592068, 0.123957, 0.1171, 0.330384, 0.051854, 0.04902], [-0.143945, -0.238736, -0.236794, -0.111228, -0.236315, -0.355748, -0.132872, 0.361381], [0.075379, 0.195015, 0.21951, 0.421372, 0.276496, 0.205759, 0.282752, 0.043197], [0.2737, 0.415137, 0.538285, 0.05538, 0.084652, 0.487489, -0.336433, 0.161505], [0.493196, 0.611657, 0.649313, 0.154137, 0.37272, 0.083658, -0.402281, 0.332455], [0.017846, 0.175128, 0.227287, -0.333768, 0.043711, -0.343091, 0.042115, 0.381215]], "network.6.bias": [0.391563, 0.053486, -0.026294, -0.085229, 0.223095, 0.157206, 0.048835, -0.259236], "network.8.weight": [[0.256525, -0.471665, -0.466111, 0.01799, -0.236338, -0.571092, -0.163899, -0.263063]], "network.8.bias": [0.239559]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7066080868244171, "train_acc": 0.44, "val_loss": 0.6552404761314392, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, 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"best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.45609694719314575, "final_val_loss": 0.5146835446357727, "initial_val_acc": 0.8, "final_val_acc": 0.72, "best_val_acc": 0.8, "best_epoch": 2}, "improvement": 0.28, "first_improvement_epoch": 1}} |
35 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.52, "improved_accuracy": 0.94, "improvement": 0.41999999999999993, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2079, "learning_rate": 0.05135048742655233, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[30.866608, 31.528688, 34.235567], [23.111173, 23.270897, 34.982013], [33.835790, 38.400645, 40.238189], [32.962071, 36.342821, 81.926394], [27.450835, 28.040884, 190.447866], [18.275835, 22.051819, 73.551874], [34.345050, 43.577194, 43.941620], [30.183531, 34.621117, 166.114588]]
### 2
fourier: [[42.451812, 48.171215, 254.200982], [7.947543, 8.063284, 9.667346], [11.062646, 12.250189, 75.992770], [15.156059, 17.138559, 55.731866], [17.287359, 17.496835, 20.520007], [34.332763, 36.273581, 170.722518], [11.656369, 11.748643, 59.631528], [11.946585, 15.018538, 75.155134]]
### 4
fourier: [[55.909604, 61.089505, 285.972570], [23.241975, 23.340063, 134.498239], [29.748438, 31.094330, 169.057655], [24.438861, 26.491075, 152.314045], [17.148368, 18.690772, 143.844644], [29.752733, 34.849916, 97.943129], [71.635152, 76.811009, 401.151848], [28.180368, 31.232096, 187.405680]]
### 6
fourier: [[2.231320, 2.542131, 49.824975], [102.607833, 104.849834, 556.717658], [13.621669, 16.379688, 121.275563], [26.504461, 27.804999, 149.833775], [43.172189, 44.594156, 146.817635], [12.834675, 13.992746, 73.891328], [46.862624, 46.973963, 277.186588], [38.616523, 39.874330, 162.752948]]
### 8
fourier: [[71.580159, 74.486941, 308.247325], [20.746989, 21.479098, 141.771885], [20.917876, 21.105790, 137.436165], [11.795848, 12.445271, 96.462754], [29.831119, 30.168404, 185.549981], [34.897432, 35.594120, 207.887911], [87.535061, 89.556362, 452.531885], [74.336669, 75.974249, 385.820872]]
### 10
fourier: [[158.268026, 160.986096, 816.480610], [181.498616, 184.708107, 945.245608], [82.879480, 84.336327, 340.543061], [28.437507, 29.003684, 160.028846], [32.673060, 33.146360, 174.626248], [23.927118, 24.419248, 148.541641], [143.808960, 146.200951, 739.851579], [119.549405, 121.586297, 635.898005]]
### 12
fourier: [[271.038586, 278.551385, 1302.417325]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[30.866608, 31.528688, 34.235567], [23.111173, 23.270897, 34.982013], [33.835790, 38.400645, 40.238189], [32.962071, 36.342821, 81.926394], [27.450835, 28.040884, 190.447866], [18.275835, 22.051819, 73.551874], [34.345050, 43.577194, 43.941620], [30.183531, 34.621117, 166.114588]]
### 2
fourier: [[42.451812, 48.171215, 254.200982], [7.947543, 8.063284, 9.667346], [11.062646, 12.250189, 75.992770], [15.156059, 17.138559, 55.731866], [17.287359, 17.496835, 20.520007], [34.332763, 36.273581, 170.722518], [11.656369, 11.748643, 59.631528], [11.946585, 15.018538, 75.155134]]
### 4
fourier: [[55.909604, 61.089505, 285.972570], [23.241975, 23.340063, 134.498239], [29.748438, 31.094330, 169.057655], [24.438861, 26.491075, 152.314045], [17.148368, 18.690772, 143.844644], [29.752733, 34.849916, 97.943129], [71.635152, 76.811009, 401.151848], [28.180368, 31.232096, 187.405680]]
### 6
fourier: [[2.231320, 2.542131, 49.824975], [102.607833, 104.849834, 556.717658], [13.621669, 16.379688, 121.275563], [26.504461, 27.804999, 149.833775], [43.172189, 44.594156, 146.817635], [12.834675, 13.992746, 73.891328], [46.862624, 46.973963, 277.186588], [38.616523, 39.874330, 162.752948]]
### 8
fourier: [[71.580159, 74.486941, 308.247325], [20.746989, 21.479098, 141.771885], [20.917876, 21.105790, 137.436165], [11.795848, 12.445271, 96.462754], [29.831119, 30.168404, 185.549981], [34.897432, 35.594120, 207.887911], [87.535061, 89.556362, 452.531885], [74.336669, 75.974249, 385.820872]]
### 10
fourier: [[158.268026, 160.986096, 816.480610], [181.498616, 184.708107, 945.245608], [82.879480, 84.336327, 340.543061], [28.437507, 29.003684, 160.028846], [32.673060, 33.146360, 174.626248], [23.927118, 24.419248, 148.541641], [143.808960, 146.200951, 739.851579], [119.549405, 121.586297, 635.898005]]
### 12
fourier: [[271.038586, 278.551385, 1302.417325]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [30.86660768687517, 31.528688283911702, 34.235567018220785]}, "1": {"fourier": [23.111173421144485, 23.27089704729665, 34.98201345978263]}, "2": {"fourier": [33.835790107947965, 38.40064516773958, 40.238189084290205]}, "3": {"fourier": [32.96207067649605, 36.342821311265894, 81.92639362812042]}, "4": {"fourier": [27.450835182826353, 28.040884308805268, 190.44786646962166]}, "5": {"fourier": [18.27583457969872, 22.05181895049643, 73.55187444388866]}, "6": {"fourier": [34.34505047242839, 43.57719409755511, 43.94161951470696]}, "7": {"fourier": [30.18353132013143, 34.621116747296206, 166.11458787322044]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [42.451812379176474, 48.17121497219856, 254.20098233222961]}, "1": {"fourier": [7.947542989944041, 8.063283660878456, 9.66734647093112]}, "2": {"fourier": [11.06264569368013, 12.25018947933162, 75.99277003109455]}, "3": {"fourier": [15.156058986412315, 17.138559039069424, 55.73186573199928]}, "4": {"fourier": [17.287358777358925, 17.49683542127392, 20.520007093986955]}, "5": {"fourier": [34.332763024011555, 36.27358054905938, 170.72251771390438]}, "6": {"fourier": [11.656368912607245, 11.748643229805552, 59.631528213620186]}, "7": {"fourier": [11.94658506294097, 15.018538358347183, 75.15513418614864]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [55.90960439651128, 61.08950466758936, 285.972570002079]}, "1": {"fourier": [23.24197509465294, 23.340062660141143, 134.4982388317585]}, "2": {"fourier": [29.74843833442094, 31.094330364228345, 169.05765494704247]}, "3": {"fourier": [24.43886118182882, 26.49107450613563, 152.31404542922974]}, "4": {"fourier": [17.14836791654438, 18.690772492640118, 143.844644010067]}, "5": {"fourier": [29.752732506415008, 34.84991602071849, 97.94312924146652]}, "6": {"fourier": [71.63515232221147, 76.81100869430448, 401.1518483310938]}, "7": {"fourier": [28.180368057638834, 31.23209636719256, 187.40568026900291]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [2.231319546204435, 2.5421309767201277, 49.824974566698074]}, "1": {"fourier": [102.60783295194669, 104.84983431902968, 556.7176581770182]}, "2": {"fourier": [13.621668619725135, 16.379688264781727, 121.27556324005127]}, "3": {"fourier": [26.50446080155507, 27.80499855766627, 149.83377538621426]}, "4": {"fourier": [43.17218871474974, 44.59415614241381, 146.81763473153114]}, "5": {"fourier": [12.834674511795162, 13.992746324254982, 73.8913283739239]}, "6": {"fourier": [46.862624131114174, 46.9739629940747, 277.18658795952797]}, "7": {"fourier": [38.616523330701796, 39.87432987484716, 162.75294825434685]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [71.58015885915775, 74.4869406381338, 308.2473250031471]}, "1": {"fourier": [20.74698930670763, 21.479097832371266, 141.77188509702682]}, "2": {"fourier": [20.917876023331186, 21.10579049895291, 137.4361652135849]}, "3": {"fourier": [11.795847742538344, 12.44527139608738, 96.46275380253792]}, "4": {"fourier": [29.831119331746553, 30.168403545663367, 185.54998144507408]}, "5": {"fourier": [34.89743244905294, 35.59412037053501, 207.8879110366106]}, "6": {"fourier": [87.53506149492972, 89.55636212878692, 452.5318850874901]}, "7": {"fourier": [74.33666945531849, 75.97424875424794, 385.8208721727133]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [158.2680260619606, 160.98609604818384, 816.480610370636]}, "1": {"fourier": [181.49861581929406, 184.70810724519032, 945.2456080317497]}, "2": {"fourier": [82.87948009612529, 84.33632682400052, 340.5430612564087]}, "3": {"fourier": [28.43750694676727, 29.003683924011657, 160.02884644269943]}, "4": {"fourier": [32.673059759017356, 33.146359550366334, 174.6262475270778]}, "5": {"fourier": [23.927117581810617, 24.419247922541, 148.54164123535156]}, "6": {"fourier": [143.8089597288542, 146.2009508468547, 739.851578772068]}, "7": {"fourier": [119.54940460407053, 121.58629674716425, 635.8980049937963]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [271.0385855189339, 278.55138531041706, 1302.4173245429993]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, 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[-0.10722, 0.60936, 0.157731, -0.586636, -0.785051, -0.442422, -0.159338, -0.113537], [0.812601, -0.241688, 0.023235, 0.737867, 1.060254, 0.765311, -0.286088, 0.211539], [-0.427094, 0.070633, -0.024134, -0.033463, 0.002282, -0.27249, -0.31324, -0.213376]], "network.4.bias": [-0.328865, 0.08793, 0.008729, -0.112378, -0.417703, 0.665801, -0.172125, -0.330214], "network.6.weight": [[0.039799, 0.182144, -0.155629, 0.110237, -0.028076, -0.004532, -0.061198, -0.236001], [0.807462, 0.039365, 0.211982, -0.000801, 0.036546, -0.499563, 0.756979, -0.116867], [0.105737, -0.089551, 0.220108, 0.276074, 0.045164, -0.234272, -0.292398, -0.047492], [0.076747, 0.025539, -0.464997, -0.463146, -0.278464, 0.120344, -0.413611, -0.028017], [-0.32418, -0.291787, -0.051211, -0.019659, -0.117227, 0.945274, -0.273502, -0.207246], [0.154201, -0.325872, -0.232224, -0.26002, 0.235042, 0.030877, -0.290097, -0.051083], [-0.353675, 0.142282, 0.065089, -0.049748, -0.03652, -0.038194, -0.361745, -0.000234], [-0.454597, 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"network.10.weight": [[0.260414, 0.042825, -0.135471, -0.132031, 0.087103, 0.195401, 0.922867, 0.841336], [0.601351, 0.076955, 0.065811, 0.408102, 0.540989, -0.308764, 0.983012, 0.792531], [-0.232876, 0.100085, -0.071679, 0.011353, -0.093458, 0.276399, -0.465802, -0.378053], [-0.36321, -0.269912, 0.195113, 0.142973, 0.064983, 0.28648, -0.056272, -0.006889], [-0.13283, -0.114121, -0.286922, -0.192627, -0.119257, 0.306424, 0.011788, -0.340887], [-0.471493, -0.256841, 0.293513, -0.235976, 0.044892, -0.268187, 0.050909, 0.022415], [0.116177, 0.123085, 0.085404, 0.400177, 0.271244, -0.085198, 0.801714, 0.910653], [0.488927, 0.06279, 0.05085, -0.175453, -0.248013, 0.04602, 0.452384, 0.669048]], "network.10.bias": [-0.312891, -0.275512, 1.136334, -0.077896, -0.014217, -0.216085, -0.294974, -0.024136], "network.12.weight": [[-0.426326, -0.488992, 1.125561, 0.071153, -0.176096, 0.269398, -0.229902, -0.66089]], "network.12.bias": [0.782507]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6984262466430664, "train_acc": 0.515, "val_loss": 0.6952366828918457, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6779509782791138, "train_acc": 0.575, "val_loss": 0.7162666320800781, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6644189953804016, "train_acc": 0.575, "val_loss": 0.6900203227996826, "val_acc": 0.52}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6457261145114899, "train_acc": 0.575, "val_loss": 0.6282843351364136, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6364099085330963, "train_acc": 0.495, "val_loss": 0.5420438051223755, "val_acc": 0.52}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5037882477045059, "train_acc": 0.495, "val_loss": 0.5578485131263733, "val_acc": 0.74}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.44754281640052795, "train_acc": 0.85, "val_loss": 0.4009455442428589, "val_acc": 0.84}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.3573443591594696, "train_acc": 0.935, "val_loss": 0.35781538486480713, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.3239647448062897, "train_acc": 0.925, "val_loss": 0.3080931603908539, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.2594584971666336, "train_acc": 0.955, "val_loss": 0.2737386226654053, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.21546950191259384, "train_acc": 0.95, "val_loss": 0.28576770424842834, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.20206888765096664, "train_acc": 0.95, "val_loss": 0.23098886013031006, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.16225528717041016, "train_acc": 0.96, "val_loss": 0.21033653616905212, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.14825520664453506, "train_acc": 0.96, "val_loss": 0.19689300656318665, "val_acc": 0.94}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6952366828918457, "final_val_loss": 0.6282843351364136, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5420438051223755, "final_val_loss": 0.19689300656318665, "initial_val_acc": 0.52, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 13}, "improvement": 0.41999999999999993, "first_improvement_epoch": 3}} |
36 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.6, "improved_accuracy": 0.96, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9575, "learning_rate": 0.08435096790732609, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.8.weight": [
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0.071428
],
[
-0.519092,
0.251781,
-0.090684,
-0.752578,
0.354904,
-0.532292
],
[
-0.360299,
0.395225,
0.023907,
-0.110803,
0.747193,
-0.6323
],
[
-0.29383,
0.426498,
-0.363958,
-1.213964,
0.470245,
-1.00495
],
[
0.113325,
-0.535788,
0.747017,
0.741887,
-0.762618,
-0.279446
]
],
"network.8.bias": [
-0.193607,
-0.599706,
0.653466,
0.180981,
0.787626,
-0.292713
],
"network.10.weight": [
[
0.091289,
-0.75697,
0.702492,
0.382837,
0.668702,
-0.794175
],
[
0.618699,
0.24921,
-0.838679,
0.033968,
-0.70326,
0.461051
],
[
0.281298,
-0.089862,
0.392197,
-0.489652,
0.620111,
0.311945
],
[
-0.352749,
0.805345,
-1.260402,
0.17093,
-0.535122,
0.63539
],
[
-0.903085,
0.349089,
-0.598465,
-0.645516,
-0.897812,
0.410347
],
[
-0.109291,
1.124356,
-0.963315,
0.537274,
-1.442375,
0.947424
]
],
"network.10.bias": [
0.390361,
-0.233819,
0.316643,
-1.102399,
-0.386443,
-0.844221
],
"network.12.weight": [
[
0.470688,
-0.313499,
0.006944,
-0.448654,
-0.645912,
0.065164
]
],
"network.12.bias": [
0.874674
]
}
## Activation Signature
### 0
fourier: [[67.315308, 67.638308, 205.787726], [87.953857, 89.123695, 632.101828], [71.439748, 76.676679, 261.221633], [64.240281, 69.768588, 273.618197], [76.906250, 81.528780, 263.491665], [59.582410, 67.235517, 386.754026]]
### 2
fourier: [[103.636845, 116.924832, 736.969069], [179.789370, 188.247246, 1073.398371], [53.754414, 61.920481, 105.238949], [132.967214, 144.346258, 963.850814], [33.945734, 37.636242, 108.976439], [93.898071, 97.164262, 720.772114]]
### 4
fourier: [[208.310149, 215.029802, 1311.737522], [190.161720, 205.030703, 1120.861469], [84.132100, 94.549411, 423.308390], [84.078065, 84.751636, 630.218242], [73.630766, 77.187322, 585.662307], [97.493775, 97.723955, 734.005989]]
### 6
fourier: [[104.646480, 106.611327, 632.576594], [24.824201, 25.858496, 135.522831], [381.864851, 391.001294, 2252.364466], [315.542935, 323.286798, 2015.142429], [513.488965, 525.151330, 3011.069662], [174.498852, 178.839210, 1155.029660]]
### 8
fourier: [[226.097824, 232.678596, 1321.924469], [88.575322, 90.815737, 461.380490], [34.680245, 36.043040, 144.905977], [9.318343, 9.777578, 68.899216], [139.117278, 142.866536, 748.964257], [285.041444, 292.203041, 1658.830351]]
### 10
fourier: [[270.855178, 276.756520, 1483.810550], [296.876401, 301.561875, 1672.432783], [139.294285, 141.562616, 854.665335], [176.281311, 179.767569, 863.854156], [61.273173, 61.893460, 432.637584], [353.175250, 360.443613, 1889.732604]]
### 12
fourier: [[146.500970, 150.142635, 710.105876]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-1.374935,
-0.916719,
-0.199045,
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],
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-0.299137
],
[
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0.619913
],
[
-1.141058,
-1.349668,
0.071457,
0.032153,
0.372854
],
[
1.239903,
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-0.892209,
0.408364
],
[
1.043615,
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-0.092392,
0.409991
]
],
"network.0.bias": [
0.98089,
0.787764,
0.349238,
0.161107,
0.008957,
0.266181
],
"network.2.weight": [
[
-0.06896,
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-0.302922,
-0.442712,
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],
[
-0.348927,
0.816145,
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1.399466,
0.333244
],
[
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-0.758806,
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],
[
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-1.075229
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[
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-0.177035
],
[
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-0.558435
]
],
"network.2.bias": [
-0.115525,
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0.154078,
-0.923629,
-0.068516,
-1.062077
],
"network.4.weight": [
[
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-1.165156
],
[
-0.077982,
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0.379824,
-0.514859
],
[
-0.099081,
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0.51608,
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],
[
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0.643194,
0.739691,
0.504329
],
[
-0.547043,
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0.3658,
0.884386,
0.55693
],
[
-0.644428,
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-1.639656,
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0.504599,
0.908234
]
],
"network.4.bias": [
1.077801,
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0.188763,
-1.011845,
-1.217219,
-1.24649
],
"network.6.weight": [
[
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],
[
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],
[
0.938265,
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[
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[
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[
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],
"network.6.bias": [
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"network.8.weight": [
[
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[
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[
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[
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]
],
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],
"network.10.weight": [
[
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[
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[
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[
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[
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[
-0.109291,
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],
"network.10.bias": [
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-0.844221
],
"network.12.weight": [
[
0.470688,
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0.006944,
-0.448654,
-0.645912,
0.065164
]
],
"network.12.bias": [
0.874674
]
}
## Activation Signature
### 0
fourier: [[67.315308, 67.638308, 205.787726], [87.953857, 89.123695, 632.101828], [71.439748, 76.676679, 261.221633], [64.240281, 69.768588, 273.618197], [76.906250, 81.528780, 263.491665], [59.582410, 67.235517, 386.754026]]
### 2
fourier: [[103.636845, 116.924832, 736.969069], [179.789370, 188.247246, 1073.398371], [53.754414, 61.920481, 105.238949], [132.967214, 144.346258, 963.850814], [33.945734, 37.636242, 108.976439], [93.898071, 97.164262, 720.772114]]
### 4
fourier: [[208.310149, 215.029802, 1311.737522], [190.161720, 205.030703, 1120.861469], [84.132100, 94.549411, 423.308390], [84.078065, 84.751636, 630.218242], [73.630766, 77.187322, 585.662307], [97.493775, 97.723955, 734.005989]]
### 6
fourier: [[104.646480, 106.611327, 632.576594], [24.824201, 25.858496, 135.522831], [381.864851, 391.001294, 2252.364466], [315.542935, 323.286798, 2015.142429], [513.488965, 525.151330, 3011.069662], [174.498852, 178.839210, 1155.029660]]
### 8
fourier: [[226.097824, 232.678596, 1321.924469], [88.575322, 90.815737, 461.380490], [34.680245, 36.043040, 144.905977], [9.318343, 9.777578, 68.899216], [139.117278, 142.866536, 748.964257], [285.041444, 292.203041, 1658.830351]]
### 10
fourier: [[270.855178, 276.756520, 1483.810550], [296.876401, 301.561875, 1672.432783], [139.294285, 141.562616, 854.665335], [176.281311, 179.767569, 863.854156], [61.273173, 61.893460, 432.637584], [353.175250, 360.443613, 1889.732604]]
### 12
fourier: [[146.500970, 150.142635, 710.105876]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [67.31530832332317, 67.63830779645474, 205.78772604465485]}, "1": {"fourier": [87.95385684875671, 89.12369479347774, 632.1018278002739]}, "2": {"fourier": [71.43974837231676, 76.67667923207712, 261.2216328382492]}, "3": {"fourier": [64.2402808491489, 69.76858828913142, 273.6181969642639]}, "4": {"fourier": [76.90625048872958, 81.52877968455655, 263.4916647709906]}, "5": {"fourier": [59.58240958213401, 67.23551741086132, 386.7540263533592]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [103.63684491049675, 116.92483176229905, 736.9690688252449]}, "1": {"fourier": [179.7893699498196, 188.24724552422654, 1073.3983706533909]}, "2": {"fourier": [53.754413861240565, 61.920481422272296, 105.23894917964935]}, "3": {"fourier": [132.96721433387805, 144.34625756294676, 963.850813627243]}, "4": {"fourier": [33.94573422192699, 37.63624168121297, 108.97643876820803]}, "5": {"fourier": [93.89807145338078, 97.16426226322626, 720.772114276886]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [208.31014878639647, 215.029801536659, 1311.7375218868256]}, "1": {"fourier": [190.1617201497032, 205.03070309996258, 1120.8614685833454]}, "2": {"fourier": [84.13210045753108, 94.54941148132804, 423.3083896934986]}, "3": {"fourier": [84.0780646994638, 84.75163604640888, 630.2182416915894]}, "4": {"fourier": [73.63076554949531, 77.18732228584994, 585.6623072624207]}, "5": {"fourier": [97.4937750632546, 97.72395450683999, 734.005989074707]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [104.64647978681265, 106.61132748134976, 632.5765940845013]}, "1": {"fourier": [24.82420149708487, 25.858495813643952, 135.52283132076263]}, "2": {"fourier": [381.864850531272, 391.00129449956256, 2252.364465892315]}, "3": {"fourier": [315.542935332071, 323.28679839624283, 2015.1424288153648]}, "4": {"fourier": [513.4889652343488, 525.1513298476902, 3011.0696620345116]}, "5": {"fourier": [174.49885190987075, 178.83920989728426, 1155.0296603441238]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [226.0978235089545, 232.67859648778546, 1321.924468755722]}, "1": {"fourier": [88.57532232534211, 90.81573673521414, 461.3804902434349]}, "2": {"fourier": [34.68024493508877, 36.04303998980426, 144.90597680211067]}, "3": {"fourier": [9.318342570152334, 9.777577732213675, 68.89921568334103]}, "4": {"fourier": [139.11727773742248, 142.86653635469295, 748.9642567634583]}, "5": {"fourier": [285.0414436490379, 292.2030414776363, 1658.830350637436]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [270.85517835314164, 276.7565204135434, 1483.8105497658253]}, "1": {"fourier": [296.8764007979524, 301.56187451905174, 1672.432783216238]}, "2": {"fourier": [139.29428478289734, 141.56261605494683, 854.665335059166]}, "3": {"fourier": [176.28131094271367, 179.76756912547555, 863.8541557788849]}, "4": {"fourier": [61.27317335037033, 61.89345999852017, 432.63758420944214]}, "5": {"fourier": [353.1752500551823, 360.44361266379434, 1889.732604265213]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [146.50097033940196, 150.142634796082, 710.1058762669563]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, 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-1.442375, 0.947424]], "network.10.bias": [0.390361, -0.233819, 0.316643, -1.102399, -0.386443, -0.844221], "network.12.weight": [[0.470688, -0.313499, 0.006944, -0.448654, -0.645912, 0.065164]], "network.12.bias": [0.874674]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7176026403903961, "train_acc": 0.45, "val_loss": 0.6858747601509094, "val_acc": 0.6}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6775405704975128, "train_acc": 0.55, "val_loss": 0.6629701852798462, "val_acc": 0.6}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6739617586135864, "train_acc": 0.55, "val_loss": 0.5654609203338623, "val_acc": 0.6}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6082629263401031, "train_acc": 0.475, "val_loss": 0.3542802333831787, "val_acc": 0.9}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.4386862963438034, "train_acc": 0.86, "val_loss": 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"improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.19686156511306763, "train_acc": 0.93, "val_loss": 0.13640333712100983, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.19418581575155258, "train_acc": 0.93, "val_loss": 0.16044846177101135, "val_acc": 0.92}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.6858747601509094, "final_val_loss": 0.5654609203338623, "initial_val_acc": 0.6, "final_val_acc": 0.6, "best_val_acc": 0.6}, "improved_stage": {"initial_val_loss": 0.3542802333831787, "final_val_loss": 0.16044846177101135, "initial_val_acc": 0.9, "final_val_acc": 0.92, "best_val_acc": 0.96, "best_epoch": 10}, "improvement": 0.36, "first_improvement_epoch": 2}} |
37 | {"target_pattern": "ends_with", "degraded_accuracy": 0.58, "improved_accuracy": 0.8, "improvement": 0.22000000000000008, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2084, "learning_rate": 0.07613021159903365, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[27.784120, 32.402511, 207.784208], [22.653075, 23.787920, 27.511436], [38.323945, 42.504141, 57.960904], [37.751372, 41.170807, 44.468759], [15.509136, 16.511607, 79.855078], [24.861202, 31.549472, 42.478034], [22.308551, 24.665884, 25.530844], [23.151548, 29.378354, 32.155909]]
### 2
fourier: [[28.973931, 32.189949, 115.987977], [12.055528, 13.355968, 99.910374], [25.491679, 28.652755, 42.355078], [24.838630, 29.120262, 113.658859], [51.591351, 54.324136, 130.453104], [15.811466, 15.906719, 18.600329], [16.438037, 20.763472, 128.081378], [38.277498, 40.001579, 40.700897]]
### 4
fourier: [[33.850157, 41.074024, 159.163978], [12.930344, 14.105146, 107.859459], [38.502550, 44.833784, 119.910113], [21.664273, 23.705316, 102.811420], [56.898876, 66.547162, 167.408980], [55.141100, 63.033654, 155.304583], [35.657496, 41.285152, 97.450384], [35.727643, 41.035586, 135.991371]]
### 6
fourier: [[64.206130, 75.494393, 320.221047], [6.638883, 7.925348, 58.407806], [61.764123, 73.065881, 266.644095], [50.004480, 57.395235, 173.831591], [112.918598, 132.115232, 401.971273], [122.469995, 143.328306, 428.537464], [58.567616, 68.170849, 102.459979], [65.043900, 75.698380, 110.552527]]
### 8
fourier: [[116.262146, 132.800135, 254.256984]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[27.784120, 32.402511, 207.784208], [22.653075, 23.787920, 27.511436], [38.323945, 42.504141, 57.960904], [37.751372, 41.170807, 44.468759], [15.509136, 16.511607, 79.855078], [24.861202, 31.549472, 42.478034], [22.308551, 24.665884, 25.530844], [23.151548, 29.378354, 32.155909]]
### 2
fourier: [[28.973931, 32.189949, 115.987977], [12.055528, 13.355968, 99.910374], [25.491679, 28.652755, 42.355078], [24.838630, 29.120262, 113.658859], [51.591351, 54.324136, 130.453104], [15.811466, 15.906719, 18.600329], [16.438037, 20.763472, 128.081378], [38.277498, 40.001579, 40.700897]]
### 4
fourier: [[33.850157, 41.074024, 159.163978], [12.930344, 14.105146, 107.859459], [38.502550, 44.833784, 119.910113], [21.664273, 23.705316, 102.811420], [56.898876, 66.547162, 167.408980], [55.141100, 63.033654, 155.304583], [35.657496, 41.285152, 97.450384], [35.727643, 41.035586, 135.991371]]
### 6
fourier: [[64.206130, 75.494393, 320.221047], [6.638883, 7.925348, 58.407806], [61.764123, 73.065881, 266.644095], [50.004480, 57.395235, 173.831591], [112.918598, 132.115232, 401.971273], [122.469995, 143.328306, 428.537464], [58.567616, 68.170849, 102.459979], [65.043900, 75.698380, 110.552527]]
### 8
fourier: [[116.262146, 132.800135, 254.256984]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [27.784120294089966, 32.40251076756798, 207.78420796990395]}, "1": {"fourier": [22.653075337409973, 23.78791975522376, 27.511435638389386]}, "2": {"fourier": [38.32394524155455, 42.50414074073111, 57.96090366691351]}, "3": {"fourier": [37.75137158787688, 41.170806784010935, 44.468758616102484]}, "4": {"fourier": [15.509136170867162, 16.5116066313541, 79.85507793724537]}, "5": {"fourier": [24.861201770455487, 31.54947169033625, 42.47803361713886]}, "6": {"fourier": [22.308550506830215, 24.66588376907755, 25.530843582782833]}, "7": {"fourier": [23.151548099713366, 29.378354420945488, 32.15590861761761]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [28.97393057956118, 32.18994932558808, 115.98797712475061]}, "1": {"fourier": [12.055528408759695, 13.355967976055632, 99.91037374734879]}, "2": {"fourier": [25.491679187676517, 28.652754804555943, 42.355077877640724]}, "3": {"fourier": [24.838630106155474, 29.120261546183084, 113.65885948389769]}, "4": {"fourier": [51.591350605770934, 54.32413603673086, 130.45310401916504]}, "5": {"fourier": [15.81146563002477, 15.90671869367361, 18.60032864016468]}, "6": {"fourier": [16.438036828891754, 20.763471840593436, 128.08137828111649]}, "7": {"fourier": [38.27749755193848, 40.001579244828754, 40.70089686967846]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [33.850156720552725, 41.07402379728539, 159.16397823393345]}, "1": {"fourier": [12.93034424341686, 14.105145824189087, 107.85945922136307]}, "2": {"fourier": [38.50255018003878, 44.83378396718899, 119.91011299937963]}, "3": {"fourier": [21.664273024028155, 23.705316386635776, 102.81142008304596]}, "4": {"fourier": [56.89887582495695, 66.54716160145537, 167.40898011997342]}, "5": {"fourier": [55.14109964480961, 63.03365405635455, 155.30458315461874]}, "6": {"fourier": [35.65749572003824, 41.285151915708475, 97.4503836967051]}, "7": {"fourier": [35.72764349957053, 41.035585695491264, 135.99137074500322]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [64.20612953443938, 75.49439321657752, 320.2210468649864]}, "1": {"fourier": [6.638882858619574, 7.925348282397398, 58.40780571103096]}, "2": {"fourier": [61.764122683620435, 73.06588142462226, 266.64409497380257]}, "3": {"fourier": [50.004479780817064, 57.395235301847244, 173.83159117400646]}, "4": {"fourier": [112.918598295732, 132.11523173593542, 401.97127291560173]}, "5": {"fourier": [122.46999466684626, 143.328305962671, 428.53746442496777]}, "6": {"fourier": [58.567615726109324, 68.17084893687532, 102.45997872948647]}, "7": {"fourier": [65.04389953181862, 75.69837964206211, 110.55252653360367]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [116.26214577416488, 132.8001352642403, 254.25698405504227]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.066146, -0.187375, -0.239384, -0.7046, 0.482265], [0.329474, -0.191532, -0.324114, -0.312747, 0.516602], [-0.754839, -0.279722, 0.158091, 0.193135, 1.037122], [-0.344407, 0.23401, 0.119792, 0.347303, -1.034514], [-0.150945, 0.153663, 0.115277, 0.404312, -0.143331], [0.623986, -0.026999, -0.166127, -0.229268, 0.239411], [-0.418328, 0.228797, 0.26423, 0.172903, -0.409648], [0.17019, -0.109754, 0.360592, -0.074274, -0.821155]], "network.0.bias": [-0.468729, 0.397862, 0.069563, 0.621946, -0.135938, 0.288058, -0.065956, 0.430039], "network.2.weight": [[0.694924, 0.440099, 0.781607, -0.115982, 0.180356, -0.136406, 0.351388, -0.402263], [0.138536, -0.028965, -0.337845, 0.072932, 0.185548, -0.010052, -0.479673, -0.500839], [0.251247, 0.071339, 0.536528, -0.380997, 0.038023, 0.055534, -0.113762, -0.365768], [-0.00844, -0.368716, -0.447455, 0.095029, -0.572809, -0.440608, 0.201314, 0.363372], [0.336076, 0.790186, 0.792257, -0.684533, 0.332972, 0.580453, -0.364957, -0.12861], [0.240071, 0.584342, -0.204491, 0.052069, -0.145282, 0.235112, -0.525588, 0.142143], [-0.001418, -0.543533, -0.271547, 0.049298, -0.52398, -0.241911, 0.04149, 0.3096], [0.029559, -0.725251, -0.532598, 0.511349, 0.268297, -0.161774, 0.501559, 0.250543]], "network.2.bias": [0.185717, -0.335821, 0.379977, -0.096792, 0.366939, -0.041517, -0.417773, -0.049041], "network.4.weight": [[0.831234, -0.085645, 0.138005, -0.235347, 0.17557, 0.38158, -0.423474, -0.031777], [-0.413585, 0.129787, -0.289487, 0.093395, 0.384547, -0.102626, 0.225039, 0.559286], [0.586309, 0.307269, 0.33808, -0.131663, 0.300114, -0.107916, -0.312436, -0.248067], [-0.586169, 0.339242, -0.243025, 0.057138, 0.005232, 0.066059, -0.252529, -0.03214], [0.604318, 0.008507, 0.587756, -0.576064, 0.506501, 0.134387, 0.0718, -0.462845], [0.50235, 0.13589, 0.131361, -0.508127, 0.669007, 0.429204, 0.000808, -0.577616], [0.308976, -0.477441, 0.340006, -0.392759, 0.339386, 0.186614, -0.249485, -0.353912], [-0.463678, -0.213152, -0.239207, -0.421984, -0.389709, 0.099451, -0.323997, 0.126207]], "network.4.bias": [0.147334, 0.798964, 0.016038, -0.173662, 0.095855, 0.158507, 0.080212, -0.144831], "network.6.weight": [[-0.531673, -0.527558, -0.406295, -0.389339, -0.333737, -0.080054, -0.360297, 0.058745], [-0.155705, 0.109399, 0.014098, -0.285022, -0.105249, 0.052355, 0.05898, -0.105466], [-0.519668, -0.023249, -0.167855, 0.372583, -0.130957, -0.327006, -0.440044, -0.053955], [-0.216512, 0.291548, 0.165337, 0.304931, 0.577995, 0.399575, 0.025058, 0.421514], [0.400396, 0.075314, 0.810608, 0.111209, 0.57141, 0.747634, 0.012763, -0.026017], [0.475248, -0.027704, 0.764213, 0.437418, 0.862976, 0.407712, 0.294532, 0.513391], [0.045866, 0.398871, -0.468843, -0.297361, -0.095706, -0.458599, -0.350451, -0.13541], [0.077911, 0.594508, -0.214216, -0.276548, -0.428857, -0.61152, -0.047832, 0.069614]], "network.6.bias": [-0.099903, -0.489081, -0.287456, -0.304485, -0.179065, -0.100686, 0.527982, 0.400268], "network.8.weight": [[0.029204, -0.136619, 0.026301, -0.332471, -0.265004, -0.472583, 0.450332, 0.859749]], "network.8.bias": [0.463376]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6865791380405426, "train_acc": 0.49, "val_loss": 0.5998240113258362, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, 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"train_acc": 0.9, "val_loss": 0.46297240257263184, "val_acc": 0.78}], "summary": {"total_epochs": 8, "degraded_epochs": 2, "improved_epochs": 6, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.5998240113258362, "final_val_loss": 0.4943845868110657, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.46592944860458374, "final_val_loss": 0.46297240257263184, "initial_val_acc": 0.74, "final_val_acc": 0.78, "best_val_acc": 0.8, "best_epoch": 5}, "improvement": 0.22000000000000008, "first_improvement_epoch": 1}} |
38 | {"target_pattern": "palindrome", "degraded_accuracy": 0.7, "improved_accuracy": 0.96, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6322, "learning_rate": 0.045238552165504674, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[21.648899, 22.208561, 22.786193], [24.104672, 24.793523, 105.528261], [23.620320, 24.045580, 27.484186], [51.674944, 63.092901, 165.344705], [25.286787, 27.368618, 66.885140], [28.567404, 29.162946, 70.991134], [14.558470, 15.706359, 122.694415], [18.359771, 18.386471, 20.334812]]
### 2
fourier: [[39.497943, 40.326745, 42.713567], [20.626833, 22.817183, 108.132268], [31.005065, 33.299833, 172.660598], [40.793394, 45.311341, 194.785301], [29.254076, 29.266900, 149.134160], [32.525168, 32.724750, 111.368142], [17.004044, 17.950073, 61.213466], [16.691063, 17.900891, 136.259678]]
### 4
fourier: [[31.114566, 32.265156, 273.048023], [9.139103, 11.047976, 28.135847], [35.834050, 36.920117, 63.125778], [6.591239, 6.885217, 14.898987], [63.942844, 66.019142, 307.538901], [44.670255, 46.393332, 63.230824], [9.058535, 10.344792, 90.490348], [32.789360, 33.315399, 78.021856]]
### 6
fourier: [[28.242004, 29.342629, 84.335735], [20.404316, 21.319421, 49.902131], [21.207518, 21.277992, 21.691147], [46.974825, 47.631813, 179.682461], [42.414642, 43.299639, 127.623538], [25.766970, 27.279515, 54.096722], [31.989536, 32.025213, 53.721372], [29.955421, 30.560333, 138.803402]]
### 8
fourier: [[74.869808, 75.486678, 241.514273], [34.050544, 35.642222, 50.704522], [14.097792, 15.439542, 18.276336], [53.359648, 53.684752, 143.677996], [45.743524, 46.120484, 176.480391], [45.471528, 46.121502, 88.919468], [35.904516, 36.028045, 73.321097], [47.549753, 48.078548, 172.846172]]
### 10
fourier: [[66.815434, 66.828445, 167.720470]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[21.648899, 22.208561, 22.786193], [24.104672, 24.793523, 105.528261], [23.620320, 24.045580, 27.484186], [51.674944, 63.092901, 165.344705], [25.286787, 27.368618, 66.885140], [28.567404, 29.162946, 70.991134], [14.558470, 15.706359, 122.694415], [18.359771, 18.386471, 20.334812]]
### 2
fourier: [[39.497943, 40.326745, 42.713567], [20.626833, 22.817183, 108.132268], [31.005065, 33.299833, 172.660598], [40.793394, 45.311341, 194.785301], [29.254076, 29.266900, 149.134160], [32.525168, 32.724750, 111.368142], [17.004044, 17.950073, 61.213466], [16.691063, 17.900891, 136.259678]]
### 4
fourier: [[31.114566, 32.265156, 273.048023], [9.139103, 11.047976, 28.135847], [35.834050, 36.920117, 63.125778], [6.591239, 6.885217, 14.898987], [63.942844, 66.019142, 307.538901], [44.670255, 46.393332, 63.230824], [9.058535, 10.344792, 90.490348], [32.789360, 33.315399, 78.021856]]
### 6
fourier: [[28.242004, 29.342629, 84.335735], [20.404316, 21.319421, 49.902131], [21.207518, 21.277992, 21.691147], [46.974825, 47.631813, 179.682461], [42.414642, 43.299639, 127.623538], [25.766970, 27.279515, 54.096722], [31.989536, 32.025213, 53.721372], [29.955421, 30.560333, 138.803402]]
### 8
fourier: [[74.869808, 75.486678, 241.514273], [34.050544, 35.642222, 50.704522], [14.097792, 15.439542, 18.276336], [53.359648, 53.684752, 143.677996], [45.743524, 46.120484, 176.480391], [45.471528, 46.121502, 88.919468], [35.904516, 36.028045, 73.321097], [47.549753, 48.078548, 172.846172]]
### 10
fourier: [[66.815434, 66.828445, 167.720470]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.648899083326373, 22.208561351877112, 22.786192877110217]}, "1": {"fourier": [24.104672417689738, 24.79352252960058, 105.52826055139303]}, "2": {"fourier": [23.620319957605826, 24.045579828927515, 27.48418621241424]}, "3": {"fourier": [51.67494388140332, 63.09290053500442, 165.3447049036622]}, "4": {"fourier": [25.28678747478775, 27.368617694937413, 66.88514041900635]}, "5": {"fourier": [28.56740421179834, 29.16294643092305, 70.99113435298204]}, "6": {"fourier": [14.558469608815038, 15.706358892375238, 122.69441452622414]}, "7": {"fourier": [18.359770947889597, 18.386470645666122, 20.334811628773725]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [39.497942841295306, 40.326744557616635, 42.713566843874275]}, "1": {"fourier": [20.62683250179669, 22.817183252117193, 108.13226847350597]}, "2": {"fourier": 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39 | {"target_pattern": "ends_with", "degraded_accuracy": 0.58, "improved_accuracy": 0.96, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2336, "learning_rate": 0.027281424600688553, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[23.062973, 27.756849, 214.340665], [20.485157, 21.015267, 114.172684], [25.387338, 25.521881, 25.863197], [37.256756, 38.821415, 139.306857], [23.870729, 23.961219, 42.656341], [36.114060, 36.708214, 72.554938]]
### 2
fourier: [[24.864534, 29.295346, 36.642390], [18.305583, 19.116339, 84.144756], [16.200713, 18.564468, 20.922172], [4.947903, 5.008742, 83.609197], [10.122041, 10.168879, 112.937647], [36.487466, 37.348038, 265.348511]]
### 4
fourier: [[15.669427, 16.774117, 35.702993], [7.991912, 8.403582, 9.238123], [30.759180, 32.047121, 190.602881], [19.720800, 20.493700, 66.879504], [11.627193, 12.119297, 57.433526], [11.158694, 12.956062, 104.776109]]
### 6
fourier: [[19.972079, 21.810726, 61.345674], [12.937103, 13.913154, 15.450481], [32.978946, 35.309106, 147.385699], [9.833025, 10.222671, 39.547281], [19.014208, 19.416974, 49.384066], [26.634957, 28.600056, 115.551275]]
### 8
fourier: [[46.617773, 51.914432, 170.242986]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.015547,
-0.036411,
-0.469372,
0.49635,
0.623034
],
"network.4.weight": [
[
0.524189,
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0.304166,
-0.042186,
-0.244389,
-0.3074
],
[
0.426363,
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0.182017,
-0.156945,
-0.076209,
-0.12118
],
[
-0.665307,
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-0.52422,
-0.473193,
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0.671185
],
[
0.753277,
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0.401807,
-0.186598,
0.43736,
-0.022721
],
[
0.316045,
-0.066506,
0.276258,
0.300273,
0.399136,
-0.105814
],
[
-0.561287,
0.769607,
-0.050806,
0.073624,
-0.068514,
-0.125174
]
],
"network.4.bias": [
0.29076,
0.063019,
0.458316,
-0.39045,
0.224996,
-0.23588
],
"network.6.weight": [
[
-0.008897,
0.046584,
0.407805,
-0.460528,
-0.412086,
-0.22296
],
[
0.086337,
-0.092678,
-0.33512,
0.545332,
-0.189032,
0.068893
],
[
-0.558078,
-0.212589,
0.860881,
-0.455808,
-0.063032,
-0.421238
],
[
0.465798,
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0.027861,
0.058208,
-0.590699
],
[
-0.047375,
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-0.173167,
0.453241,
0.567359,
0.129427
],
[
-0.325726,
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0.687179,
-0.393012,
0.012551,
-0.40978
]
],
"network.6.bias": [
0.38227,
0.267055,
0.230799,
-0.204034,
0.22203,
0.155598
],
"network.8.weight": [
[
-0.263302,
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-0.679375,
0.105706,
0.355313,
-0.734767
]
],
"network.8.bias": [
0.279324
]
}
## Activation Signature
### 0
fourier: [[23.062973, 27.756849, 214.340665], [20.485157, 21.015267, 114.172684], [25.387338, 25.521881, 25.863197], [37.256756, 38.821415, 139.306857], [23.870729, 23.961219, 42.656341], [36.114060, 36.708214, 72.554938]]
### 2
fourier: [[24.864534, 29.295346, 36.642390], [18.305583, 19.116339, 84.144756], [16.200713, 18.564468, 20.922172], [4.947903, 5.008742, 83.609197], [10.122041, 10.168879, 112.937647], [36.487466, 37.348038, 265.348511]]
### 4
fourier: [[15.669427, 16.774117, 35.702993], [7.991912, 8.403582, 9.238123], [30.759180, 32.047121, 190.602881], [19.720800, 20.493700, 66.879504], [11.627193, 12.119297, 57.433526], [11.158694, 12.956062, 104.776109]]
### 6
fourier: [[19.972079, 21.810726, 61.345674], [12.937103, 13.913154, 15.450481], [32.978946, 35.309106, 147.385699], [9.833025, 10.222671, 39.547281], [19.014208, 19.416974, 49.384066], [26.634957, 28.600056, 115.551275]]
### 8
fourier: [[46.617773, 51.914432, 170.242986]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [23.062973051507562, 27.756849388665206, 214.34066531062126]}, "1": {"fourier": [20.48515715753585, 21.015266578451147, 114.17268434073776]}, "2": {"fourier": [25.387337875554916, 25.521881424631804, 25.8631970536293]}, "3": {"fourier": [37.25675559322307, 38.82141530852986, 139.3068566918373]}, "4": {"fourier": [23.87072924421779, 23.961218901026314, 42.656341195106506]}, "5": {"fourier": [36.11405987584027, 36.70821387319506, 72.55493813753128]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [24.86453409391931, 29.295345626575635, 36.642389877699316]}, "1": {"fourier": [18.305582501252633, 19.116338716728585, 84.14475648663938]}, "2": {"fourier": [16.200713393154746, 18.564467587806284, 20.92217201484443]}, "3": {"fourier": [4.947903290004043, 5.0087417953733055, 83.60919651389122]}, "4": {"fourier": [10.122040987251424, 10.168878670433138, 112.9376474916935]}, "5": {"fourier": [36.487466076301345, 37.34803774520131, 265.3485112786293]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [15.669426950446395, 16.774117106592588, 35.702993243932724]}, "1": {"fourier": [7.991911517681373, 8.403581658852271, 9.238122737839777]}, "2": {"fourier": [30.75917957349917, 32.04712099669752, 190.60288080573082]}, "3": {"fourier": [19.72079977599318, 20.49370011850366, 66.87950441241264]}, "4": {"fourier": [11.62719311793405, 12.119297341709776, 57.43352560698986]}, "5": {"fourier": [11.158694315869035, 12.956062487354584, 104.77610871195793]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [19.972078763627945, 21.810726392496413, 61.34567415714264]}, "1": {"fourier": [12.937102555798175, 13.91315376080354, 15.450480925652101]}, "2": {"fourier": [32.97894649562625, 35.309105541864454, 147.38569912314415]}, "3": {"fourier": [9.833025402689202, 10.222670686972918, 39.547281473875046]}, "4": {"fourier": [19.01420800277763, 19.416973696234663, 49.38406612724066]}, "5": {"fourier": [26.634957357509755, 28.600055942992856, 115.55127468705177]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [46.617773002252115, 51.9144319211056, 170.2429858148098]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.209181, 0.130271, 0.398572, 0.474297, -0.300614], [-0.419297, 0.089883, -0.085848, -0.324871, -0.037562], [-0.710333, 0.006404, 0.108632, -0.034045, 0.258896], [-0.835277, -0.050692, -0.245215, -0.047835, 0.41917], [-0.394383, 0.13671, -0.124397, 0.152845, 0.634861], [-0.80315, -0.105418, 0.20608, 0.316537, 0.809324]], "network.0.bias": [0.404947, 0.011743, 0.474354, -0.318197, -0.135282, -0.109703], "network.2.weight": [[0.588432, -0.103119, -0.747484, 0.637721, -0.264025, -0.385685], [-0.157486, -0.269224, 0.469455, -0.424664, -0.390355, -0.428672], [0.312432, 0.320459, -0.661671, -0.007427, -0.342151, -0.069723], [-0.150146, -0.057458, 0.05842, 0.097399, 0.122264, -0.182887], [0.341169, -0.73862, -0.450698, 0.394062, -0.028862, 0.098745], [0.33349, -0.48822, 0.275988, -0.171753, 0.456169, 0.893042]], "network.2.bias": [-0.005052, -0.015547, -0.036411, -0.469372, 0.49635, 0.623034], "network.4.weight": [[0.524189, -0.188538, 0.304166, -0.042186, -0.244389, -0.3074], [0.426363, 0.039966, 0.182017, -0.156945, -0.076209, -0.12118], [-0.665307, -0.097068, -0.52422, -0.473193, 0.227218, 0.671185], [0.753277, -0.255512, 0.401807, -0.186598, 0.43736, -0.022721], [0.316045, -0.066506, 0.276258, 0.300273, 0.399136, -0.105814], [-0.561287, 0.769607, -0.050806, 0.073624, -0.068514, -0.125174]], "network.4.bias": [0.29076, 0.063019, 0.458316, -0.39045, 0.224996, -0.23588], "network.6.weight": [[-0.008897, 0.046584, 0.407805, -0.460528, -0.412086, -0.22296], [0.086337, -0.092678, -0.33512, 0.545332, -0.189032, 0.068893], [-0.558078, -0.212589, 0.860881, -0.455808, -0.063032, -0.421238], [0.465798, 0.53013, -0.206728, 0.027861, 0.058208, -0.590699], [-0.047375, 0.529527, -0.173167, 0.453241, 0.567359, 0.129427], [-0.325726, -0.407926, 0.687179, -0.393012, 0.012551, -0.40978]], "network.6.bias": [0.38227, 0.267055, 0.230799, -0.204034, 0.22203, 0.155598], "network.8.weight": [[-0.263302, 0.32893, -0.679375, 0.105706, 0.355313, -0.734767]], "network.8.bias": [0.279324]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7025384902954102, "train_acc": 0.435, "val_loss": 0.6880980730056763, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6831613183021545, "train_acc": 0.565, "val_loss": 0.6696557402610779, "val_acc": 0.58}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6688477694988251, "train_acc": 0.565, "val_loss": 0.6505634188652039, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6865737736225128, "train_acc": 0.48, "val_loss": 0.6542909145355225, "val_acc": 0.58}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.653821587562561, "train_acc": 0.675, "val_loss": 0.6345487833023071, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.6111337244510651, "train_acc": 0.725, "val_loss": 0.573506236076355, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.5493861436843872, "train_acc": 0.77, "val_loss": 0.4991315007209778, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.4944599121809006, "train_acc": 0.795, "val_loss": 0.460259348154068, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4450604170560837, "train_acc": 0.805, "val_loss": 0.40147048234939575, "val_acc": 0.8}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.40586331486701965, "train_acc": 0.825, "val_loss": 0.27993708848953247, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.37263910472393036, "train_acc": 0.875, "val_loss": 0.21626944839954376, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.2802641987800598, "train_acc": 0.895, "val_loss": 0.210580974817276, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.28099460899829865, "train_acc": 0.9, "val_loss": 0.15407398343086243, "val_acc": 0.96}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6880980730056763, "final_val_loss": 0.6505634188652039, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.6542909145355225, "final_val_loss": 0.15407398343086243, "initial_val_acc": 0.58, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 10}, "improvement": 0.38, "first_improvement_epoch": 2}} |
40 | {"target_pattern": "palindrome", "degraded_accuracy": 0.56, "improved_accuracy": 0.92, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7385, "learning_rate": 0.03768603114736421, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.44519,
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0.704945
],
[
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0.632442
],
[
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],
[
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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[
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[
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[
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],
"network.2.bias": [
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],
"network.4.weight": [
[
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],
[
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],
[
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[
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],
[
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],
"network.4.bias": [
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],
"network.6.weight": [
[
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],
[
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],
[
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],
[
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[
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],
"network.6.bias": [
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],
"network.8.weight": [
[
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]
],
"network.8.bias": [
0.235066
]
}
## Activation Signature
### 0
fourier: [[37.036220, 39.186778, 152.924561], [26.748854, 27.444760, 85.144204], [27.415498, 28.737985, 53.400856], [16.949145, 19.282002, 20.179523], [23.166663, 24.923751, 141.022472]]
### 2
fourier: [[9.337201, 10.771681, 95.901678], [35.455727, 35.949089, 172.595240], [20.969285, 21.987913, 131.204498], [26.986649, 31.561314, 61.834374], [13.956569, 17.365839, 136.901042]]
### 4
fourier: [[17.608053, 18.441291, 76.361213], [16.431634, 17.203118, 65.183405], [16.334156, 17.999013, 92.998483], [11.177719, 11.331335, 64.777855], [10.676785, 11.149704, 88.826156]]
### 6
fourier: [[0.562682, 0.618352, 32.469625], [19.717419, 19.995485, 114.349927], [15.915924, 16.884482, 108.252633], [7.880496, 8.100847, 44.725219], [1.930933, 1.945480, 16.164830]]
### 8
fourier: [[14.314526, 14.900985, 58.337414]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.44519,
-0.09786,
0.008264,
0.233631,
0.704945
],
[
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0.427953,
0.632442
],
[
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0.123062,
0.379882,
-0.520626
],
[
0.528682,
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-0.254137,
0.182373,
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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[
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],
[
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],
[
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],
[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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[
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0.011603,
-0.185453,
0.119766
],
[
-0.180594,
0.452069,
-0.023878,
-0.432797,
0.207805
],
[
0.085771,
-0.314725,
-0.065762,
0.00865,
0.161807
],
[
0.00417,
-0.318865,
0.444376,
-0.282966,
0.00196
]
],
"network.4.bias": [
-0.268376,
-0.115439,
0.263809,
-0.117863,
-0.312257
],
"network.6.weight": [
[
0.171528,
-0.35608,
0.145199,
-0.345107,
-0.096482
],
[
0.598846,
0.172735,
0.368269,
0.296078,
0.173969
],
[
-0.12928,
0.415006,
0.689592,
-0.125656,
0.225347
],
[
0.042943,
0.30475,
0.125646,
0.311247,
-0.037803
],
[
0.437863,
-0.228762,
-0.259558,
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0.21308
]
],
"network.6.bias": [
-0.39091,
0.242449,
0.272005,
0.097786,
0.253784
],
"network.8.weight": [
[
0.02361,
-0.450164,
-0.325856,
-0.015534,
0.49196
]
],
"network.8.bias": [
0.235066
]
}
## Activation Signature
### 0
fourier: [[37.036220, 39.186778, 152.924561], [26.748854, 27.444760, 85.144204], [27.415498, 28.737985, 53.400856], [16.949145, 19.282002, 20.179523], [23.166663, 24.923751, 141.022472]]
### 2
fourier: [[9.337201, 10.771681, 95.901678], [35.455727, 35.949089, 172.595240], [20.969285, 21.987913, 131.204498], [26.986649, 31.561314, 61.834374], [13.956569, 17.365839, 136.901042]]
### 4
fourier: [[17.608053, 18.441291, 76.361213], [16.431634, 17.203118, 65.183405], [16.334156, 17.999013, 92.998483], [11.177719, 11.331335, 64.777855], [10.676785, 11.149704, 88.826156]]
### 6
fourier: [[0.562682, 0.618352, 32.469625], [19.717419, 19.995485, 114.349927], [15.915924, 16.884482, 108.252633], [7.880496, 8.100847, 44.725219], [1.930933, 1.945480, 16.164830]]
### 8
fourier: [[14.314526, 14.900985, 58.337414]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [37.0362202744271, 39.1867777287955, 152.92456100136042]}, "1": {"fourier": [26.74885360891981, 27.44476028182039, 85.14420403540134]}, "2": {"fourier": [27.41549833031281, 28.737984786493538, 53.40085592865944]}, "3": {"fourier": [16.949145492406032, 19.282002463196367, 20.17952318490667]}, "4": {"fourier": [23.16666300875615, 24.92375104663788, 141.02247182652354]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [9.337200554880738, 10.771680987872717, 95.90167754888535]}, "1": {"fourier": [35.45572670805845, 35.949088767192556, 172.59524020552635]}, "2": {"fourier": [20.96928518349181, 21.98791339685522, 131.20449789613485]}, "3": {"fourier": [26.986649153750765, 31.561313989565644, 61.83437440544367]}, "4": {"fourier": [13.956568878419422, 17.36583896260558, 136.90104195475578]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [17.608053386407253, 18.44129081144748, 76.36121289432049]}, "1": {"fourier": [16.43163449592395, 17.203117962941747, 65.18340485543013]}, "2": {"fourier": [16.33415649627578, 17.99901256456218, 92.99848346412182]}, "3": {"fourier": [11.17771940862124, 11.331335416867232, 64.77785459160805]}, "4": {"fourier": [10.676785007579964, 11.149703678448809, 88.82615622878075]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [0.5626815376341546, 0.6183515425544895, 32.469624906778336]}, "1": {"fourier": [19.717418802680893, 19.995485430548417, 114.34992709755898]}, "2": {"fourier": [15.915924147167251, 16.884481859784707, 108.25263340771198]}, "3": {"fourier": [7.8804964818863175, 8.100847307874156, 44.72521946579218]}, "4": {"fourier": [1.9309329939170317, 1.9454804139133444, 16.164830073714256]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [14.314526325162749, 14.900985322598359, 58.33741434663534]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.44519, -0.09786, 0.008264, 0.233631, 0.704945], [-0.15895, -0.247616, -0.081714, 0.427953, 0.632442], [-0.331087, 0.474568, 0.123062, 0.379882, -0.520626], [0.528682, -0.166129, -0.254137, 0.182373, -0.276954], [-0.195081, -0.242809, -0.315832, 0.010465, -0.2182]], "network.0.bias": [-0.064235, 0.068021, -0.289, 0.238605, 0.024712], "network.2.weight": [[-0.256541, 0.092051, -0.25534, -0.343807, 0.020394], [0.58517, 0.570143, -0.099446, 0.104457, -0.112667], [-0.543342, -0.14538, -0.354773, -0.257126, -0.564162], [-0.346875, -0.514714, 0.425186, -0.323521, -0.236336], [-0.429075, 0.047115, -0.332672, -0.414905, -0.291928]], "network.2.bias": [-0.325727, 0.312871, 0.101326, 0.235325, -0.32606], "network.4.weight": [[-0.361781, 0.527327, -0.160067, 0.467979, -0.209499], [-0.179615, 0.459539, 0.011603, -0.185453, 0.119766], [-0.180594, 0.452069, -0.023878, -0.432797, 0.207805], [0.085771, -0.314725, -0.065762, 0.00865, 0.161807], [0.00417, -0.318865, 0.444376, -0.282966, 0.00196]], "network.4.bias": [-0.268376, -0.115439, 0.263809, -0.117863, -0.312257], "network.6.weight": [[0.171528, -0.35608, 0.145199, -0.345107, -0.096482], [0.598846, 0.172735, 0.368269, 0.296078, 0.173969], [-0.12928, 0.415006, 0.689592, -0.125656, 0.225347], [0.042943, 0.30475, 0.125646, 0.311247, -0.037803], [0.437863, -0.228762, -0.259558, 0.450862, 0.21308]], "network.6.bias": [-0.39091, 0.242449, 0.272005, 0.097786, 0.253784], "network.8.weight": [[0.02361, -0.450164, -0.325856, -0.015534, 0.49196]], "network.8.bias": [0.235066]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6899383366107941, "train_acc": 0.55, "val_loss": 0.669598400592804, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6703197360038757, "train_acc": 0.55, "val_loss": 0.6223757266998291, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.652113676071167, "train_acc": 0.485, "val_loss": 0.5360884070396423, "val_acc": 0.7}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5597374439239502, "train_acc": 0.645, "val_loss": 0.45683661103248596, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4652033597230911, "train_acc": 0.85, "val_loss": 0.4104410409927368, "val_acc": 0.84}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.42626628279685974, "train_acc": 0.81, "val_loss": 0.36158761382102966, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.3633739650249481, "train_acc": 0.87, "val_loss": 0.35481053590774536, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.31915970146656036, "train_acc": 0.88, "val_loss": 0.30444031953811646, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.2700403928756714, "train_acc": 0.9, "val_loss": 0.3197271227836609, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.27662745863199234, "train_acc": 0.9, "val_loss": 0.4045076072216034, "val_acc": 0.82}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.28265486657619476, "train_acc": 0.885, "val_loss": 0.39986348152160645, "val_acc": 0.82}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.669598400592804, "final_val_loss": 0.6223757266998291, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.5360884070396423, "final_val_loss": 0.39986348152160645, "initial_val_acc": 0.7, "final_val_acc": 0.82, "best_val_acc": 0.92, "best_epoch": 3}, "improvement": 0.36, "first_improvement_epoch": 1}} |
41 | {"target_pattern": "ends_with", "degraded_accuracy": 0.74, "improved_accuracy": 0.92, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1221, "learning_rate": 0.0691798830068229, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.066832,
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-1.066031
],
[
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[
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[
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],
[
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],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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[
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[
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[
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]
],
"network.2.bias": [
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"network.4.weight": [
[
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],
[
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],
[
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[
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],
[
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]
],
"network.4.bias": [
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],
"network.6.weight": [
[
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],
[
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],
[
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],
[
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],
[
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],
"network.6.bias": [
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],
"network.8.weight": [
[
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]
],
"network.8.bias": [
-0.621241
]
}
## Activation Signature
### 0
fourier: [[41.317696, 50.152751, 129.340269], [25.687705, 31.423914, 105.231411], [33.422779, 38.438810, 145.738305], [19.137466, 20.272005, 71.042362], [39.952180, 43.526886, 188.972219]]
### 2
fourier: [[33.657199, 34.096988, 38.558745], [32.335231, 38.855474, 77.357151], [37.966026, 44.545814, 171.594852], [23.099568, 27.836967, 48.774585], [32.718654, 34.201451, 85.317621]]
### 4
fourier: [[4.966446, 5.653276, 39.659062], [45.349329, 51.917966, 100.904338], [23.011905, 26.642014, 37.266143], [33.495144, 34.495796, 34.962578], [49.532613, 57.859275, 186.217094]]
### 6
fourier: [[68.709332, 76.929835, 248.248183], [30.784128, 32.581219, 39.096124], [11.622406, 14.325995, 14.837829], [2.021880, 2.241169, 48.448313], [27.980079, 32.132540, 54.524731]]
### 8
fourier: [[57.553942, 62.375420, 237.871919]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.066832,
0.584676,
0.150473,
0.616734,
-1.066031
],
[
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-0.173453,
0.162935,
0.699435
],
[
-0.105998,
-0.517619,
0.076027,
-0.450382,
0.5054
],
[
0.468144,
-0.052618,
-0.180276,
-0.149016,
-0.326475
],
[
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]
],
"network.0.bias": [
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-0.360507,
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],
"network.2.weight": [
[
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],
[
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0.138167,
-0.153524
],
[
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0.49039,
0.47491
],
[
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-0.041742
],
[
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]
],
"network.2.bias": [
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0.545135
],
"network.4.weight": [
[
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],
[
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-0.103941,
0.764478
],
[
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-0.322289
],
[
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],
[
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]
],
"network.4.bias": [
-0.488033,
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],
"network.6.weight": [
[
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],
[
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-0.446833
],
[
-0.556216,
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-0.193032
],
[
-0.02782,
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],
[
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]
],
"network.6.bias": [
0.863663,
0.156,
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0.107984
],
"network.8.weight": [
[
-0.769176,
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]
],
"network.8.bias": [
-0.621241
]
}
## Activation Signature
### 0
fourier: [[41.317696, 50.152751, 129.340269], [25.687705, 31.423914, 105.231411], [33.422779, 38.438810, 145.738305], [19.137466, 20.272005, 71.042362], [39.952180, 43.526886, 188.972219]]
### 2
fourier: [[33.657199, 34.096988, 38.558745], [32.335231, 38.855474, 77.357151], [37.966026, 44.545814, 171.594852], [23.099568, 27.836967, 48.774585], [32.718654, 34.201451, 85.317621]]
### 4
fourier: [[4.966446, 5.653276, 39.659062], [45.349329, 51.917966, 100.904338], [23.011905, 26.642014, 37.266143], [33.495144, 34.495796, 34.962578], [49.532613, 57.859275, 186.217094]]
### 6
fourier: [[68.709332, 76.929835, 248.248183], [30.784128, 32.581219, 39.096124], [11.622406, 14.325995, 14.837829], [2.021880, 2.241169, 48.448313], [27.980079, 32.132540, 54.524731]]
### 8
fourier: [[57.553942, 62.375420, 237.871919]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [41.31769646051523, 50.1527508646883, 129.34026890993118]}, "1": {"fourier": [25.687704782556455, 31.423914491873575, 105.23141120374203]}, "2": {"fourier": [33.42277875952944, 38.43880999821665, 145.73830503225327]}, "3": {"fourier": [19.137466023074666, 20.27200470606604, 71.04236188530922]}, "4": {"fourier": [39.95217988394558, 43.52688628962849, 188.9722192287445]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [33.6571989278721, 34.09698751081241, 38.55874478564354]}, "1": {"fourier": [32.335230886008894, 38.8554740366508, 77.35715065151453]}, "2": {"fourier": [37.96602622645104, 44.54581448281665, 171.594852283597]}, "3": {"fourier": [23.09956815744627, 27.836967358750663, 48.77458507567644]}, "4": {"fourier": [32.718653728027284, 34.2014507932193, 85.31762143969536]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [4.966445804977677, 5.65327613857727, 39.659061551094055]}, "1": {"fourier": [45.349328706518435, 51.91796594810718, 100.90433765947819]}, "2": {"fourier": [23.011905181825973, 26.642013912116578, 37.26614257693291]}, "3": {"fourier": [33.49514371439374, 34.49579612237071, 34.962577783266426]}, "4": {"fourier": [49.53261292065479, 57.859274869283794, 186.21709375083447]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [68.70933151393017, 76.92983528557063, 248.24818271398544]}, "1": {"fourier": [30.784128450874704, 32.58121924627903, 39.09612365812063]}, "2": {"fourier": [11.622405516099809, 14.325995385820235, 14.83782938531303]}, "3": {"fourier": [2.0218796075115493, 2.2411688807222014, 48.44831269979477]}, "4": {"fourier": [27.980079467150155, 32.13254048977704, 54.52473074197769]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [57.55394234842161, 62.375420423452816, 237.8719188272953]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.066832, 0.584676, 0.150473, 0.616734, -1.066031], [-0.05695, 0.26204, -0.173453, 0.162935, 0.699435], [-0.105998, -0.517619, 0.076027, -0.450382, 0.5054], [0.468144, -0.052618, -0.180276, -0.149016, -0.326475], [0.300957, 0.402212, -0.033556, 0.187716, 0.821435]], "network.0.bias": [0.132772, -0.087104, -0.360507, -0.177272, -0.353307], "network.2.weight": [[0.648462, -0.391383, 0.061582, -0.278048, -0.351854], [0.259836, -0.962307, 0.242737, 0.138167, -0.153524], [-0.117796, 0.654794, 0.318886, 0.49039, 0.47491], [0.618058, -0.257347, 0.221065, -0.66401, -0.041742], [-0.44882, 0.117855, 0.020111, 0.567018, 0.510099]], "network.2.bias": [0.328269, 0.052057, 0.339243, -0.191072, 0.545135], "network.4.weight": [[-0.028015, 0.088251, -0.038036, 0.218807, -0.024666], [-0.332651, 0.297356, 0.48584, -0.103941, 0.764478], [-0.215315, 0.109312, -0.279379, 0.522364, -0.322289], [0.428206, 0.472505, -0.193338, 0.41551, -0.456964], [-0.143703, 0.103694, 0.462007, -0.086146, 1.039284]], "network.4.bias": [-0.488033, -0.237182, 0.230071, 0.122149, 0.307182], "network.6.weight": [[-0.467486, 0.487734, -0.173369, -0.650839, 0.795351], [-0.630781, -0.049378, 0.122474, 0.461118, -0.446833], [-0.556216, 0.139981, 0.556372, 0.467051, -0.193032], [-0.02782, 0.330564, -0.464359, -0.025394, -0.334503], [0.201699, -0.371498, -0.090282, 0.328898, -0.188763]], "network.6.bias": [0.863663, 0.156, -0.143293, -0.225616, 0.107984], "network.8.weight": [[-0.769176, 0.379719, 0.28433, 0.320935, 0.306849]], "network.8.bias": [-0.621241]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6879914402961731, "train_acc": 0.58, "val_loss": 0.6775883436203003, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6574699282646179, "train_acc": 0.6, "val_loss": 0.6172741651535034, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5266508311033249, "train_acc": 0.78, "val_loss": 0.5550997853279114, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4577248990535736, "train_acc": 0.78, "val_loss": 0.4036388397216797, "val_acc": 0.86}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.3834720253944397, "train_acc": 0.86, "val_loss": 0.423827588558197, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3319413661956787, "train_acc": 0.88, "val_loss": 0.3161788284778595, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.3396309167146683, "train_acc": 0.87, "val_loss": 0.29276683926582336, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.27866970002651215, "train_acc": 0.88, "val_loss": 0.36498337984085083, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.2944376766681671, "train_acc": 0.88, "val_loss": 0.3042227029800415, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.2435823678970337, "train_acc": 0.905, "val_loss": 0.22780853509902954, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.24502618610858917, "train_acc": 0.9, "val_loss": 0.2288864254951477, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.21110495179891586, "train_acc": 0.925, "val_loss": 0.2753043472766876, "val_acc": 0.92}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6775883436203003, "final_val_loss": 0.6172741651535034, "initial_val_acc": 0.56, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.5550997853279114, "final_val_loss": 0.2753043472766876, "initial_val_acc": 0.82, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 5}, "improvement": 0.18000000000000005, "first_improvement_epoch": 1}} |
42 | {"target_pattern": "palindrome", "degraded_accuracy": 0.48, "improved_accuracy": 0.9, "improvement": 0.42000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9124, "learning_rate": 0.05450317299859903, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.115173,
0.469267
],
[
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0.028124,
-0.020518,
0.683452
],
[
0.51605,
-0.019664,
0.000105,
0.090409,
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],
[
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0.000236,
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0.019263
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[
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0.261753
],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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[
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[
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[
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[
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],
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],
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[
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],
[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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"network.8.weight": [
[
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]
],
"network.8.bias": [
0.363127
]
}
## Activation Signature
### 0
fourier: [[25.451267, 27.874397, 110.715443], [30.717347, 33.044853, 111.095098], [24.992254, 25.076477, 35.611585], [22.273735, 22.350818, 24.747611], [28.445369, 28.731178, 34.052142], [31.843238, 37.179988, 129.116356]]
### 2
fourier: [[44.171364, 51.231415, 193.122852], [29.476254, 32.580987, 97.110334], [14.462670, 17.045094, 21.126499], [21.705633, 25.795161, 28.430690], [48.803137, 55.664685, 244.725224], [11.767913, 12.189006, 20.983608]]
### 4
fourier: [[39.450302, 46.259127, 185.840062], [14.230772, 14.314176, 147.897839], [97.530343, 110.900094, 423.025737], [9.999443, 10.284983, 11.194481], [13.253695, 14.515060, 34.126657], [47.240065, 52.935365, 100.291272]]
### 6
fourier: [[24.441666, 25.185746, 27.871743], [96.367281, 107.467287, 345.738230], [97.630390, 110.433156, 392.162005], [22.391372, 22.635876, 25.812691], [18.086253, 18.637649, 21.512916], [43.165603, 47.916579, 92.040224]]
### 8
fourier: [[140.532997, 149.797107, 439.148281]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.344344,
-0.015337,
0.018714,
0.115173,
0.469267
],
[
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0.028124,
-0.020518,
0.683452
],
[
0.51605,
-0.019664,
0.000105,
0.090409,
-0.727532
],
[
-0.344608,
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0.000236,
0.491557,
0.019263
],
[
-0.476075,
-0.59327,
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0.543041,
0.261753
],
[
0.566684,
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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0.248403
],
[
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],
[
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],
[
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],
[
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],
"network.2.bias": [
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],
"network.4.weight": [
[
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[
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[
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[
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[
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[
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],
"network.4.bias": [
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],
"network.6.weight": [
[
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[
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[
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[
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[
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[
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],
"network.6.bias": [
0.62548,
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],
"network.8.weight": [
[
0.508975,
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-0.289301,
0.5673,
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0.35194
]
],
"network.8.bias": [
0.363127
]
}
## Activation Signature
### 0
fourier: [[25.451267, 27.874397, 110.715443], [30.717347, 33.044853, 111.095098], [24.992254, 25.076477, 35.611585], [22.273735, 22.350818, 24.747611], [28.445369, 28.731178, 34.052142], [31.843238, 37.179988, 129.116356]]
### 2
fourier: [[44.171364, 51.231415, 193.122852], [29.476254, 32.580987, 97.110334], [14.462670, 17.045094, 21.126499], [21.705633, 25.795161, 28.430690], [48.803137, 55.664685, 244.725224], [11.767913, 12.189006, 20.983608]]
### 4
fourier: [[39.450302, 46.259127, 185.840062], [14.230772, 14.314176, 147.897839], [97.530343, 110.900094, 423.025737], [9.999443, 10.284983, 11.194481], [13.253695, 14.515060, 34.126657], [47.240065, 52.935365, 100.291272]]
### 6
fourier: [[24.441666, 25.185746, 27.871743], [96.367281, 107.467287, 345.738230], [97.630390, 110.433156, 392.162005], [22.391372, 22.635876, 25.812691], [18.086253, 18.637649, 21.512916], [43.165603, 47.916579, 92.040224]]
### 8
fourier: [[140.532997, 149.797107, 439.148281]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.451266725385885, 27.874397280882466, 110.71544347703457]}, "1": {"fourier": [30.717346733207183, 33.044853078982534, 111.09509803541005]}, "2": {"fourier": [24.992254193911347, 25.07647681565396, 35.611584946513176]}, "3": {"fourier": [22.27373540586211, 22.350817571628948, 24.74761116853794]}, "4": {"fourier": [28.445368740658196, 28.73117805589343, 34.05214180485998]}, "5": {"fourier": [31.84323829965525, 37.17998831662112, 129.1163560450077]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [44.17136372423247, 51.23141498154048, 193.12285174429417]}, "1": {"fourier": [29.476254313432868, 32.58098691942417, 97.11033406853676]}, "2": {"fourier": [14.46266982973778, 17.045094107301352, 21.126498818397522]}, "3": {"fourier": [21.705633198545463, 25.795160533033652, 28.430689841508865]}, "4": {"fourier": [48.803137077314425, 55.66468543381463, 244.72522390633821]}, "5": {"fourier": [11.767913094560296, 12.189006093064682, 20.983607590198517]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [39.45030184588349, 46.25912674440827, 185.84006249997765]}, "1": {"fourier": [14.230771821651226, 14.314176041779332, 147.89783883094788]}, "2": {"fourier": [97.53034320620849, 110.90009448068658, 423.0257373601198]}, "3": {"fourier": [9.999442905853025, 10.284982684551721, 11.194480823106268]}, "4": {"fourier": [13.253695452248525, 14.51506036748391, 34.126657128334045]}, "5": {"fourier": [47.24006501857269, 52.93536541921128, 100.29127198457718]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [24.441665565852695, 25.18574570191286, 27.871743261309458]}, "1": {"fourier": [96.36728141326776, 107.46728725343726, 345.73822988569736]}, "2": {"fourier": [97.6303903131582, 110.43315616253031, 392.1620047017932]}, "3": {"fourier": [22.3913722735035, 22.635875744831353, 25.812690842699634]}, "4": {"fourier": [18.08625303817217, 18.637649118416814, 21.51291627157759]}, "5": {"fourier": [43.16560309990372, 47.91657915563491, 92.04022397100925]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [140.53299689925433, 149.79710698198588, 439.14828073978424]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.344344, -0.015337, 0.018714, 0.115173, 0.469267], [0.244513, 0.025985, 0.028124, -0.020518, 0.683452], [0.51605, -0.019664, 0.000105, 0.090409, -0.727532], [-0.344608, -0.443107, 0.000236, 0.491557, 0.019263], [-0.476075, -0.59327, -0.024813, 0.543041, 0.261753], [0.566684, -0.238008, -0.043686, 0.261943, 0.522716]], "network.0.bias": [-0.035235, 0.025084, -0.298857, 0.024301, 0.304876, 0.047973], "network.2.weight": [[0.243718, 0.307271, 0.862535, 0.691282, 0.780333, 0.646418], [0.293002, 0.266659, 0.737522, 0.435341, 0.203665, 0.248403], [0.461176, 0.321868, 0.804984, -0.086055, 0.464628, -0.441901], [0.180476, 0.011725, 0.177941, 0.790394, 0.579658, 0.050051], [0.317725, 0.599924, 0.955615, 0.601753, 0.558448, 0.487968], [0.027826, 0.099546, -0.600409, 0.065355, -0.525387, 0.215261]], "network.2.bias": [-0.421648, -0.422188, -0.530722, -0.719057, 0.103291, -0.212038], "network.4.weight": [[0.248375, 0.290666, -0.19642, 0.508189, 0.37248, 0.083754], [0.138929, 0.35409, -0.071253, 0.212436, -0.642892, 0.534958], [0.783598, 0.714063, 0.501883, 0.262697, 0.776596, -0.401105], [0.291754, 0.159889, -0.076574, -0.134084, -0.093728, -0.111265], [0.129652, 0.400666, -0.023083, 0.674078, -0.343216, 0.429128], [-0.761617, -0.744436, -0.786889, -0.733763, 0.495461, -0.412935]], "network.4.bias": [-0.003692, -0.724839, -0.184543, -0.423491, -0.536272, 0.693983], "network.6.weight": [[0.233593, -0.275735, -0.292201, -0.360525, -0.232315, 0.301639], [0.085346, 0.37438, 0.858254, 0.105332, 0.391456, -1.008133], [0.122475, 0.452973, 0.910222, 0.194509, 0.246726, -0.31056], [-0.02648, -0.505788, -0.142837, -0.221604, -0.466022, 0.571215], [0.26436, -0.745353, -0.178636, -0.78895, -0.544504, 0.50882], [0.233085, -0.952228, -0.418276, -0.688508, -0.355329, 0.623885]], "network.6.bias": [0.62548, -0.027206, -0.10867, 0.451755, 0.163162, 0.267113], "network.8.weight": [[0.508975, -1.07878, -0.289301, 0.5673, 0.376282, 0.35194]], "network.8.bias": [0.363127]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7041590809822083, "train_acc": 0.47, "val_loss": 0.6790732741355896, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.632940262556076, "train_acc": 0.58, "val_loss": 0.6592801809310913, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.5668361186981201, "train_acc": 0.58, "val_loss": 0.5520657300949097, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.4831620156764984, "train_acc": 0.61, "val_loss": 0.44113314151763916, "val_acc": 0.86}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.3547043800354004, "train_acc": 0.895, "val_loss": 0.3759233057498932, "val_acc": 0.86}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.2955820709466934, "train_acc": 0.915, "val_loss": 0.33296310901641846, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.22483549267053604, "train_acc": 0.92, "val_loss": 0.3159198760986328, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.23501445353031158, "train_acc": 0.935, "val_loss": 1.2280099391937256, "val_acc": 0.72}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.5435025840997696, "train_acc": 0.835, "val_loss": 0.4231124818325043, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.2577323466539383, "train_acc": 0.92, "val_loss": 0.49690619111061096, "val_acc": 0.82}], "summary": {"total_epochs": 10, "degraded_epochs": 3, "improved_epochs": 7, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6790732741355896, "final_val_loss": 0.5520657300949097, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.44113314151763916, "final_val_loss": 0.49690619111061096, "initial_val_acc": 0.86, "final_val_acc": 0.82, "best_val_acc": 0.9, "best_epoch": 6}, "improvement": 0.42000000000000004, "first_improvement_epoch": 2}} |
43 | {"target_pattern": "palindrome", "degraded_accuracy": 0.48, "improved_accuracy": 0.86, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9386, "learning_rate": 0.08356802268451656, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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[
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[
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[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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],
[
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0.406612
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[
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[
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[
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[
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],
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[
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[
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[
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[
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"network.8.weight": [
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[
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"network.10.weight": [
[
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[
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],
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"network.12.weight": [
[
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],
"network.12.bias": [
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]
}
## Activation Signature
### 0
fourier: [[39.452256, 40.710835, 250.476574], [69.369172, 70.418681, 348.962967], [33.420304, 39.756030, 231.868524], [27.528710, 28.188409, 145.663560], [55.218769, 59.490631, 439.567614], [39.461821, 40.788807, 84.931100]]
### 2
fourier: [[11.487821, 12.486757, 99.022638], [34.669850, 37.130576, 236.704673], [20.291353, 22.346540, 35.409487], [22.477789, 24.594649, 152.808524], [46.937142, 53.674659, 116.372562], [10.868181, 11.119178, 81.267778]]
### 4
fourier: [[16.863605, 19.378982, 41.781234], [32.850775, 37.351850, 98.145957], [23.356473, 24.827198, 87.732652], [9.260249, 10.433566, 92.975884], [27.578039, 32.471436, 85.410844], [27.355254, 30.420335, 33.400943]]
### 6
fourier: [[24.771227, 30.357329, 74.339461], [26.402655, 27.265949, 32.696435], [54.422598, 65.118719, 148.050006], [10.599849, 11.053409, 29.500032], [9.369997, 10.612271, 19.135404], [36.531666, 42.575572, 56.205928]]
### 8
fourier: [[21.522995, 24.891176, 49.224874], [32.113383, 38.625993, 173.623352], [60.974024, 69.959478, 72.025025], [25.270074, 25.403190, 343.417964], [35.667290, 40.365708, 230.852879], [60.573064, 69.164289, 137.708739]]
### 10
fourier: [[18.487899, 22.563648, 43.584589], [6.585199, 7.039032, 9.516180], [27.548688, 30.782076, 36.670935], [51.289273, 57.815548, 131.920109], [24.947102, 26.717610, 41.109628], [33.782224, 35.976330, 38.306833]]
### 12
fourier: [[52.373113, 57.373298, 115.180072]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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],
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0.545793,
0.947911
],
[
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0.042564
],
[
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],
[
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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[
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[
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0.437934,
-0.553825,
-0.7898,
0.669797
],
[
0.121234,
-0.270267,
-0.104706,
0.021012,
-0.303067,
-0.963503
],
[
1.231117,
0.594777,
-0.854404,
0.570653,
0.428274,
-0.527666
],
[
0.025109,
0.085126,
0.475436,
-0.522618,
0.005138,
0.434514
]
],
"network.2.bias": [
0.046479,
-0.848795,
-0.219426,
0.56128,
-0.271624,
0.008847
],
"network.4.weight": [
[
0.56439,
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-0.445965
],
[
-0.009488,
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0.406612
],
[
-0.019868,
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],
[
0.197911,
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],
[
-0.062067,
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],
[
0.520554,
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-0.554247,
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]
],
"network.4.bias": [
0.87274,
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-0.575927,
0.319294,
-0.238813,
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],
"network.6.weight": [
[
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],
[
-0.801276,
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],
[
-0.758165,
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[
0.236737,
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[
-0.067078,
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[
0.263231,
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],
"network.6.bias": [
-0.284003,
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],
"network.8.weight": [
[
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],
[
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[
-0.231619,
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[
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[
0.162925,
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[
0.230121,
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],
"network.8.bias": [
0.250472,
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-1.243418,
-1.161685,
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],
"network.10.weight": [
[
-1.013827,
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],
[
-0.392681,
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[
0.789058,
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[
0.700511,
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[
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[
0.17495,
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],
"network.10.bias": [
-0.384963,
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],
"network.12.weight": [
[
0.470015,
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-0.190517,
-0.566392,
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]
],
"network.12.bias": [
0.264643
]
}
## Activation Signature
### 0
fourier: [[39.452256, 40.710835, 250.476574], [69.369172, 70.418681, 348.962967], [33.420304, 39.756030, 231.868524], [27.528710, 28.188409, 145.663560], [55.218769, 59.490631, 439.567614], [39.461821, 40.788807, 84.931100]]
### 2
fourier: [[11.487821, 12.486757, 99.022638], [34.669850, 37.130576, 236.704673], [20.291353, 22.346540, 35.409487], [22.477789, 24.594649, 152.808524], [46.937142, 53.674659, 116.372562], [10.868181, 11.119178, 81.267778]]
### 4
fourier: [[16.863605, 19.378982, 41.781234], [32.850775, 37.351850, 98.145957], [23.356473, 24.827198, 87.732652], [9.260249, 10.433566, 92.975884], [27.578039, 32.471436, 85.410844], [27.355254, 30.420335, 33.400943]]
### 6
fourier: [[24.771227, 30.357329, 74.339461], [26.402655, 27.265949, 32.696435], [54.422598, 65.118719, 148.050006], [10.599849, 11.053409, 29.500032], [9.369997, 10.612271, 19.135404], [36.531666, 42.575572, 56.205928]]
### 8
fourier: [[21.522995, 24.891176, 49.224874], [32.113383, 38.625993, 173.623352], [60.974024, 69.959478, 72.025025], [25.270074, 25.403190, 343.417964], [35.667290, 40.365708, 230.852879], [60.573064, 69.164289, 137.708739]]
### 10
fourier: [[18.487899, 22.563648, 43.584589], [6.585199, 7.039032, 9.516180], [27.548688, 30.782076, 36.670935], [51.289273, 57.815548, 131.920109], [24.947102, 26.717610, 41.109628], [33.782224, 35.976330, 38.306833]]
### 12
fourier: [[52.373113, 57.373298, 115.180072]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [39.452256135936395, 40.71083519452164, 250.47657418996096]}, "1": {"fourier": [69.36917176438084, 70.41868063406443, 348.96296741068363]}, "2": {"fourier": [33.420304167550405, 39.75603042619246, 231.86852402985096]}, "3": {"fourier": [27.528709786054748, 28.188408827090228, 145.66356046497822]}, "4": {"fourier": [55.218768687260294, 59.49063103487987, 439.56761384010315]}, "5": {"fourier": [39.461820532702504, 40.788806703091886, 84.93110033869743]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [11.48782085264192, 12.486757166431817, 99.02263769507408]}, "1": {"fourier": [34.669849745945136, 37.13057594761178, 236.70467329025269]}, "2": {"fourier": [20.291352565514416, 22.346540044779807, 35.409487433731556]}, "3": {"fourier": [22.477788920090738, 24.594648597148886, 152.80852416157722]}, "4": {"fourier": [46.93714223435809, 53.674658676409805, 116.37256236374378]}, "5": {"fourier": [10.868181440811098, 11.119177842815215, 81.26777777075768]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [16.863604635914413, 19.37898218295869, 41.781234085559845]}, "1": {"fourier": [32.85077525189222, 37.35185040118393, 98.14595682919025]}, "2": {"fourier": [23.35647335036886, 24.827198290965654, 87.732651501894]}, "3": {"fourier": [9.260249247038962, 10.433565538965494, 92.97588416934013]}, "4": {"fourier": [27.57803946647809, 32.4714361825095, 85.41084437072277]}, "5": {"fourier": [27.35525358383609, 30.420334873706807, 33.40094271284166]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [24.771227085276134, 30.357328853443484, 74.33946073055267]}, "1": {"fourier": [26.40265453149833, 27.265948684352672, 32.69643491077521]}, "2": {"fourier": [54.42259776468724, 65.11871876062261, 148.05000621080399]}, "3": {"fourier": [10.599848918137193, 11.053408910593397, 29.50003245100379]}, "4": {"fourier": [9.369996815940802, 10.612270694274, 19.135404340922832]}, "5": {"fourier": [36.5316659718068, 42.57557171496463, 56.205928057432175]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [21.522995031376475, 24.89117622064332, 49.224874049425125]}, "1": {"fourier": [32.11338260003852, 38.62599317836582, 173.62335214018822]}, "2": {"fourier": [60.974024434774655, 69.95947806179625, 72.02502506971359]}, "3": {"fourier": [25.270074020825607, 25.403189876832933, 343.417964220047]}, "4": {"fourier": [35.66728978290307, 40.365708346473646, 230.85287880897522]}, "5": {"fourier": [60.57306365244031, 69.16428902447414, 137.70873939990997]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [18.487898773476076, 22.563648363556464, 43.58458885550499]}, "1": {"fourier": [6.585199152398171, 7.039032194830691, 9.516179629095799]}, "2": {"fourier": [27.548688016570566, 30.782075936994755, 36.6709353774786]}, "3": {"fourier": [51.28927275999756, 57.81554759600817, 131.92010855674744]}, "4": {"fourier": [24.94710239890972, 26.717610101534877, 41.109628438949585]}, "5": {"fourier": [33.782224008539714, 35.97632959485054, 38.30683269219026]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [52.37311270562692, 57.37329768163603, 115.18007232248783]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.360115, -0.487204, 0.011715, -0.451871, -0.388783], [0.919996, -0.080447, 0.332858, 0.545793, 0.947911], [0.066181, -0.265378, -0.964028, -0.157624, 0.042564], [-0.080422, -0.385197, -0.190783, 0.070579, -0.532428], [-0.383245, -0.236043, -1.083098, -0.41957, -0.341361], [-0.427889, -0.115716, 0.738016, 0.168691, -0.864478]], "network.0.bias": [-0.023095, -0.155743, 0.124172, 0.087345, -0.393806, 0.849829], "network.2.weight": [[-0.522377, 0.099752, 0.203392, -0.302673, -0.831321, 0.487335], [0.108806, -0.488123, 0.923629, 0.092228, -0.529521, 0.097462], [-0.197858, -0.07301, 0.437934, -0.553825, -0.7898, 0.669797], [0.121234, -0.270267, -0.104706, 0.021012, -0.303067, -0.963503], [1.231117, 0.594777, -0.854404, 0.570653, 0.428274, -0.527666], [0.025109, 0.085126, 0.475436, -0.522618, 0.005138, 0.434514]], "network.2.bias": [0.046479, -0.848795, -0.219426, 0.56128, -0.271624, 0.008847], "network.4.weight": [[0.56439, -0.674593, -0.107368, -0.052012, -0.391368, -0.445965], [-0.009488, 0.47943, -0.687333, -0.426549, 0.603979, 0.406612], [-0.019868, 0.949693, 0.018713, 0.547739, -0.484123, 0.556835], [0.197911, 0.141997, 0.238526, 0.087368, 0.065185, 0.39158], [-0.062067, 0.996409, -0.228285, -0.573663, 0.618391, 0.586477], [0.520554, -0.690661, 0.266657, 0.072238, -0.554247, -0.062725]], "network.4.bias": [0.87274, 0.243433, -0.575927, 0.319294, -0.238813, 0.292011], "network.6.weight": [[-0.943907, 0.216651, 0.431608, -0.001424, 0.114743, -0.661223], [-0.801276, 0.288814, 0.399103, -0.155935, 0.300925, -0.325424], [-0.758165, 0.76061, 0.670397, 0.27439, 0.831936, -0.441056], [0.236737, -0.150629, 0.048595, -0.539481, -0.029605, 0.25007], [-0.067078, -0.401716, -0.430712, 0.056788, 0.043921, -0.07731], [0.263231, -0.45489, -0.933682, 0.533514, -0.487217, 0.634996]], "network.6.bias": [-0.284003, -0.076333, 0.403176, 0.085005, 0.228152, 0.605796], "network.8.weight": [[-0.06391, 0.018754, 0.315885, 0.044735, -0.301782, -0.243779], [0.301707, 0.2345, 0.073569, 0.141521, -0.774185, -1.117628], [-0.231619, -0.660113, -0.734525, 0.324495, 0.033918, 0.521919], [-0.257718, -0.248177, -0.678517, -0.331958, -0.501265, -1.047346], [0.162925, -0.253827, -0.63861, 0.71175, 0.011103, -0.105218], [0.230121, 0.566642, 0.766431, -0.706889, -0.358296, -0.408225]], "network.8.bias": [0.250472, -0.940424, 0.288187, -1.243418, -1.161685, 0.272391], "network.10.weight": [[-1.013827, 0.208842, 0.454001, 0.216484, 0.500968, 0.105877], [-0.392681, -0.260206, 0.343143, 0.09774, -0.107645, 0.097296], [0.789058, -0.227258, -0.220152, -0.252535, 0.132162, 0.165164], [0.700511, -0.755559, -0.669083, -0.250191, 0.543178, 0.51811], [-0.347801, 0.749713, 0.071981, 0.710228, 0.9585, 0.536168], [0.17495, -0.459907, -0.476093, -0.891396, -0.116215, 0.446254]], "network.10.bias": [-0.384963, -0.265635, -0.194111, 0.67481, -0.329496, -0.152611], "network.12.weight": [[0.470015, 0.385792, -0.190517, -0.566392, -0.458305, -0.314995]], "network.12.bias": [0.264643]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7139422595500946, "train_acc": 0.425, "val_loss": 0.6979189515113831, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6939050257205963, "train_acc": 0.575, "val_loss": 0.7200202941894531, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6750213801860809, "train_acc": 0.575, "val_loss": 0.7078514099121094, "val_acc": 0.48}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6735662221908569, "train_acc": 0.575, "val_loss": 0.654421865940094, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5568504333496094, "train_acc": 0.64, "val_loss": 0.47597944736480713, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5000993609428406, "train_acc": 0.825, "val_loss": 0.4546869695186615, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.4036644846200943, "train_acc": 0.835, "val_loss": 0.45841971039772034, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.4786577671766281, "train_acc": 0.78, "val_loss": 0.47186774015426636, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.42792636156082153, "train_acc": 0.79, "val_loss": 0.3761812150478363, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.4654921591281891, "train_acc": 0.78, "val_loss": 0.36126449704170227, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.41068798303604126, "train_acc": 0.815, "val_loss": 0.3938189744949341, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.4133124351501465, "train_acc": 0.795, "val_loss": 0.40010887384414673, "val_acc": 0.82}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.39560675621032715, "train_acc": 0.8, "val_loss": 0.3959343433380127, "val_acc": 0.82}], "summary": {"total_epochs": 13, "degraded_epochs": 4, "improved_epochs": 9, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6979189515113831, "final_val_loss": 0.654421865940094, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.47597944736480713, "final_val_loss": 0.3959343433380127, "initial_val_acc": 0.76, "final_val_acc": 0.82, "best_val_acc": 0.86, "best_epoch": 8}, "improvement": 0.38, "first_improvement_epoch": 3}} |
44 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.58, "improved_accuracy": 0.94, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8890, "learning_rate": 0.024940936964749232, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
[
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[
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0.447101
],
[
-0.243412,
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],
[
-0.593176,
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],
[
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0.530572
]
],
"network.0.bias": [
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],
"network.2.weight": [
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}
## Activation Signature
### 0
fourier: [[16.031913, 17.291426, 61.918333], [20.921012, 24.520480, 161.897777], [25.292953, 28.726703, 39.007280], [24.696309, 26.437590, 200.263957], [22.878858, 30.759865, 50.316047], [18.073702, 18.077971, 22.514500]]
### 2
fourier: [[6.611483, 8.285912, 37.151529], [21.716629, 21.750768, 162.989258], [17.984863, 20.265741, 108.212019], [21.650236, 21.755866, 144.391804], [6.433581, 7.234363, 54.871558], [10.903825, 12.795256, 38.204951]]
### 4
fourier: [[41.417891, 43.552553, 304.001600], [21.279136, 22.322224, 134.986382], [36.755024, 38.121684, 243.953946], [14.745153, 16.031955, 95.480339], [6.548745, 6.769228, 11.553020], [32.791447, 35.266757, 175.090635]]
### 6
fourier: [[34.375274, 35.750203, 249.196305], [10.580560, 10.684842, 70.249488], [75.547783, 78.712899, 423.524454], [4.777948, 5.021957, 11.430982], [30.700484, 32.588225, 220.828406], [54.886502, 57.001477, 337.634572]]
### 8
fourier: [[15.283080, 15.310356, 103.078024], [68.396148, 70.534357, 361.789998], [3.713255, 3.781139, 27.750719], [57.156517, 59.445328, 334.723677], [15.654221, 16.113449, 143.811652], [49.895493, 51.387185, 280.684116]]
### 10
fourier: [[32.851483, 34.081955, 203.195739], [99.186845, 103.126904, 553.507894], [4.548052, 4.706975, 37.259290], [4.591871, 4.662779, 16.851827], [2.906646, 3.153216, 40.654995], [7.438614, 7.836874, 73.341522]]
### 12
fourier: [[52.551575, 54.197646, 222.652914]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[16.031913, 17.291426, 61.918333], [20.921012, 24.520480, 161.897777], [25.292953, 28.726703, 39.007280], [24.696309, 26.437590, 200.263957], [22.878858, 30.759865, 50.316047], [18.073702, 18.077971, 22.514500]]
### 2
fourier: [[6.611483, 8.285912, 37.151529], [21.716629, 21.750768, 162.989258], [17.984863, 20.265741, 108.212019], [21.650236, 21.755866, 144.391804], [6.433581, 7.234363, 54.871558], [10.903825, 12.795256, 38.204951]]
### 4
fourier: [[41.417891, 43.552553, 304.001600], [21.279136, 22.322224, 134.986382], [36.755024, 38.121684, 243.953946], [14.745153, 16.031955, 95.480339], [6.548745, 6.769228, 11.553020], [32.791447, 35.266757, 175.090635]]
### 6
fourier: [[34.375274, 35.750203, 249.196305], [10.580560, 10.684842, 70.249488], [75.547783, 78.712899, 423.524454], [4.777948, 5.021957, 11.430982], [30.700484, 32.588225, 220.828406], [54.886502, 57.001477, 337.634572]]
### 8
fourier: [[15.283080, 15.310356, 103.078024], [68.396148, 70.534357, 361.789998], [3.713255, 3.781139, 27.750719], [57.156517, 59.445328, 334.723677], [15.654221, 16.113449, 143.811652], [49.895493, 51.387185, 280.684116]]
### 10
fourier: [[32.851483, 34.081955, 203.195739], [99.186845, 103.126904, 553.507894], [4.548052, 4.706975, 37.259290], [4.591871, 4.662779, 16.851827], [2.906646, 3.153216, 40.654995], [7.438614, 7.836874, 73.341522]]
### 12
fourier: [[52.551575, 54.197646, 222.652914]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [16.03191345716173, 17.291425551787135, 61.918332695961]}, "1": {"fourier": [20.921012457365126, 24.52047963869048, 161.89777743816376]}, "2": {"fourier": [25.29295269132728, 28.7267029777276, 39.00728043913841]}, "3": {"fourier": [24.696309495748814, 26.437589626350395, 200.26395678520203]}, "4": {"fourier": [22.878858143853304, 30.75986463497511, 50.31604650616646]}, "5": {"fourier": [18.07370227376716, 18.077971156667, 22.51450014859438]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [6.6114828673400705, 8.285911788874886, 37.15152880176902]}, "1": {"fourier": [21.716628502719686, 21.750767970790527, 162.98925837874413]}, "2": {"fourier": [17.984863374209954, 20.265740870700586, 108.21201868355274]}, "3": {"fourier": [21.65023628927169, 21.755865757272424, 144.39180443063378]}, "4": {"fourier": 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{"fourier": [75.54778315760115, 78.71289945380425, 423.52445352077484]}, "3": {"fourier": [4.7779484552503515, 5.0219567058782815, 11.430982142686844]}, "4": {"fourier": [30.70048437849812, 32.588225214729576, 220.82840594649315]}, "5": {"fourier": [54.88650183263962, 57.00147664804662, 337.63457173109055]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [15.283079691511487, 15.31035604411272, 103.0780238956213]}, "1": {"fourier": [68.3961482563934, 70.53435713998839, 361.7899978607893]}, "2": {"fourier": [3.713255352570653, 3.781139322817137, 27.75071942061186]}, "3": {"fourier": [57.15651739043663, 59.445328094365, 334.723677162081]}, "4": {"fourier": [15.654221091305745, 16.113448987889043, 143.81165248155594]}, "5": {"fourier": [49.895492708371066, 51.387184813173754, 280.6841155849397]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [32.851483348353426, 34.08195523669182, 203.19573904573917]}, "1": {"fourier": [99.18684540486605, 103.12690417423575, 553.5078937113285]}, "2": {"fourier": [4.548051721930216, 4.706975483129173, 37.25928966701031]}, "3": {"fourier": [4.591871388985271, 4.662779092914109, 16.851827457547188]}, "4": {"fourier": [2.9066460729912325, 3.1532155805392565, 40.65499484539032]}, "5": {"fourier": [7.438613596763981, 7.836874294860095, 73.34152239561081]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [52.551574889385634, 54.197645840219245, 222.65291441231966]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.355458, -0.115937, 0.384801, 0.018808, 0.073311], [-0.258201, 0.172004, -0.400283, -0.174749, -0.148629], [-0.425315, 0.032609, -0.179128, 0.391045, 0.447101], [-0.243412, -0.184068, 0.089709, -0.411058, -0.291213], [-0.593176, 0.14725, 0.027479, 0.246586, -0.107182], [-0.241492, 0.031441, -0.080168, -0.260798, 0.530572]], "network.0.bias": [0.407034, -0.396781, -0.112547, -0.53357, 0.57492, 0.065427], "network.2.weight": [[0.314351, -0.01305, -0.080972, 0.080843, 0.128213, 0.497217], [0.69155, 0.455601, 0.408486, 0.012752, 0.713072, 0.26006], [0.256467, -0.04099, 0.668213, -0.257033, 0.277748, 0.355353], [0.539042, -0.036474, 0.41474, 0.253559, 0.687169, 0.569115], [-0.027537, 0.348512, -0.281783, 0.137982, 0.092078, -0.252865], 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0.449086, 0.550476, -0.102912, -0.424892, 0.53658]], "network.6.bias": [-0.286294, 0.006503, -0.487805, 0.491985, -0.201882, 0.089531], "network.8.weight": [[-0.033688, -0.167921, 0.06188, 0.392548, 0.253784, -0.336089], [0.32842, -0.403077, 0.679355, -0.53378, -0.112339, 0.299255], [0.348277, -0.17135, -0.198359, 0.099544, -0.094617, 0.205367], [-0.04037, -0.314367, 0.390575, -0.058199, -0.254044, 0.513361], [-0.098257, -0.163204, -0.058839, -0.077925, -0.383689, 0.359018], [-0.292501, -0.26428, 0.452204, -0.422768, 0.053336, 0.274361]], "network.8.bias": [-0.252953, -0.244059, -0.151064, -0.059133, 0.546293, 0.01108], "network.10.weight": [[0.246586, -0.234395, 0.157002, 0.039836, -0.309397, -0.301392], [-0.214676, 0.639515, -0.114492, 0.621403, 0.115618, 0.403623], [0.054172, 0.014217, -0.103466, -0.016367, 0.409613, -0.223087], [0.346692, 0.20379, -0.010199, -0.176521, 0.273956, -0.250211], [0.013331, -0.224053, 0.014148, -0.007732, 0.49982, 0.092475], [0.304542, -0.347307, 0.108237, 0.268554, -0.193642, 0.066198]], "network.10.bias": [-0.004117, -0.241097, 0.463871, 0.360173, 0.308705, -0.292984], "network.12.weight": [[0.218058, -0.486544, 0.517375, 0.326727, 0.504022, 0.116464]], "network.12.bias": [0.007991]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6983940899372101, "train_acc": 0.445, "val_loss": 0.6842834949493408, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6819095015525818, "train_acc": 0.555, "val_loss": 0.6789032816886902, "val_acc": 0.58}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6887918710708618, "train_acc": 0.555, "val_loss": 0.6685178875923157, "val_acc": 0.58}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6714825332164764, "train_acc": 0.555, "val_loss": 0.6404300928115845, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6451559960842133, "train_acc": 0.48, "val_loss": 0.5715429186820984, "val_acc": 0.58}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5649116039276123, "train_acc": 0.48, "val_loss": 0.4622061252593994, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.45433464646339417, "train_acc": 0.81, "val_loss": 0.3606742024421692, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.37603385746479034, "train_acc": 0.905, "val_loss": 0.2900390923023224, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.30701689422130585, "train_acc": 0.935, "val_loss": 0.24709652364253998, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.2554938644170761, "train_acc": 0.955, "val_loss": 0.23540298640727997, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.22333815693855286, "train_acc": 0.96, "val_loss": 0.22407524287700653, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.16412612795829773, "train_acc": 0.955, "val_loss": 0.22351700067520142, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.15929009765386581, "train_acc": 0.955, "val_loss": 0.23677249252796173, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.15069181472063065, "train_acc": 0.96, "val_loss": 0.259005606174469, "val_acc": 0.92}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6842834949493408, "final_val_loss": 0.6404300928115845, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.5715429186820984, "final_val_loss": 0.259005606174469, "initial_val_acc": 0.58, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 8}, "improvement": 0.36, "first_improvement_epoch": 3}} |
45 | {"target_pattern": "starts_with", "degraded_accuracy": 0.48, "improved_accuracy": 0.82, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1794, "learning_rate": 0.045307675361688976, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[31.533381, 32.497899, 123.277084], [28.125080, 40.810212, 125.837834], [25.463902, 30.471551, 136.114655], [32.407774, 36.542438, 155.509474], [38.338294, 42.329422, 221.768994], [27.475515, 29.762574, 29.932120], [32.237556, 34.785649, 35.283361]]
### 2
fourier: [[23.732409, 25.665270, 105.551762], [39.187869, 41.200985, 182.382830], [15.710090, 18.117198, 99.245936], [35.974689, 43.501196, 99.934645], [17.645783, 19.374987, 61.045683], [10.389118, 11.569198, 14.460917], [17.484258, 18.009763, 19.389536]]
### 4
fourier: [[27.063054, 28.186194, 141.598311], [45.489616, 46.774427, 234.217737], [16.935926, 17.039573, 85.058375], [9.363822, 9.951599, 16.085364], [31.456062, 31.757502, 62.823740], [11.990419, 12.415259, 16.802676], [27.085172, 27.366237, 96.135772]]
### 6
fourier: [[5.255506, 6.573803, 9.226342], [4.866698, 6.739044, 10.123280], [17.418879, 19.362425, 20.758957], [8.092554, 11.268561, 21.029657], [8.156697, 9.081066, 19.065728], [12.094996, 12.666935, 13.874819], [10.753901, 11.773443, 31.854486]]
### 8
fourier: [[5.501557, 6.420720, 6.959048], [19.799558, 22.163903, 25.648929], [12.325629, 15.568575, 17.753314], [19.184891, 20.526212, 22.092039], [8.678514, 10.547201, 22.075979], [10.088757, 11.368656, 35.664862], [19.901282, 22.256386, 25.350208]]
### 10
fourier: [[24.900825, 29.040626, 119.733716]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.290413,
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}
## Activation Signature
### 0
fourier: [[31.533381, 32.497899, 123.277084], [28.125080, 40.810212, 125.837834], [25.463902, 30.471551, 136.114655], [32.407774, 36.542438, 155.509474], [38.338294, 42.329422, 221.768994], [27.475515, 29.762574, 29.932120], [32.237556, 34.785649, 35.283361]]
### 2
fourier: [[23.732409, 25.665270, 105.551762], [39.187869, 41.200985, 182.382830], [15.710090, 18.117198, 99.245936], [35.974689, 43.501196, 99.934645], [17.645783, 19.374987, 61.045683], [10.389118, 11.569198, 14.460917], [17.484258, 18.009763, 19.389536]]
### 4
fourier: [[27.063054, 28.186194, 141.598311], [45.489616, 46.774427, 234.217737], [16.935926, 17.039573, 85.058375], [9.363822, 9.951599, 16.085364], [31.456062, 31.757502, 62.823740], [11.990419, 12.415259, 16.802676], [27.085172, 27.366237, 96.135772]]
### 6
fourier: [[5.255506, 6.573803, 9.226342], [4.866698, 6.739044, 10.123280], [17.418879, 19.362425, 20.758957], [8.092554, 11.268561, 21.029657], [8.156697, 9.081066, 19.065728], [12.094996, 12.666935, 13.874819], [10.753901, 11.773443, 31.854486]]
### 8
fourier: [[5.501557, 6.420720, 6.959048], [19.799558, 22.163903, 25.648929], [12.325629, 15.568575, 17.753314], [19.184891, 20.526212, 22.092039], [8.678514, 10.547201, 22.075979], [10.088757, 11.368656, 35.664862], [19.901282, 22.256386, 25.350208]]
### 10
fourier: [[24.900825, 29.040626, 119.733716]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [31.53338052411569, 32.49789862467508, 123.27708375453949]}, "1": {"fourier": [28.125080388384777, 40.81021240135129, 125.83783435076475]}, "2": {"fourier": [25.463902288425157, 30.471550669004756, 136.1146550923586]}, "3": {"fourier": [32.40777388042653, 36.5424381927587, 155.50947357341647]}, "4": {"fourier": [38.33829411409139, 42.32942245305255, 221.7689939290285]}, "5": {"fourier": [27.4755147112585, 29.762573662897317, 29.932120007271834]}, "6": {"fourier": [32.23755566404618, 34.78564850854259, 35.28336115570497]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [23.73240881059129, 25.665270169631544, 105.55176167562604]}, "1": {"fourier": [39.18786914770898, 41.20098543485371, 182.38283030688763]}, "2": {"fourier": [15.71008952264538, 18.117197916606695, 99.24593628570437]}, "3": {"fourier": [35.974688523597514, 43.501196064869795, 99.934645190835]}, "4": {"fourier": [17.645783474629898, 19.37498692167562, 61.04568312317133]}, "5": {"fourier": [10.389118108869416, 11.569197823963803, 14.460916720330715]}, "6": {"fourier": [17.48425774433631, 18.009763387790333, 19.389536434671843]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [27.06305407237068, 28.186194365892344, 141.59831132367253]}, "1": {"fourier": [45.48961599866647, 46.774427015545534, 234.21773654222488]}, "2": {"fourier": [16.93592551546145, 17.039573020378477, 85.05837496370077]}, "3": {"fourier": [9.363821884750296, 9.95159908953865, 16.085364140570164]}, "4": {"fourier": [31.45606166210415, 31.757502489114824, 62.82374033331871]}, "5": {"fourier": [11.99041906251544, 12.41525913922311, 16.802675697603128]}, "6": {"fourier": [27.08517248857847, 27.366237096524426, 96.13577177375555]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [5.255505669039506, 6.573803134029066, 9.22634158283472]}, "1": {"fourier": [4.866697808724787, 6.7390435681142655, 10.123279795050621]}, "2": {"fourier": [17.418878951544283, 19.362424523369825, 20.758956830179404]}, "3": {"fourier": [8.092553693057054, 11.26856050636786, 21.029657281935215]}, "4": {"fourier": [8.156696534226276, 9.081065701161055, 19.065727949142456]}, "5": {"fourier": [12.094995900988579, 12.666934683125918, 13.874819271745254]}, "6": {"fourier": [10.75390131181341, 11.773443301132984, 31.854485508054495]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [5.501556858128683, 6.420720110056549, 6.959047521614318]}, "1": {"fourier": [19.799557961036264, 22.163903469501435, 25.64892938733101]}, "2": {"fourier": [12.325628503742161, 15.568574926157412, 17.753314203406738]}, "3": {"fourier": [19.184891253709793, 20.526211860339334, 22.092039357472828]}, "4": {"fourier": [8.678514079540145, 10.547200566115416, 22.07597928494215]}, "5": {"fourier": [10.088756934589968, 11.36865568708348, 35.664862006902695]}, "6": {"fourier": [19.90128152644725, 22.25638624216203, 25.35020825266838]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [24.90082547413614, 29.040626458342157, 119.73371629416943]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": 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"epoch": 8, "global_epoch": 11, "train_loss": 0.4864731431007385, "train_acc": 0.765, "val_loss": 0.4436739981174469, "val_acc": 0.82}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.48630475997924805, "train_acc": 0.735, "val_loss": 0.4421273171901703, "val_acc": 0.82}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.7518340945243835, "final_val_loss": 0.694712221622467, "initial_val_acc": 0.44, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6669801473617554, "final_val_loss": 0.4421273171901703, "initial_val_acc": 0.58, "final_val_acc": 0.82, "best_val_acc": 0.82, "best_epoch": 11}, "improvement": 0.33999999999999997, "first_improvement_epoch": 2}} |
46 | {"target_pattern": "alternating", "degraded_accuracy": 0.46, "improved_accuracy": 0.98, "improvement": 0.52, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3911, "learning_rate": 0.03942708661657638, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.572285
]
}
## Activation Signature
### 0
fourier: [[21.407213, 24.474679, 62.315266], [28.254216, 38.607056, 157.994976], [26.081038, 29.691720, 203.942072], [26.575432, 30.993106, 44.417243], [33.274087, 35.022529, 116.039277], [33.883848, 36.408500, 42.607798], [56.702075, 59.430071, 213.986375]]
### 2
fourier: [[37.460414, 37.598792, 208.694518], [26.092581, 31.763207, 61.450620], [15.526047, 19.273957, 163.672825], [27.168089, 29.584595, 59.301086], [29.536615, 33.196936, 103.865490], [25.583442, 31.419505, 78.404329], [27.064118, 33.407033, 198.828633]]
### 4
fourier: [[40.702988, 41.474858, 229.106138], [43.081924, 43.184267, 55.565779], [41.364426, 42.257136, 141.959441], [14.403612, 15.609838, 50.229671], [40.767561, 42.930810, 173.903736], [26.779886, 34.325587, 212.782533], [58.473341, 58.519032, 62.163983]]
### 6
fourier: [[71.427904, 76.734968, 125.303284], [29.288102, 32.922105, 35.185145], [39.126235, 42.681171, 202.223452], [28.199455, 29.386596, 88.731786], [85.278589, 100.535957, 523.910004], [71.714217, 74.365477, 272.179071], [97.392429, 99.427008, 432.234424]]
### 8
fourier: [[158.521773, 175.147930, 814.241691], [138.392009, 140.047093, 548.800326], [28.868897, 32.511741, 180.220653], [79.224451, 85.918829, 463.925921], [244.934776, 274.795215, 1324.614526], [44.124840, 53.708474, 331.237476], [114.570705, 117.365407, 546.459331]]
### 10
fourier: [[351.609199, 384.800984, 1784.953176]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.079802,
0.675796,
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],
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],
[
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],
[
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[
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],
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]
}
## Activation Signature
### 0
fourier: [[21.407213, 24.474679, 62.315266], [28.254216, 38.607056, 157.994976], [26.081038, 29.691720, 203.942072], [26.575432, 30.993106, 44.417243], [33.274087, 35.022529, 116.039277], [33.883848, 36.408500, 42.607798], [56.702075, 59.430071, 213.986375]]
### 2
fourier: [[37.460414, 37.598792, 208.694518], [26.092581, 31.763207, 61.450620], [15.526047, 19.273957, 163.672825], [27.168089, 29.584595, 59.301086], [29.536615, 33.196936, 103.865490], [25.583442, 31.419505, 78.404329], [27.064118, 33.407033, 198.828633]]
### 4
fourier: [[40.702988, 41.474858, 229.106138], [43.081924, 43.184267, 55.565779], [41.364426, 42.257136, 141.959441], [14.403612, 15.609838, 50.229671], [40.767561, 42.930810, 173.903736], [26.779886, 34.325587, 212.782533], [58.473341, 58.519032, 62.163983]]
### 6
fourier: [[71.427904, 76.734968, 125.303284], [29.288102, 32.922105, 35.185145], [39.126235, 42.681171, 202.223452], [28.199455, 29.386596, 88.731786], [85.278589, 100.535957, 523.910004], [71.714217, 74.365477, 272.179071], [97.392429, 99.427008, 432.234424]]
### 8
fourier: [[158.521773, 175.147930, 814.241691], [138.392009, 140.047093, 548.800326], [28.868897, 32.511741, 180.220653], [79.224451, 85.918829, 463.925921], [244.934776, 274.795215, 1324.614526], [44.124840, 53.708474, 331.237476], [114.570705, 117.365407, 546.459331]]
### 10
fourier: [[351.609199, 384.800984, 1784.953176]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.407212859131157, 24.474679281086484, 62.315266236662865]}, "1": {"fourier": [28.254216164653357, 38.60705575790016, 157.9949758052826]}, "2": {"fourier": [26.081038475304634, 29.691720305018308, 203.94207237660885]}, "3": {"fourier": [26.575431620072575, 30.993105864692943, 44.41724255681038]}, "4": {"fourier": [33.2740874291514, 35.02252865376857, 116.03927710652351]}, "5": {"fourier": [33.88384789228439, 36.40850015612481, 42.60779847821379]}, "6": {"fourier": [56.70207507958344, 59.430070718243435, 213.98637527227402]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [37.460413547225045, 37.59879171789549, 208.69451755285263]}, "1": {"fourier": [26.092580608825944, 31.76320725082782, 61.45062048174441]}, "2": {"fourier": [15.526046910175275, 19.273956565621152, 163.6728254556656]}, "3": {"fourier": [27.168088814858027, 29.584594729423877, 59.30108632147312]}, "4": {"fourier": [29.536614828222874, 33.19693633066112, 103.8654896505177]}, "5": {"fourier": [25.583442220371428, 31.419504634326145, 78.40432859957218]}, "6": {"fourier": [27.064117580488745, 33.407033109980915, 198.8286328613758]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [40.70298784116456, 41.47485844254752, 229.106137663126]}, "1": {"fourier": [43.08192431366366, 43.184267147531074, 55.56577929206941]}, "2": {"fourier": [41.36442575566439, 42.25713633033111, 141.9594407826662]}, "3": {"fourier": [14.403612340613204, 15.609838267979475, 50.22967106103897]}, "4": {"fourier": [40.76756100761389, 42.930809501265756, 173.90373557806015]}, "5": {"fourier": [26.77988570669991, 34.32558659376615, 212.78253324329853]}, "6": {"fourier": [58.473340600631964, 58.51903226701728, 62.163982551544905]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [71.42790426088798, 76.73496761124363, 125.30328360199928]}, "1": {"fourier": [29.288101698135165, 32.92210479699597, 35.185144654102544]}, "2": {"fourier": [39.12623514718922, 42.6811712415034, 202.22345171496272]}, "3": {"fourier": [28.199455451985646, 29.386595998117315, 88.7317864894867]}, "4": {"fourier": [85.27858890235031, 100.53595668708002, 523.9100035056472]}, "5": {"fourier": [71.71421745125399, 74.36547691689036, 272.1790709197521]}, "6": {"fourier": [97.3924287329677, 99.42700804124875, 432.2344240248203]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [158.52177347843536, 175.14792979791062, 814.2416912019253]}, "1": {"fourier": [138.3920089597868, 140.04709280816147, 548.8003262281418]}, "2": {"fourier": [28.868897205098936, 32.51174107893547, 180.2206525951624]}, "3": {"fourier": [79.22445055767189, 85.91882904211545, 463.92592108249664]}, "4": {"fourier": [244.93477563487022, 274.79521516630354, 1324.614526256919]}, "5": {"fourier": [44.124840125699684, 53.708473961508176, 331.23747634887695]}, "6": {"fourier": [114.57070474776177, 117.3654074309519, 546.4593305960298]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [351.6091993264029, 384.800983865675, 1784.9531759917736]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.084997, -0.353094, 0.079802, 0.675796, -0.276206], [-0.280768, 0.161847, 0.75519, -0.195307, 0.395432], [-0.392863, 0.320782, 0.662743, 0.104764, 0.212664], [-0.455277, -0.252651, -0.214715, 0.201335, 0.558145], [0.886098, 0.362283, -0.383383, -0.090144, -0.028801], [0.122906, 0.43442, -0.683138, 0.161806, -0.425845], [0.656619, -1.208492, 0.107933, -0.903286, 0.245074]], "network.0.bias": [-0.045218, 0.163596, 0.29904, -0.138186, 0.55614, 0.284178, 0.416716], "network.2.weight": [[0.592254, 0.683751, 0.473918, 0.119609, -0.404561, 0.087833, -0.41361], [0.36411, 0.075505, -0.425477, 0.337919, 0.828571, -0.067952, -0.269061], [-0.388143, -0.041957, -0.468782, -0.152503, -0.042747, -0.220922, -0.370737], [0.118209, 0.487354, 0.302538, 0.237948, -0.311438, -0.170438, -0.468505], [0.878569, 0.098515, 0.383557, 0.185143, -0.422367, -0.297033, -0.071827], [-0.544078, 0.004059, 0.046086, -0.209004, 0.24882, 0.767006, 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0.431219, 0.088501, 0.413953, -0.300614, 0.217137, 0.516097], [-0.383602, -0.375622, -0.011507, -0.257887, -0.152929, 0.26913, 0.481587], [0.7583, 0.731711, 0.692525, 0.148953, -0.360517, 0.439601, 1.101596], [0.353784, 0.579348, 0.394662, 0.586479, -0.579313, 0.626109, 0.203774], [0.350566, 1.055589, 0.574066, 0.601162, -0.426221, 0.826913, 0.241195]], "network.6.bias": [0.304163, 0.00241, -0.041687, -0.278248, -0.059768, -0.09008, -0.130385], "network.8.weight": [[-0.412019, 0.694729, 0.274861, 0.651213, 0.455462, 0.322685, 0.909369], [0.592277, 0.225425, -0.099926, -0.135089, -0.367864, -0.523589, -0.614035], [-0.056041, 0.025637, -0.169369, -0.518156, 0.035373, -0.416118, 0.016464], [-0.281864, 0.247729, -0.028922, 0.110738, -0.377511, -0.320402, -0.264559], [-0.3314, 1.1938, 0.781361, 0.183326, 1.034047, 0.657795, 0.876177], [-0.298865, 0.210683, -0.038723, -0.016496, -0.47725, -0.088862, 0.017005], [-0.005983, -0.182607, 0.528757, 0.050993, 0.147809, 0.546814, 0.439697]], "network.8.bias": [-0.204343, 0.511223, -0.224924, -0.29469, -0.335578, -0.381029, -0.089002], "network.10.weight": [[-0.50143, 0.647665, 0.085237, -0.366201, -0.859715, 0.040988, -0.524955]], "network.10.bias": [0.572285]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6790937781333923, "train_acc": 0.58, "val_loss": 0.7166121006011963, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6686617732048035, "train_acc": 0.58, "val_loss": 0.7104504108428955, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6429232358932495, "train_acc": 0.58, "val_loss": 0.6795019507408142, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6118739247322083, "train_acc": 0.51, "val_loss": 0.5897324085235596, "val_acc": 0.46}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5188994258642197, "train_acc": 0.51, "val_loss": 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"improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.15430914983153343, "train_acc": 0.965, "val_loss": 0.1494181752204895, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.12817486748099327, "train_acc": 0.965, "val_loss": 0.0865638330578804, "val_acc": 0.98}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.7166121006011963, "final_val_loss": 0.6795019507408142, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.5897324085235596, "final_val_loss": 0.0865638330578804, "initial_val_acc": 0.46, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 12}, "improvement": 0.52, "first_improvement_epoch": 2}} |
47 | {"target_pattern": "palindrome", "degraded_accuracy": 0.38, "improved_accuracy": 0.96, "improvement": 0.58, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8776, "learning_rate": 0.0354662552402799, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[26.252846, 28.350018, 61.688176], [28.644297, 28.980798, 114.829285], [24.223014, 26.252854, 78.113719], [22.407499, 25.511396, 25.640510], [12.253858, 12.882623, 14.275342]]
### 2
fourier: [[6.558632, 7.134508, 48.468771], [9.562895, 11.349545, 114.278755], [13.270779, 14.359790, 15.807045], [21.280377, 21.309365, 25.849223], [39.452144, 43.547108, 83.872986]]
### 4
fourier: [[2.722301, 2.813323, 63.488865], [17.162760, 17.717520, 20.308073], [19.977554, 20.515864, 22.863547], [18.322965, 20.957513, 73.070136], [15.713999, 15.769910, 29.447961]]
### 6
fourier: [[7.855733, 9.568992, 18.844145], [9.303758, 9.894717, 14.818134], [12.699037, 14.658835, 64.664829], [7.517771, 8.277674, 18.784434], [8.433762, 9.204832, 9.545878]]
### 8
fourier: [[5.996943, 7.153736, 10.869331], [16.966827, 18.533194, 52.841641], [15.801129, 18.712515, 60.663986], [4.060112, 4.686778, 48.932293], [5.928656, 5.991871, 6.879148]]
### 10
fourier: [[16.628637, 18.738184, 70.801483], [4.547496, 4.665941, 13.520595], [13.292269, 16.351887, 61.259758], [4.042248, 4.617305, 27.990880], [3.862404, 3.990743, 37.523930]]
### 12
fourier: [[18.154578, 21.660783, 24.167595]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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"network.2.bias": [
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"network.4.weight": [
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"network.6.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[26.252846, 28.350018, 61.688176], [28.644297, 28.980798, 114.829285], [24.223014, 26.252854, 78.113719], [22.407499, 25.511396, 25.640510], [12.253858, 12.882623, 14.275342]]
### 2
fourier: [[6.558632, 7.134508, 48.468771], [9.562895, 11.349545, 114.278755], [13.270779, 14.359790, 15.807045], [21.280377, 21.309365, 25.849223], [39.452144, 43.547108, 83.872986]]
### 4
fourier: [[2.722301, 2.813323, 63.488865], [17.162760, 17.717520, 20.308073], [19.977554, 20.515864, 22.863547], [18.322965, 20.957513, 73.070136], [15.713999, 15.769910, 29.447961]]
### 6
fourier: [[7.855733, 9.568992, 18.844145], [9.303758, 9.894717, 14.818134], [12.699037, 14.658835, 64.664829], [7.517771, 8.277674, 18.784434], [8.433762, 9.204832, 9.545878]]
### 8
fourier: [[5.996943, 7.153736, 10.869331], [16.966827, 18.533194, 52.841641], [15.801129, 18.712515, 60.663986], [4.060112, 4.686778, 48.932293], [5.928656, 5.991871, 6.879148]]
### 10
fourier: [[16.628637, 18.738184, 70.801483], [4.547496, 4.665941, 13.520595], [13.292269, 16.351887, 61.259758], [4.042248, 4.617305, 27.990880], [3.862404, 3.990743, 37.523930]]
### 12
fourier: [[18.154578, 21.660783, 24.167595]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [26.2528458846525, 28.350017807689103, 61.68817636370659]}, "1": {"fourier": [28.644296801890523, 28.98079843294264, 114.82928451895714]}, "2": {"fourier": [24.223013689149393, 26.25285399600489, 78.11371856927872]}, "3": {"fourier": [22.40749937791606, 25.511395812064567, 25.640509905850198]}, "4": {"fourier": [12.2538579930108, 12.882623189623677, 14.275341745604528]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [6.558631793224826, 7.134508019965943, 48.46877110004425]}, "1": {"fourier": [9.562895172023664, 11.349545273863933, 114.27875483036041]}, "2": {"fourier": [13.270779427696947, 14.359789637518714, 15.807045096556905]}, "3": {"fourier": [21.28037692036352, 21.30936490306396, 25.849222663476144]}, "4": {"fourier": [39.45214412705921, 43.54710820035497, 83.87298629805446]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [2.722300869281122, 2.8133234526332984, 63.48886474967003]}, "1": {"fourier": [17.162760419727707, 17.71751998970151, 20.308073130628852]}, "2": {"fourier": [19.977553958814607, 20.515864072060936, 22.863546604132317]}, "3": {"fourier": [18.32296475899018, 20.957512926291614, 73.0701359808445]}, "4": {"fourier": [15.71399866632086, 15.769910173645451, 29.44796121120453]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [7.85573288722917, 9.568991604526545, 18.844144858419895]}, "1": {"fourier": [9.303757777729139, 9.894717159270789, 14.818133845925331]}, "2": {"fourier": [12.69903733557708, 14.658835226610515, 64.66482852399349]}, "3": {"fourier": [7.517771054176801, 8.277673525221028, 18.784434113651514]}, "4": {"fourier": [8.433762201388207, 9.20483234241864, 9.545878430897206]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [5.9969428349360285, 7.153735934436581, 10.8693305850029]}, "1": {"fourier": [16.966826555324896, 18.533193829616888, 52.84164133667946]}, "2": {"fourier": [15.801128758722767, 18.712514714502618, 60.66398584842682]}, "3": {"fourier": [4.060112338510313, 4.686778218176296, 48.932293117046356]}, "4": {"fourier": [5.928656416827783, 5.9918706009478475, 6.879147982605116]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [16.628637104199463, 18.7381838137587, 70.8014826476574]}, "1": {"fourier": [4.547496221681115, 4.665941097884243, 13.52059531211853]}, "2": {"fourier": [13.292268766819372, 16.351887334264337, 61.25975821912289]}, "3": {"fourier": [4.042248027114589, 4.617304515231834, 27.99087956547737]}, "4": {"fourier": [3.8624038412979607, 3.990742761167698, 37.5239302366972]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [18.154577934333826, 21.660782983447536, 24.167595334351063]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.112791, -0.230379, -0.113479, 0.241262, 0.701537], [0.6791, -0.058067, 0.142176, 0.070405, -0.365576], [-0.40928, 0.164855, 0.139645, -0.192315, 0.690438], [-0.241613, -0.208187, -0.287649, 0.259999, 0.506459], [-0.184496, 0.222858, -0.26961, -0.069874, 0.317926]], "network.0.bias": [0.100031, 0.539497, 0.346019, 0.164622, 0.141165], "network.2.weight": [[0.179295, -0.162533, 0.162793, -0.309627, 0.184976], [0.06195, -0.138459, -0.525696, -0.063796, 0.031078], [0.206306, 0.374212, -0.617791, 0.158701, -0.109494], [-0.320764, 0.268888, -0.262703, -0.572268, 0.145243], [0.71009, -0.459231, 0.469705, 0.42986, 0.60503]], "network.2.bias": [0.541107, -0.56948, -0.0289, 0.396109, 0.027531], "network.4.weight": [[-0.370225, -0.000599, 0.202601, -0.124957, 0.023684], [0.459577, -0.396787, -0.416143, 0.069825, -0.581626], [0.203886, 0.026217, -0.111168, 0.436056, -0.568], [0.100904, 0.016924, 0.490167, 0.359386, 0.584454], [-0.079228, -0.227991, 0.711383, 0.350908, -0.282379]], "network.4.bias": [-0.549966, 0.454232, 0.546723, -0.266735, -0.326676], "network.6.weight": [[0.255518, 0.317181, 0.615401, -0.243507, -0.429238], [-0.233847, 0.541215, 0.333329, -0.277968, -0.397575], [-0.226222, -0.489371, 0.030006, 0.554761, 0.444663], [0.100214, 0.514638, 0.439739, -0.121086, -0.559778], [-0.295792, 0.424266, 0.223149, -0.295393, -0.434337]], "network.6.bias": [0.113842, 0.168676, 0.289049, 0.073234, 0.186517], "network.8.weight": [[0.152979, 0.207273, -0.123999, 0.395007, 0.149666], [-0.610427, -0.44228, 0.69217, -0.264897, -0.247103], [0.789317, 0.629075, -0.472329, 0.303977, 0.299597], [0.004511, -0.104193, -0.405023, -0.084174, -0.109326], [0.007171, -0.237468, -0.013125, -0.614995, -0.321502]], "network.8.bias": [-0.301217, 0.56581, 0.395076, -0.167737, 0.347813], "network.10.weight": [[-0.415922, 0.804198, -0.280301, 0.144397, 0.343431], [0.422568, 0.312921, 0.039403, 0.155035, 0.410933], [0.042521, -0.351865, 0.652108, -0.035033, -0.137631], [-0.185048, -0.178406, 0.169242, 0.288146, 0.096192], [0.359315, -0.327746, -0.113562, 0.324712, 0.025822]], "network.10.bias": [0.387461, -0.232981, 0.450096, -0.303681, -0.122048], "network.12.weight": [[-0.710234, -0.100544, 0.614316, -0.198844, -0.062244]], "network.12.bias": [-0.085222]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6802124381065369, "train_acc": 0.605, "val_loss": 0.7295581698417664, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.666690319776535, "train_acc": 0.605, "val_loss": 0.7070908546447754, "val_acc": 0.38}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6462147533893585, "train_acc": 0.605, "val_loss": 0.66290283203125, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6461910009384155, "train_acc": 0.53, "val_loss": 0.6725580096244812, "val_acc": 0.38}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5845130980014801, "train_acc": 0.685, "val_loss": 0.5495725870132446, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.5357065796852112, "train_acc": 0.855, "val_loss": 0.4814292788505554, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.45296674966812134, "train_acc": 0.86, "val_loss": 0.34245696663856506, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.3263399004936218, "train_acc": 0.885, "val_loss": 0.364292711019516, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.25854797661304474, "train_acc": 0.915, "val_loss": 0.2639107406139374, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.19489596039056778, "train_acc": 0.925, "val_loss": 0.3689037263393402, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.16455909609794617, "train_acc": 0.93, "val_loss": 0.2785435616970062, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.13342848420143127, "train_acc": 0.94, "val_loss": 0.24970029294490814, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.15510369837284088, "train_acc": 0.955, "val_loss": 0.3009173274040222, "val_acc": 0.94}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7295581698417664, "final_val_loss": 0.66290283203125, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.6725580096244812, "final_val_loss": 0.3009173274040222, "initial_val_acc": 0.38, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 6}, "improvement": 0.58, "first_improvement_epoch": 2}} |
48 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.64, "improved_accuracy": 0.82, "improvement": 0.17999999999999994, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1955, "learning_rate": 0.09855088108934446, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.821258,
0.695183,
-0.144194,
0.45044
],
[
-0.766331,
-0.816548,
0.089336,
0.617624,
-0.425841,
0.635875
],
[
-0.589813,
-1.150473,
0.395366,
0.316806,
-0.734269,
0.162096
],
[
0.204895,
-0.105591,
-0.604131,
-0.658563,
0.478353,
-0.566598
]
],
"network.8.bias": [
-0.09459,
0.418902,
-0.298226,
0.299086,
0.419013,
0.284927
],
"network.10.weight": [
[
0.185118,
-0.678524,
-0.351746,
-0.848627,
-1.080981,
0.200478
]
],
"network.10.bias": [
0.329956
]
}
## Activation Signature
### 0
fourier: [[26.447183, 29.086987, 63.332508], [32.084278, 35.367063, 278.547730], [51.006574, 57.304361, 163.478403], [34.227564, 39.177497, 43.104836], [27.066577, 27.253074, 203.011581], [29.006698, 33.263189, 231.847348]]
### 2
fourier: [[4.598635, 4.787610, 59.100745], [44.528495, 47.664434, 184.233670], [41.351393, 41.830574, 173.777784], [22.214509, 23.797053, 55.641987], [34.855857, 36.089456, 157.990420], [49.016942, 53.635291, 76.342847]]
### 4
fourier: [[16.541061, 18.198069, 152.627727], [85.942184, 86.721702, 333.150681], [131.451419, 132.552691, 545.584783], [165.707834, 168.280968, 721.627431], [53.808215, 54.081004, 188.535944], [119.244631, 120.211391, 427.321809]]
### 6
fourier: [[73.593684, 75.057490, 302.746640], [25.484312, 25.680884, 137.973733], [106.248480, 108.782551, 481.243928], [119.094988, 120.090785, 470.402480], [133.325205, 135.372968, 509.367454], [63.774139, 66.399726, 300.612709]]
### 8
fourier: [[164.106029, 168.029811, 705.352277], [216.065621, 222.581333, 986.911698], [199.644112, 203.296418, 826.114256], [122.714394, 126.216088, 555.064178], [88.679489, 92.472398, 428.416571], [179.318048, 183.586812, 738.338148]]
### 10
fourier: [[417.373569, 430.990401, 1861.057098]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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],
[
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],
[
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],
[
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],
[
0.239939,
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
[
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],
[
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],
[
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0.799254
],
[
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0.27004,
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],
[
0.222756,
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0.689254,
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]
],
"network.2.bias": [
-0.463434,
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0.005515,
0.172266,
0.035638,
0.161671
],
"network.4.weight": [
[
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0.002615
],
[
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],
[
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1.008554,
0.3895
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[
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[
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[
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]
],
"network.4.bias": [
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],
"network.6.weight": [
[
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[
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[
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[
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[
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[
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],
"network.6.bias": [
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],
"network.8.weight": [
[
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],
[
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[
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[
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[
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],
[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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-0.848627,
-1.080981,
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]
],
"network.10.bias": [
0.329956
]
}
## Activation Signature
### 0
fourier: [[26.447183, 29.086987, 63.332508], [32.084278, 35.367063, 278.547730], [51.006574, 57.304361, 163.478403], [34.227564, 39.177497, 43.104836], [27.066577, 27.253074, 203.011581], [29.006698, 33.263189, 231.847348]]
### 2
fourier: [[4.598635, 4.787610, 59.100745], [44.528495, 47.664434, 184.233670], [41.351393, 41.830574, 173.777784], [22.214509, 23.797053, 55.641987], [34.855857, 36.089456, 157.990420], [49.016942, 53.635291, 76.342847]]
### 4
fourier: [[16.541061, 18.198069, 152.627727], [85.942184, 86.721702, 333.150681], [131.451419, 132.552691, 545.584783], [165.707834, 168.280968, 721.627431], [53.808215, 54.081004, 188.535944], [119.244631, 120.211391, 427.321809]]
### 6
fourier: [[73.593684, 75.057490, 302.746640], [25.484312, 25.680884, 137.973733], [106.248480, 108.782551, 481.243928], [119.094988, 120.090785, 470.402480], [133.325205, 135.372968, 509.367454], [63.774139, 66.399726, 300.612709]]
### 8
fourier: [[164.106029, 168.029811, 705.352277], [216.065621, 222.581333, 986.911698], [199.644112, 203.296418, 826.114256], [122.714394, 126.216088, 555.064178], [88.679489, 92.472398, 428.416571], [179.318048, 183.586812, 738.338148]]
### 10
fourier: [[417.373569, 430.990401, 1861.057098]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [26.447183376440048, 29.086986658736972, 63.33250768482685]}, "1": {"fourier": [32.084277844015105, 35.367063032879514, 278.5477304458618]}, "2": {"fourier": [51.00657430112886, 57.30436082409574, 163.478403121233]}, "3": {"fourier": [34.227564420781555, 39.177497163619925, 43.10483607131229]}, "4": {"fourier": [27.06657651636887, 27.25307365570049, 203.01158076524734]}, "5": {"fourier": [29.006698271522097, 33.2631888464511, 231.8473483622074]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [4.598634925087179, 4.787610054045156, 59.10074517130852]}, "1": {"fourier": [44.52849497966461, 47.664433918437695, 184.23367006424814]}, "2": {"fourier": [41.35139292803343, 41.83057380825966, 173.77778413891792]}, "3": {"fourier": [22.214508557770124, 23.797053490395346, 55.64198691397905]}, "4": {"fourier": [34.8558568402202, 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[106.24848039215203, 108.78255064006093, 481.24392779171467]}, "3": {"fourier": [119.094988019965, 120.09078502084633, 470.40248027443886]}, "4": {"fourier": [133.32520511437647, 135.3729675469255, 509.3674538731575]}, "5": {"fourier": [63.774138803035925, 66.3997260961507, 300.6127091050148]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [164.1060287041632, 168.02981082105927, 705.3522772341967]}, "1": {"fourier": [216.06562110575348, 222.5813334168956, 986.9116983413696]}, "2": {"fourier": [199.64411156382863, 203.29641830515135, 826.1142564564943]}, "3": {"fourier": [122.71439413305559, 126.21608840869717, 555.0641775429249]}, "4": {"fourier": [88.67948872275343, 92.4723979362884, 428.4165708720684]}, "5": {"fourier": [179.31804838908315, 183.58681158034486, 738.3381479531527]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [417.3735694401733, 430.9904006638466, 1861.057097941637]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.520574, -0.500451, 0.228212, 0.374417, -0.078132], [0.036264, 0.135393, -0.75617, -0.413394, -0.432267], [1.164616, 0.90257, -0.250046, -0.390013, -0.410002], [-0.884984, -0.076331, -0.053459, 0.400438, 0.396611], [0.239939, 0.074195, -0.478655, -0.353172, -0.484368], [0.399419, 0.04239, -0.745763, -0.417805, -0.170981]], "network.0.bias": [-0.3272, 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0.299086, 0.419013, 0.284927], "network.10.weight": [[0.185118, -0.678524, -0.351746, -0.848627, -1.080981, 0.200478]], "network.10.bias": [0.329956]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6877061426639557, "train_acc": 0.565, "val_loss": 0.6857731342315674, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6883341073989868, "train_acc": 0.565, "val_loss": 0.6857035160064697, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6835896670818329, "train_acc": 0.565, "val_loss": 0.6714523434638977, "val_acc": 0.6}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6747648119926453, "train_acc": 0.61, "val_loss": 0.6388542056083679, "val_acc": 0.64}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.7508282661437988, "train_acc": 0.595, "val_loss": 0.5318901538848877, "val_acc": 0.72}, {"stage": "improved", "epoch": 1, 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"train_acc": 0.795, "val_loss": 0.47037652134895325, "val_acc": 0.72}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.4043327420949936, "train_acc": 0.83, "val_loss": 0.3642432391643524, "val_acc": 0.82}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.40946105122566223, "train_acc": 0.845, "val_loss": 0.5574055314064026, "val_acc": 0.7}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6857731342315674, "final_val_loss": 0.6388542056083679, "initial_val_acc": 0.56, "final_val_acc": 0.64, "best_val_acc": 0.64}, "improved_stage": {"initial_val_loss": 0.5318901538848877, "final_val_loss": 0.5574055314064026, "initial_val_acc": 0.72, "final_val_acc": 0.7, "best_val_acc": 0.82, "best_epoch": 12}, "improvement": 0.17999999999999994, "first_improvement_epoch": 3}} |
49 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.5, "improved_accuracy": 0.94, "improvement": 0.43999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5360, "learning_rate": 0.0885264373224075, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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[
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[
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[
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[
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[
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[
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[
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[
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],
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"network.12.weight": [
[
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]
],
"network.12.bias": [
1.143543
]
}
## Activation Signature
### 0
fourier: [[84.695000, 88.981694, 380.092058], [100.053348, 107.486777, 486.287620], [66.763587, 72.997618, 266.431717], [83.926959, 89.785283, 292.820754], [24.470766, 24.984853, 170.132283]]
### 2
fourier: [[127.841706, 128.021199, 569.904662], [18.976964, 23.142838, 148.211653], [191.043147, 197.644100, 832.847566], [54.552671, 55.661066, 270.342255], [111.750040, 119.342127, 585.049438]]
### 4
fourier: [[15.344866, 15.355266, 85.795086], [136.147856, 136.240127, 554.328259], [105.426352, 105.497805, 473.173329], [6.457963, 6.462339, 53.956285], [124.795155, 124.879734, 515.204289]]
### 6
fourier: [[127.629357, 131.250398, 527.555641], [90.663566, 93.373114, 420.245019], [28.672128, 29.609488, 153.934396], [134.747790, 138.538541, 493.865066], [80.200057, 82.526479, 352.670380]]
### 8
fourier: [[122.574207, 128.382552, 517.842678], [42.698937, 44.299455, 208.869279], [24.002555, 24.655992, 157.611692], [118.941737, 126.945474, 417.887053], [126.070422, 135.028307, 460.076536]]
### 10
fourier: [[55.441734, 58.877594, 219.849628], [12.496869, 13.023004, 72.537467], [162.734984, 172.767931, 568.416121], [25.728474, 27.371837, 124.994969], [147.578887, 156.425050, 504.910340]]
### 12
fourier: [[206.782446, 216.353178, 639.747575]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
1.845982,
0.465397,
0.518749,
0.449045,
0.045656
],
[
2.02587,
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0.574275,
0.288121
],
[
1.331713,
1.121038,
0.339309,
-0.339043,
-0.01457
],
[
2.130467,
0.203164,
0.158207,
0.263139,
-0.092677
],
[
0.153987,
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
[
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],
[
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],
[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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],
[
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[
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[
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[
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],
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[
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[
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],
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],
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[
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[
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]
],
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],
"network.10.weight": [
[
-0.129677,
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-0.169452,
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],
[
-0.209759,
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0.229409
],
[
0.070583,
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0.76791
],
[
0.350095,
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],
[
0.010946,
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0.356557,
0.82787,
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]
],
"network.10.bias": [
-0.134491,
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-0.453937,
-0.312297,
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],
"network.12.weight": [
[
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-0.878376,
-0.165043,
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]
],
"network.12.bias": [
1.143543
]
}
## Activation Signature
### 0
fourier: [[84.695000, 88.981694, 380.092058], [100.053348, 107.486777, 486.287620], [66.763587, 72.997618, 266.431717], [83.926959, 89.785283, 292.820754], [24.470766, 24.984853, 170.132283]]
### 2
fourier: [[127.841706, 128.021199, 569.904662], [18.976964, 23.142838, 148.211653], [191.043147, 197.644100, 832.847566], [54.552671, 55.661066, 270.342255], [111.750040, 119.342127, 585.049438]]
### 4
fourier: [[15.344866, 15.355266, 85.795086], [136.147856, 136.240127, 554.328259], [105.426352, 105.497805, 473.173329], [6.457963, 6.462339, 53.956285], [124.795155, 124.879734, 515.204289]]
### 6
fourier: [[127.629357, 131.250398, 527.555641], [90.663566, 93.373114, 420.245019], [28.672128, 29.609488, 153.934396], [134.747790, 138.538541, 493.865066], [80.200057, 82.526479, 352.670380]]
### 8
fourier: [[122.574207, 128.382552, 517.842678], [42.698937, 44.299455, 208.869279], [24.002555, 24.655992, 157.611692], [118.941737, 126.945474, 417.887053], [126.070422, 135.028307, 460.076536]]
### 10
fourier: [[55.441734, 58.877594, 219.849628], [12.496869, 13.023004, 72.537467], [162.734984, 172.767931, 568.416121], [25.728474, 27.371837, 124.994969], [147.578887, 156.425050, 504.910340]]
### 12
fourier: [[206.782446, 216.353178, 639.747575]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [84.69499998755015, 88.98169396609788, 380.09205800294876]}, "1": {"fourier": [100.05334823454751, 107.48677683220416, 486.2876201868057]}, "2": {"fourier": [66.76358725151975, 72.99761782313328, 266.43171739578247]}, "3": {"fourier": [83.92695931022804, 89.7852832295006, 292.82075425982475]}, "4": {"fourier": [24.470766445332064, 24.98485338909548, 170.13228346407413]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [127.8417056539276, 128.0211987649836, 569.9046618416905]}, "1": {"fourier": [18.976964147892776, 23.142837779681706, 148.21165305376053]}, "2": {"fourier": [191.04314656036019, 197.6440995213002, 832.847565561533]}, "3": {"fourier": [54.55267120200031, 55.66106578575854, 270.34225453436375]}, "4": {"fourier": [111.75003974433903, 119.34212652755393, 585.0494384467602]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [15.344866480780691, 15.355266454823942, 85.79508583247662]}, "1": {"fourier": [136.14785606794248, 136.2401272848254, 554.328259319067]}, "2": {"fourier": [105.42635206510313, 105.49780484456791, 473.1733286678791]}, "3": {"fourier": [6.457962969099308, 6.462339311061579, 53.95628488063812]}, "4": {"fourier": [124.79515466090025, 124.87973408098476, 515.2042889744043]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [127.62935713313603, 131.25039766944246, 527.5556406378746]}, "1": {"fourier": [90.66356641709005, 93.37311351502252, 420.2450187802315]}, "2": {"fourier": [28.672127725574263, 29.60948779657539, 153.93439614772797]}, "3": {"fourier": [134.7477897792949, 138.5385411365422, 493.8650659918785]}, "4": {"fourier": [80.20005664093793, 82.52647865538405, 352.670380204916]}}, "layer_info": 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0.175292, -0.878376, -0.165043, -0.440125]], "network.12.bias": [1.143543]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.700906902551651, "train_acc": 0.435, "val_loss": 0.692647397518158, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6715249121189117, "train_acc": 0.565, "val_loss": 0.760621190071106, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6530344188213348, "train_acc": 0.565, "val_loss": 0.662980854511261, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.60840904712677, "train_acc": 0.565, "val_loss": 0.589059591293335, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6192219257354736, "train_acc": 0.585, "val_loss": 0.5671709179878235, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5256700217723846, "train_acc": 0.815, "val_loss": 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"improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.23474040627479553, "train_acc": 0.93, "val_loss": 0.2690354585647583, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.23693636059761047, "train_acc": 0.93, "val_loss": 0.22007472813129425, "val_acc": 0.94}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.692647397518158, "final_val_loss": 0.589059591293335, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5671709179878235, "final_val_loss": 0.22007472813129425, "initial_val_acc": 0.82, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 11}, "improvement": 0.43999999999999995, "first_improvement_epoch": 3}} |
50 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.74, "improved_accuracy": 0.9, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9169, "learning_rate": 0.02856298291523507, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[20.128421, 22.354247, 88.992597], [24.441660, 27.429049, 130.209160], [32.792209, 33.705214, 34.835219], [26.470440, 28.186938, 28.239808], [32.792600, 33.533522, 114.243474], [29.594202, 31.867065, 141.006520]]
### 2
fourier: [[27.331859, 29.153161, 34.992303], [14.246684, 15.913559, 19.068479], [12.190036, 15.438049, 85.534940], [12.826894, 13.949824, 109.077537], [10.652737, 10.924132, 89.091638], [37.969082, 38.280931, 44.423661]]
### 4
fourier: [[15.850047, 16.138224, 16.554541], [7.598812, 8.054717, 86.231101], [7.285347, 10.983775, 62.087381], [4.644050, 4.658790, 65.119118], [9.462895, 10.320938, 15.634335], [14.024817, 14.107015, 126.446075]]
### 6
fourier: [[14.292501, 14.631270, 50.302373], [6.007827, 6.293172, 62.268888], [12.864814, 14.031812, 142.484418], [6.278842, 6.978347, 110.105457], [10.244928, 10.994612, 119.274723], [10.249919, 10.893029, 41.312332]]
### 8
fourier: [[19.527010, 20.294360, 233.275528]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.421745,
0.412765,
0.010861,
0.488999,
-0.300247
]
],
"network.6.bias": [
0.039959,
-0.312104,
0.354036,
0.564275,
0.321211,
0.230757
],
"network.8.weight": [
[
0.626756,
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-0.340547,
-0.511359,
-0.70349,
0.424742
]
],
"network.8.bias": [
-0.621065
]
}
## Activation Signature
### 0
fourier: [[20.128421, 22.354247, 88.992597], [24.441660, 27.429049, 130.209160], [32.792209, 33.705214, 34.835219], [26.470440, 28.186938, 28.239808], [32.792600, 33.533522, 114.243474], [29.594202, 31.867065, 141.006520]]
### 2
fourier: [[27.331859, 29.153161, 34.992303], [14.246684, 15.913559, 19.068479], [12.190036, 15.438049, 85.534940], [12.826894, 13.949824, 109.077537], [10.652737, 10.924132, 89.091638], [37.969082, 38.280931, 44.423661]]
### 4
fourier: [[15.850047, 16.138224, 16.554541], [7.598812, 8.054717, 86.231101], [7.285347, 10.983775, 62.087381], [4.644050, 4.658790, 65.119118], [9.462895, 10.320938, 15.634335], [14.024817, 14.107015, 126.446075]]
### 6
fourier: [[14.292501, 14.631270, 50.302373], [6.007827, 6.293172, 62.268888], [12.864814, 14.031812, 142.484418], [6.278842, 6.978347, 110.105457], [10.244928, 10.994612, 119.274723], [10.249919, 10.893029, 41.312332]]
### 8
fourier: [[19.527010, 20.294360, 233.275528]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [20.12842137774726, 22.354246903792802, 88.99259655177593]}, "1": {"fourier": [24.441660367934876, 27.429048631842157, 130.20916049741209]}, "2": {"fourier": [32.79220888796202, 33.705213523231606, 34.83521935733877]}, "3": {"fourier": [26.470440174579444, 28.186937912133946, 28.239807851005274]}, "4": {"fourier": [32.792599826449084, 33.53352165586413, 114.24347406625748]}, "5": {"fourier": [29.59420180086502, 31.867065218195062, 141.0065201818943]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [27.33185909040192, 29.153161360950886, 34.99230255931616]}, "1": {"fourier": [14.246683815303374, 15.913559429436752, 19.06847919523716]}, "2": {"fourier": [12.190036239455285, 15.43804861217242, 85.53493993356824]}, "3": {"fourier": [12.826894007561298, 13.949824494535525, 109.07753673195839]}, "4": {"fourier": [10.65273672638796, 10.924132225445828, 89.09163787961006]}, "5": {"fourier": [37.96908222805594, 38.2809313564069, 44.42366069785864]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [15.850047086287695, 16.1382242972583, 16.554540649056435]}, "1": {"fourier": [7.598812067622942, 8.054717183061847, 86.23110097646713]}, "2": {"fourier": [7.28534699954873, 10.983774901460025, 62.087381184101105]}, "3": {"fourier": [4.644049873545122, 4.658790253503788, 65.1191183924675]}, "4": {"fourier": [9.462894534422887, 10.320938126529622, 15.634335026144981]}, "5": {"fourier": [14.024816733368784, 14.107014709629079, 126.44607508182526]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [14.292501335694784, 14.631269625052395, 50.30237263441086]}, "1": {"fourier": [6.007827213374997, 6.293171689183542, 62.26888833940029]}, "2": {"fourier": [12.86481434338785, 14.031812070073356, 142.48441809415817]}, "3": {"fourier": [6.2788419862296845, 6.978346550122786, 110.1054573059082]}, "4": {"fourier": [10.24492760954016, 10.994612385855408, 119.27472287416458]}, "5": {"fourier": [10.249918968894436, 10.893029129196348, 41.312331557273865]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [19.527010396082876, 20.294360368792102, 233.27552777528763]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.003591, 0.022307, -0.102354, -0.243793, -0.448295], [-0.534966, 0.249665, 0.346929, 0.32325, 0.210121], [-0.911377, 0.068391, 0.188778, 0.065309, 0.374757], [0.104803, -0.866026, -0.068396, 0.214154, 0.239875], [-0.497091, -0.231376, 0.669203, 0.375894, 0.273717], [0.543494, 0.618652, -0.263075, -0.026883, -0.076242]], "network.0.bias": [0.264519, -0.019476, 0.324281, 0.650046, -0.231966, 0.464287], "network.2.weight": [[0.851831, 0.464355, 0.437631, -0.780342, 0.291025, -0.353494], [0.33422, 0.165709, 0.080096, -0.630141, 0.395529, -0.024468], [-0.272055, -0.182964, -0.289256, 0.175595, 0.006955, -0.335285], [0.494805, -0.453474, -0.296564, -0.378128, 0.244246, -0.306591], [-0.325517, -0.116413, -0.370884, 0.370056, 0.491262, 0.12804], [-0.334484, -0.238617, -0.324574, 0.034263, -0.715847, 0.647375]], "network.2.bias": [-0.148829, -0.344769, -0.037615, 0.001441, 0.39321, 0.541985], "network.4.weight": [[0.634987, 0.513551, 0.651392, -0.2919, -0.574917, -0.006252], [0.030613, -0.064308, -0.445748, -0.642433, 0.590661, 0.165433], [-0.515878, 0.207787, 0.677182, 0.296412, 0.406696, -0.19405], [-0.027285, -0.279252, 0.178169, 0.183912, 0.154677, -0.129252], [0.415574, -0.034756, 0.796691, 0.031778, -0.065051, -0.193619], [-0.088964, 0.00982, -0.709487, -0.172422, 0.386396, 0.55809]], "network.4.bias": [-0.2907, 0.194013, -0.464698, -0.60044, -0.172177, 0.595922], "network.6.weight": [[0.691695, 0.010532, 0.247739, -0.191468, 0.237372, -0.586863], [0.407001, 0.110762, 0.302055, 0.337235, -0.34318, -0.347401], [-0.156729, 0.493839, -0.201026, -0.150731, -0.145086, 0.633698], [-0.273528, 0.358079, -0.715793, -0.26071, 0.093617, 0.226317], [-0.084116, 0.187226, -0.35852, -0.445655, -0.21822, 0.592645], [0.3596, -0.421745, 0.412765, 0.010861, 0.488999, -0.300247]], "network.6.bias": [0.039959, -0.312104, 0.354036, 0.564275, 0.321211, 0.230757], "network.8.weight": [[0.626756, 0.323901, -0.340547, -0.511359, -0.70349, 0.424742]], "network.8.bias": [-0.621065]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6870701909065247, "train_acc": 0.555, "val_loss": 0.6929000616073608, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6878697276115417, "train_acc": 0.555, "val_loss": 0.687052309513092, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6752554476261139, "train_acc": 0.585, "val_loss": 0.6615450978279114, "val_acc": 0.7}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6667123734951019, "train_acc": 0.63, "val_loss": 0.6425054669380188, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6281623244285583, "train_acc": 0.715, "val_loss": 0.613358736038208, "val_acc": 0.74}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5941150486469269, "train_acc": 0.71, "val_loss": 0.5830345153808594, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5467813313007355, "train_acc": 0.78, "val_loss": 0.5213663578033447, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.4882854074239731, "train_acc": 0.805, "val_loss": 0.4566018283367157, "val_acc": 0.8}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.40870797634124756, "train_acc": 0.835, "val_loss": 0.4283798933029175, "val_acc": 0.72}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.3945188671350479, "train_acc": 0.82, "val_loss": 0.40306463837623596, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.3724464625120163, "train_acc": 0.82, "val_loss": 0.2589341402053833, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.374486580491066, "train_acc": 0.85, "val_loss": 0.23542289435863495, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.28662317991256714, "train_acc": 0.875, "val_loss": 0.293496698141098, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.3268279433250427, "train_acc": 0.855, "val_loss": 0.23994003236293793, "val_acc": 0.88}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.6929000616073608, "final_val_loss": 0.6425054669380188, "initial_val_acc": 0.52, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.613358736038208, "final_val_loss": 0.23994003236293793, "initial_val_acc": 0.74, "final_val_acc": 0.88, "best_val_acc": 0.9, "best_epoch": 10}, "improvement": 0.16000000000000003, "first_improvement_epoch": 3}} |
51 | {"target_pattern": "has_majority", "degraded_accuracy": 0.56, "improved_accuracy": 0.74, "improvement": 0.17999999999999994, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7506, "learning_rate": 0.05975136536946539, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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]
}
## Activation Signature
### 0
fourier: [[33.398703, 36.681075, 57.484531], [24.964587, 27.646480, 165.350165], [28.058963, 32.770028, 155.776936], [51.937364, 55.240508, 230.698543], [24.156765, 26.822413, 32.508668], [33.677052, 35.286634, 48.589579], [23.789081, 23.898983, 144.574790]]
### 2
fourier: [[21.188295, 22.285647, 204.721253], [18.938501, 20.480894, 90.295972], [6.699168, 9.193027, 27.128994], [21.473884, 25.502354, 106.399444], [14.524768, 16.132987, 167.178736], [10.819144, 13.475131, 31.934908], [9.841842, 11.149770, 15.073825]]
### 4
fourier: [[11.127243, 12.812654, 94.417443], [25.817043, 31.808260, 104.292986], [8.660344, 9.649527, 64.732683], [9.063000, 10.472500, 31.486070], [20.702870, 25.296160, 44.864593], [8.731759, 9.014164, 10.053007], [13.055282, 15.109026, 89.316744]]
### 6
fourier: [[11.707955, 13.224132, 13.669580], [5.860970, 7.379259, 49.711380], [12.661083, 14.476720, 27.244960], [18.753347, 21.844579, 72.361441], [5.294937, 6.510391, 10.804992], [1.038057, 1.161905, 40.801551], [9.612084, 11.874244, 75.128850]]
### 8
fourier: [[15.317404, 15.687568, 39.398314], [6.690980, 7.314833, 42.576638], [7.643964, 7.939635, 8.844454], [2.062313, 2.681012, 33.160825], [1.145424, 1.388218, 17.492651], [0.666687, 0.949846, 28.888455], [15.003334, 16.034844, 56.500820]]
### 10
fourier: [[12.155661, 12.303285, 29.521980]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[33.398703, 36.681075, 57.484531], [24.964587, 27.646480, 165.350165], [28.058963, 32.770028, 155.776936], [51.937364, 55.240508, 230.698543], [24.156765, 26.822413, 32.508668], [33.677052, 35.286634, 48.589579], [23.789081, 23.898983, 144.574790]]
### 2
fourier: [[21.188295, 22.285647, 204.721253], [18.938501, 20.480894, 90.295972], [6.699168, 9.193027, 27.128994], [21.473884, 25.502354, 106.399444], [14.524768, 16.132987, 167.178736], [10.819144, 13.475131, 31.934908], [9.841842, 11.149770, 15.073825]]
### 4
fourier: [[11.127243, 12.812654, 94.417443], [25.817043, 31.808260, 104.292986], [8.660344, 9.649527, 64.732683], [9.063000, 10.472500, 31.486070], [20.702870, 25.296160, 44.864593], [8.731759, 9.014164, 10.053007], [13.055282, 15.109026, 89.316744]]
### 6
fourier: [[11.707955, 13.224132, 13.669580], [5.860970, 7.379259, 49.711380], [12.661083, 14.476720, 27.244960], [18.753347, 21.844579, 72.361441], [5.294937, 6.510391, 10.804992], [1.038057, 1.161905, 40.801551], [9.612084, 11.874244, 75.128850]]
### 8
fourier: [[15.317404, 15.687568, 39.398314], [6.690980, 7.314833, 42.576638], [7.643964, 7.939635, 8.844454], [2.062313, 2.681012, 33.160825], [1.145424, 1.388218, 17.492651], [0.666687, 0.949846, 28.888455], [15.003334, 16.034844, 56.500820]]
### 10
fourier: [[12.155661, 12.303285, 29.521980]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [11.707955253284023, 13.224132412725199, 13.669580310583115]}, "1": {"fourier": [5.860969616199129, 7.379259238205298, 49.711379647254944]}, "2": {"fourier": [12.661083413227887, 14.476719788313108, 27.244959890842438]}, "3": {"fourier": [18.753347224134085, 21.844579288469063, 72.3614412099123]}, "4": {"fourier": [5.2949371928596545, 6.51039050755388, 10.804992407560349]}, "5": {"fourier": [1.038056799083878, 1.1619051447615105, 40.80155101418495]}, "6": {"fourier": [9.612083936158726, 11.874244406466739, 75.12885010242462]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [15.31740423257139, 15.687568084109797, 39.398314490914345]}, "1": {"fourier": [6.690979803294927, 7.314833009763424, 42.576637610793114]}, "2": {"fourier": [7.643963935198744, 7.939635068167356, 8.844453899726235]}, "3": {"fourier": [2.0623126180299636, 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"degraded_epochs": 4, "improved_epochs": 7, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.696847140789032, "final_val_loss": 0.6585147976875305, "initial_val_acc": 0.48, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.6918662786483765, "final_val_loss": 0.6238958835601807, "initial_val_acc": 0.52, "final_val_acc": 0.68, "best_val_acc": 0.74, "best_epoch": 7}, "improvement": 0.17999999999999994, "first_improvement_epoch": 3}} |
52 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.74, "improved_accuracy": 0.94, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2026, "learning_rate": 0.03338577609673197, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[42.248434, 44.993643, 267.637938], [33.067780, 35.686544, 37.288059], [24.544252, 29.214876, 138.769255], [16.339702, 18.849736, 41.216259], [26.913491, 28.764169, 152.352055], [32.456208, 34.369116, 231.100991], [30.133370, 32.293393, 105.655297], [15.869260, 18.189149, 146.186078]]
### 2
fourier: [[12.614132, 13.867860, 15.428569], [23.190468, 23.748613, 129.041849], [18.565098, 20.356687, 87.997724], [10.859892, 10.995340, 119.569791], [26.349751, 30.198304, 220.453620], [23.485520, 24.587831, 130.945158], [6.314885, 6.977030, 7.021983], [13.441443, 16.091302, 121.088943]]
### 4
fourier: [[25.354782, 27.688641, 199.204117], [14.612386, 15.647733, 48.442220], [25.773829, 28.179728, 110.514081], [16.271123, 19.712499, 183.283947], [15.254911, 17.361379, 85.148343], [16.621012, 17.984954, 177.312230], [23.962886, 26.182629, 112.915932], [14.419550, 14.739115, 107.457368]]
### 6
fourier: [[21.404184, 24.148940, 73.017946], [33.943794, 34.118115, 35.359935], [24.887210, 29.060628, 123.834778], [34.964966, 35.715875, 121.330036], [24.651324, 24.713096, 235.089985], [10.330932, 11.901326, 128.904484], [28.130633, 29.697973, 41.954175], [13.755816, 14.631082, 82.923821]]
### 8
fourier: [[47.269495, 52.973736, 213.476702]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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],
"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[42.248434, 44.993643, 267.637938], [33.067780, 35.686544, 37.288059], [24.544252, 29.214876, 138.769255], [16.339702, 18.849736, 41.216259], [26.913491, 28.764169, 152.352055], [32.456208, 34.369116, 231.100991], [30.133370, 32.293393, 105.655297], [15.869260, 18.189149, 146.186078]]
### 2
fourier: [[12.614132, 13.867860, 15.428569], [23.190468, 23.748613, 129.041849], [18.565098, 20.356687, 87.997724], [10.859892, 10.995340, 119.569791], [26.349751, 30.198304, 220.453620], [23.485520, 24.587831, 130.945158], [6.314885, 6.977030, 7.021983], [13.441443, 16.091302, 121.088943]]
### 4
fourier: [[25.354782, 27.688641, 199.204117], [14.612386, 15.647733, 48.442220], [25.773829, 28.179728, 110.514081], [16.271123, 19.712499, 183.283947], [15.254911, 17.361379, 85.148343], [16.621012, 17.984954, 177.312230], [23.962886, 26.182629, 112.915932], [14.419550, 14.739115, 107.457368]]
### 6
fourier: [[21.404184, 24.148940, 73.017946], [33.943794, 34.118115, 35.359935], [24.887210, 29.060628, 123.834778], [34.964966, 35.715875, 121.330036], [24.651324, 24.713096, 235.089985], [10.330932, 11.901326, 128.904484], [28.130633, 29.697973, 41.954175], [13.755816, 14.631082, 82.923821]]
### 8
fourier: [[47.269495, 52.973736, 213.476702]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [42.248433520639416, 44.99364349544018, 267.63793758675456]}, "1": {"fourier": [33.06777974219399, 35.68654375581085, 37.28805915610518]}, "2": {"fourier": [24.544251553272158, 29.21487646179985, 138.7692551612854]}, "3": {"fourier": [16.339701939554292, 18.849736057026103, 41.216258600354195]}, "4": {"fourier": [26.913490647358632, 28.764169116426963, 152.35205486416817]}, "5": {"fourier": [32.45620765604988, 34.36911644524574, 231.10099110007286]}, "6": {"fourier": [30.133370114405324, 32.293392640632916, 105.6552973985672]}, "7": {"fourier": [15.869260179388425, 18.18914921007118, 146.18607798218727]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [12.614132055608593, 13.867860427274383, 15.428568954811663]}, "1": {"fourier": [23.190467757185754, 23.748613456115375, 129.04184938967228]}, "2": {"fourier": [18.56509798669378, 20.35668708803674, 87.99772426486015]}, "3": {"fourier": [10.859891709956452, 10.995339623028519, 119.56979149580002]}, "4": {"fourier": [26.34975117843149, 30.19830437782837, 220.45361977815628]}, "5": {"fourier": [23.485520269525946, 24.587830736135345, 130.9451580941677]}, "6": {"fourier": [6.314885228872299, 6.977030361125686, 7.02198308572022]}, "7": {"fourier": [13.441442511583743, 16.091301607472865, 121.08894342184067]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [25.354782288764007, 27.68864123174761, 199.20411667227745]}, "1": {"fourier": [14.61238579633487, 15.647733331410766, 48.44222044944763]}, "2": {"fourier": [25.773829385014693, 28.17972836906272, 110.51408052444458]}, "3": {"fourier": [16.271122699581586, 19.712499280115683, 183.28394734859467]}, "4": {"fourier": [15.254911330576046, 17.361378973059978, 85.14834326505661]}, "5": {"fourier": [16.621012173861494, 17.984954056207922, 177.31223011016846]}, "6": {"fourier": [23.96288631455875, 26.182628735849466, 112.91593186557293]}, "7": {"fourier": [14.419550067769958, 14.739115340736237, 107.4573675096035]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [21.404184207690374, 24.148940441804747, 73.01794631779194]}, "1": {"fourier": [33.9437942944761, 34.118114590644836, 35.35993458842196]}, "2": {"fourier": [24.887209875582418, 29.06062779463256, 123.83477847278118]}, "3": {"fourier": [34.96496553919194, 35.71587521665668, 121.33003574609756]}, "4": {"fourier": [24.651324136713654, 24.713096226042648, 235.08998453617096]}, "5": {"fourier": [10.330931790783234, 11.901325641493571, 128.90448427200317]}, "6": {"fourier": [28.13063252266205, 29.697973007849395, 41.95417474210262]}, "7": {"fourier": [13.755816084774208, 14.631081708217403, 82.92382100224495]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [47.2694946145133, 52.97373555046931, 213.4767015427351]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.462254, -0.47006, -0.014951, -0.48518, -0.430504], [-0.020587, 0.348213, -0.671486, 0.353866, -0.257769], [0.234915, -0.228687, 0.451584, 0.300487, 0.254216], [0.129163, 0.4747, -0.092261, -0.134925, 0.031672], [-0.365028, 0.111318, 0.42817, 0.19403, 0.542192], [-0.31739, 0.126688, -0.391787, -0.237109, -0.445633], [0.726824, 0.047418, 0.144674, -0.008557, -0.26643], [-0.033729, 0.401033, 0.002053, 0.083421, 0.249306]], "network.0.bias": [0.060676, 0.157121, -0.234959, -0.124789, -0.034979, -0.527187, 0.227787, 0.444835], "network.2.weight": [[-0.071417, 0.518032, -0.046706, 0.401239, -0.01786, 0.234886, -0.285564, 0.156041], [-0.317515, -0.17621, 0.369757, 0.29465, -0.254378, 0.102579, 0.516856, 0.207786], [0.000438, 0.34152, 0.15348, -0.173602, 0.545589, 0.021001, -0.288874, -0.044668], [-0.308109, 0.025596, -0.016742, -0.203356, -0.326627, -0.027454, -0.052189, -0.124576], [-0.076626, 0.010424, 0.375791, -0.123423, 0.191939, 0.05514, 0.567424, 0.389159], [-0.088543, 0.246174, 0.353697, -0.116174, 0.508008, 0.094645, -0.52461, 0.142899], [0.247442, 0.354704, 0.114346, -0.519661, 0.01265, -0.064576, 0.177132, -0.051725], [-0.230195, -0.181915, -0.207882, -0.086052, 0.289687, 0.15021, 0.434101, 0.42594]], "network.2.bias": [-0.211451, 0.218652, 0.146719, -0.351126, 0.238156, 0.378868, -0.1426, 0.072392], "network.4.weight": [[0.34067, 0.0372, 0.696037, 0.12519, 0.103173, 0.525336, 0.462976, 0.036815], [-0.370389, 0.373603, -0.293629, -0.288586, -0.002499, -0.030302, -0.305362, 0.254665], [-0.494822, 0.555188, -0.207136, 0.123847, 0.310666, -0.351654, -0.165996, 0.119225], [-0.357116, -0.26921, 0.004988, -0.150578, -0.271559, 0.023085, 0.159916, -0.396517], [-0.202233, 0.217002, -0.069587, -0.028912, 0.367976, -0.299563, -0.21309, 0.020521], [0.438132, -0.044742, -0.030684, 0.053187, 0.139097, 0.526742, 0.022863, 0.496889], [-0.319588, 0.496577, -0.526142, -0.344913, 0.144213, -0.05356, -0.262009, 0.583193], [0.102792, 0.132441, 0.375398, -0.1041, 0.469523, -0.091725, 0.429815, -0.283108]], "network.4.bias": [0.086733, 0.199558, 0.464804, -0.417907, 0.350659, 0.099062, 0.206415, -0.140765], "network.6.weight": [[0.001153, 0.238598, 0.255203, -0.492912, 0.368678, 0.129532, 0.363936, -0.425403], [-0.175798, 0.389186, 0.330764, -0.112786, 0.230469, -0.33745, 0.558908, -0.495301], [0.603808, -0.071022, -0.304835, -0.006666, -0.287882, 0.132355, -0.01716, 0.331845], [0.5545, -0.229232, -0.465058, 0.005838, -0.444199, 0.397159, -0.07095, 0.058472], [0.452731, -0.180143, -0.003108, 0.156833, -0.123454, 0.518988, 0.071915, 0.356746], [-0.228126, 0.352602, 0.105652, -0.081566, -0.18236, -0.126499, -0.240213, -0.291854], [-0.257855, 0.284168, 0.499263, -0.563838, 0.222473, -0.088445, 0.203931, -0.397352], [-0.140893, 0.057962, 0.178475, 0.19052, -0.036745, 0.36679, 0.253099, 0.14236]], "network.6.bias": [-0.242355, 0.408477, 0.119757, 0.531378, 0.302933, -0.200708, 0.384087, -0.219557], "network.8.weight": [[0.08625, 0.38367, -0.368916, -0.734345, -0.318585, 0.001178, 0.422326, -0.337922]], "network.8.bias": [-0.235577]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6975021660327911, "train_acc": 0.465, "val_loss": 0.6671959161758423, "val_acc": 0.72}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6571891009807587, "train_acc": 0.655, "val_loss": 0.6217471957206726, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6036905646324158, "train_acc": 0.735, "val_loss": 0.48350411653518677, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.44696804881095886, "train_acc": 0.87, "val_loss": 0.3810785710811615, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.2962309867143631, "train_acc": 0.915, "val_loss": 0.33219677209854126, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.32484276592731476, "train_acc": 0.93, "val_loss": 0.3583541214466095, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.28492702543735504, "train_acc": 0.93, "val_loss": 0.2814509868621826, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.24412710219621658, "train_acc": 0.93, "val_loss": 0.23809976875782013, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.27845434844493866, "train_acc": 0.915, "val_loss": 0.22403313219547272, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.2414628565311432, "train_acc": 0.93, "val_loss": 0.2215646356344223, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.22060757130384445, "train_acc": 0.945, "val_loss": 0.23432494699954987, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.21491804718971252, "train_acc": 0.94, "val_loss": 0.213835671544075, "val_acc": 0.92}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6671959161758423, "final_val_loss": 0.6217471957206726, "initial_val_acc": 0.72, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.48350411653518677, "final_val_loss": 0.213835671544075, "initial_val_acc": 0.88, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 7}, "improvement": 0.19999999999999996, "first_improvement_epoch": 1}} |
53 | {"target_pattern": "has_majority", "degraded_accuracy": 0.54, "improved_accuracy": 0.72, "improvement": 0.17999999999999994, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5859, "learning_rate": 0.048405008971870465, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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[
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-0.153204,
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0.045501
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[
-0.217134,
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],
[
-0.936061,
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0.219462
]
],
"network.0.bias": [
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-0.112363,
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"network.2.weight": [
[
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[
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0.169693,
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[
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0.289234
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[
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[
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[
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]
],
"network.2.bias": [
-0.180422,
-0.268744,
0.160204,
-0.601689,
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],
"network.4.weight": [
[
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[
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[
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[
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[
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0.439815
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[
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],
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[
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0.469047,
0.002542
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[
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[
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[
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"network.6.bias": [
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"network.8.weight": [
[
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[
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[
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[
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0.49388,
0.295381
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[
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],
"network.8.bias": [
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"network.10.weight": [
[
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[
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[
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[
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[
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[
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8e-05
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],
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"network.12.weight": [
[
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[35.986119, 40.681742, 47.534628], [34.695664, 40.110474, 236.654798], [41.170091, 42.753748, 48.253103], [30.022669, 32.602389, 175.663394], [35.202829, 38.490728, 247.990123], [37.685504, 40.124837, 137.970470]]
### 2
fourier: [[10.893411, 11.338594, 84.894026], [12.680940, 15.815916, 80.834135], [46.475953, 48.084157, 333.122370], [25.002610, 25.910060, 229.869673], [22.334779, 24.770139, 189.427271], [35.521000, 37.344628, 234.645447]]
### 4
fourier: [[32.173661, 33.420098, 233.021744], [12.089560, 12.555189, 45.030486], [14.100519, 14.783123, 97.606520], [25.010252, 26.117884, 151.595088], [43.136399, 44.886313, 283.770259], [14.880732, 15.382653, 128.508736]]
### 6
fourier: [[14.432106, 15.012192, 120.122890], [6.643380, 6.788990, 80.543135], [23.439108, 24.501385, 114.243917], [34.583921, 36.074177, 214.227496], [18.867912, 19.721696, 152.491785], [16.666612, 17.335361, 124.914290]]
### 8
fourier: [[21.293596, 22.275673, 149.062632], [20.989987, 21.943830, 142.426805], [14.101625, 14.697246, 59.772795], [22.470718, 23.511756, 103.469913], [7.712232, 8.044971, 119.253835], [19.610040, 20.474851, 94.308244]]
### 10
fourier: [[7.563040, 7.861397, 113.722101], [3.585345, 3.683189, 62.823831], [1.051977, 1.125884, 64.632393], [29.163486, 29.892352, 136.017074], [8.104921, 8.409943, 87.044309], [13.014664, 13.405190, 114.619488]]
### 12
fourier: [[7.329714, 8.530280, 8.700981]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.0.bias": [
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-0.112363,
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"network.2.weight": [
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[
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[
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0.289234
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[
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[
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[
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],
"network.2.bias": [
-0.180422,
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0.160204,
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[
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],
[
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0.211964,
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[
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[
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[
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[
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],
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[
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[
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[35.986119, 40.681742, 47.534628], [34.695664, 40.110474, 236.654798], [41.170091, 42.753748, 48.253103], [30.022669, 32.602389, 175.663394], [35.202829, 38.490728, 247.990123], [37.685504, 40.124837, 137.970470]]
### 2
fourier: [[10.893411, 11.338594, 84.894026], [12.680940, 15.815916, 80.834135], [46.475953, 48.084157, 333.122370], [25.002610, 25.910060, 229.869673], [22.334779, 24.770139, 189.427271], [35.521000, 37.344628, 234.645447]]
### 4
fourier: [[32.173661, 33.420098, 233.021744], [12.089560, 12.555189, 45.030486], [14.100519, 14.783123, 97.606520], [25.010252, 26.117884, 151.595088], [43.136399, 44.886313, 283.770259], [14.880732, 15.382653, 128.508736]]
### 6
fourier: [[14.432106, 15.012192, 120.122890], [6.643380, 6.788990, 80.543135], [23.439108, 24.501385, 114.243917], [34.583921, 36.074177, 214.227496], [18.867912, 19.721696, 152.491785], [16.666612, 17.335361, 124.914290]]
### 8
fourier: [[21.293596, 22.275673, 149.062632], [20.989987, 21.943830, 142.426805], [14.101625, 14.697246, 59.772795], [22.470718, 23.511756, 103.469913], [7.712232, 8.044971, 119.253835], [19.610040, 20.474851, 94.308244]]
### 10
fourier: [[7.563040, 7.861397, 113.722101], [3.585345, 3.683189, 62.823831], [1.051977, 1.125884, 64.632393], [29.163486, 29.892352, 136.017074], [8.104921, 8.409943, 87.044309], [13.014664, 13.405190, 114.619488]]
### 12
fourier: [[7.329714, 8.530280, 8.700981]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [35.98611902449191, 40.68174189342407, 47.534628203281216]}, "1": {"fourier": [34.69566390163443, 40.11047376158656, 236.65479750186205]}, "2": {"fourier": [41.1700907782468, 42.75374842458221, 48.25310254766698]}, "3": {"fourier": [30.02266899795884, 32.60238865884339, 175.66339415311813]}, "4": {"fourier": [35.20282897880432, 38.49072780422752, 247.99012319743633]}, "5": {"fourier": [37.68550434481877, 40.124836844256514, 137.9704704619944]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [10.89341056792439, 11.338594298486548, 84.89402598142624]}, "1": {"fourier": [12.680939987308403, 15.815916211280703, 80.83413492143154]}, "2": {"fourier": [46.47595288443425, 48.084157496236365, 333.12236964702606]}, "3": {"fourier": [25.002609831895764, 25.91006022138738, 229.8696728348732]}, "4": {"fourier": [22.33477875431166, 24.77013915408196, 189.42727074027061]}, "5": {"fourier": [35.52099991487987, 37.344628367238435, 234.6454466432333]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [32.17366128385782, 33.420098113050436, 233.0217443406582]}, "1": {"fourier": [12.089559727691137, 12.555188798061636, 45.03048551082611]}, "2": {"fourier": [14.100519128628083, 14.783122716766819, 97.60652000829577]}, "3": {"fourier": [25.01025189308396, 26.117884096781218, 151.59508788585663]}, "4": {"fourier": [43.13639876805972, 44.88631303732166, 283.77025850862265]}, "5": {"fourier": [14.880731761116014, 15.382652814322029, 128.50873559713364]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [14.432105827256235, 15.012192195686493, 120.1228897869587]}, "1": {"fourier": [6.643379973015702, 6.788990109895933, 80.54313546419144]}, "2": {"fourier": [23.43910769561518, 24.5013848786647, 114.2439172565937]}, "3": {"fourier": [34.583921253942, 36.07417672538808, 214.22749646008015]}, "4": {"fourier": [18.867911799079536, 19.721695549850057, 152.49178516864777]}, "5": {"fourier": [16.666611732951086, 17.335361333582743, 124.91429018974304]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [21.29359571905429, 22.275672827162172, 149.06263242661953]}, "1": {"fourier": [20.989986689967388, 21.94383020015787, 142.42680453509092]}, "2": {"fourier": [14.101624545456769, 14.69724570996015, 59.77279481291771]}, "3": {"fourier": [22.47071782295423, 23.511755547678273, 103.46991297602654]}, "4": {"fourier": [7.712232012342013, 8.044971344813442, 119.2538350224495]}, "5": {"fourier": [19.610040429521646, 20.474851138249416, 94.30824440717697]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [7.563040218884127, 7.861397332545598, 113.7221006155014]}, "1": {"fourier": [3.5853453992078195, 3.6831889703099265, 62.82383105158806]}, "2": {"fourier": [1.0519774430900777, 1.1258836129644876, 64.63239341974258]}, "3": {"fourier": [29.163485597965902, 29.892352178824463, 136.01707377284765]}, "4": {"fourier": [8.104921423003828, 8.409943209081302, 87.04430869221687]}, "5": {"fourier": [13.014663797344447, 13.405190184517581, 114.6194879412651]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [7.329714284204936, 8.530280102097386, 8.700981213763022]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 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0.54, "final_val_acc": 0.66, "best_val_acc": 0.72, "best_epoch": 12}, "improvement": 0.17999999999999994, "first_improvement_epoch": 4}} |
54 | {"target_pattern": "has_majority", "degraded_accuracy": 0.54, "improved_accuracy": 0.82, "improvement": 0.2799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8445, "learning_rate": 0.09004911743914298, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[28.731690, 46.019346, 201.021640], [26.054197, 31.740677, 32.272342], [30.494894, 34.023348, 242.774162], [41.546503, 42.002963, 295.718164], [27.121587, 33.919425, 55.534800], [47.427221, 53.321975, 376.902681], [35.212672, 38.600170, 194.233325], [20.843258, 21.066976, 108.786522]]
### 2
fourier: [[72.566369, 74.685231, 571.288109], [60.579054, 63.882686, 469.614553], [15.068031, 17.279104, 23.847053], [52.293353, 57.416837, 394.685425], [16.214738, 18.324660, 133.917615], [74.271668, 75.537700, 585.207061], [36.333411, 36.551551, 235.871686], [55.301412, 60.626339, 371.067739]]
### 4
fourier: [[12.358231, 12.419340, 50.258940], [10.008511, 10.058301, 86.575768], [11.960857, 13.134102, 94.800729], [9.124864, 9.289482, 52.628056], [16.212464, 17.368287, 70.291920], [21.233212, 22.969930, 114.950684], [21.398139, 21.450171, 203.751134], [14.684408, 15.404748, 77.672559]]
### 6
fourier: [[22.196873, 23.385474, 103.892174], [3.244442, 3.406088, 44.537713], [15.969773, 16.747558, 89.861250], [10.223337, 10.312704, 40.364238], [16.576618, 17.299454, 49.856871], [17.671103, 18.003311, 28.989541], [14.663423, 14.969953, 54.406657], [14.204075, 14.277652, 79.676407]]
### 8
fourier: [[2.816318, 3.844787, 20.918269], [6.443585, 7.649579, 50.599327], [8.585132, 9.909892, 11.232726], [12.576460, 13.585174, 20.118619], [24.547211, 25.964716, 122.639184], [12.313443, 13.359113, 25.911948], [8.998873, 9.233453, 25.738298], [6.101422, 6.454745, 13.474717]]
### 10
fourier: [[14.633005, 15.608730, 26.441697]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
0.301715,
0.200831,
0.159707,
-0.048514,
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-0.234166,
0.288475,
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],
[
-0.376849,
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0.02382,
0.285778,
0.275034,
0.1251,
-0.410248,
0.456349
],
[
0.196569,
-0.345602,
-0.031006,
-0.14999,
-0.108604,
-0.272771,
0.234914,
-0.190938
]
],
"network.8.bias": [
0.12415,
-0.166943,
0.524987,
0.216289,
0.242227,
-0.135871,
-0.045749,
-0.044547
],
"network.10.weight": [
[
0.001183,
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0.246116,
0.19549,
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-0.222811,
0.274562,
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]
],
"network.10.bias": [
0.234619
]
}
## Activation Signature
### 0
fourier: [[28.731690, 46.019346, 201.021640], [26.054197, 31.740677, 32.272342], [30.494894, 34.023348, 242.774162], [41.546503, 42.002963, 295.718164], [27.121587, 33.919425, 55.534800], [47.427221, 53.321975, 376.902681], [35.212672, 38.600170, 194.233325], [20.843258, 21.066976, 108.786522]]
### 2
fourier: [[72.566369, 74.685231, 571.288109], [60.579054, 63.882686, 469.614553], [15.068031, 17.279104, 23.847053], [52.293353, 57.416837, 394.685425], [16.214738, 18.324660, 133.917615], [74.271668, 75.537700, 585.207061], [36.333411, 36.551551, 235.871686], [55.301412, 60.626339, 371.067739]]
### 4
fourier: [[12.358231, 12.419340, 50.258940], [10.008511, 10.058301, 86.575768], [11.960857, 13.134102, 94.800729], [9.124864, 9.289482, 52.628056], [16.212464, 17.368287, 70.291920], [21.233212, 22.969930, 114.950684], [21.398139, 21.450171, 203.751134], [14.684408, 15.404748, 77.672559]]
### 6
fourier: [[22.196873, 23.385474, 103.892174], [3.244442, 3.406088, 44.537713], [15.969773, 16.747558, 89.861250], [10.223337, 10.312704, 40.364238], [16.576618, 17.299454, 49.856871], [17.671103, 18.003311, 28.989541], [14.663423, 14.969953, 54.406657], [14.204075, 14.277652, 79.676407]]
### 8
fourier: [[2.816318, 3.844787, 20.918269], [6.443585, 7.649579, 50.599327], [8.585132, 9.909892, 11.232726], [12.576460, 13.585174, 20.118619], [24.547211, 25.964716, 122.639184], [12.313443, 13.359113, 25.911948], [8.998873, 9.233453, 25.738298], [6.101422, 6.454745, 13.474717]]
### 10
fourier: [[14.633005, 15.608730, 26.441697]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [28.73168955918125, 46.019346389921765, 201.02164040505886]}, "1": {"fourier": [26.0541974172671, 31.740676805331297, 32.27234211564064]}, "2": {"fourier": [30.494894206389507, 34.02334803498714, 242.7741623520851]}, "3": {"fourier": [41.54650275585106, 42.00296322600249, 295.7181643843651]}, "4": {"fourier": [27.121587120329423, 33.91942504081082, 55.53479966521263]}, "5": {"fourier": [47.42722059711043, 53.32197505355495, 376.9026805758476]}, "6": {"fourier": [35.21267183628874, 38.600170346868495, 194.23332497477531]}, "7": {"fourier": [20.843257502443205, 21.06697585533757, 108.78652191907167]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [72.56636882562543, 74.68523051969996, 571.2881089448929]}, "1": {"fourier": [60.57905425000592, 63.88268604704809, 469.61455261707306]}, "2": {"fourier": [15.068031290291485, 17.279103764246965, 23.84705263376236]}, "3": {"fourier": [52.293353104838594, 57.416836993184795, 394.6854246854782]}, "4": {"fourier": [16.214738232942505, 18.324660065541195, 133.91761535406113]}, "5": {"fourier": [74.27166809843516, 75.53770034378067, 585.2070605158806]}, "6": {"fourier": [36.33341071453019, 36.551551265269744, 235.8716855943203]}, "7": {"fourier": [55.30141231357409, 60.626338568236136, 371.0677388012409]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [12.358230701495296, 12.419340389640487, 50.258939534425735]}, "1": {"fourier": [10.008511281564887, 10.05830053062719, 86.57576754689217]}, "2": {"fourier": [11.960856866436764, 13.134101834421912, 94.80072945356369]}, "3": {"fourier": [9.124863859039703, 9.289482041898621, 52.628055572509766]}, "4": {"fourier": [16.212463766648575, 17.36828662023273, 70.29192023910582]}, "5": {"fourier": [21.23321210072888, 22.96993031784021, 114.95068396627903]}, "6": {"fourier": [21.39813911270522, 21.45017096897846, 203.7511335015297]}, "7": {"fourier": [14.6844080119039, 15.404747726979657, 77.6725587695837]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [22.196873110610436, 23.38547436350945, 103.892174474895]}, "1": {"fourier": [3.244442498515673, 3.40608803503817, 44.53771349787712]}, "2": {"fourier": [15.969773048761535, 16.747557625518088, 89.86125006526709]}, "3": {"fourier": [10.223337369415908, 10.312703703635048, 40.36423820257187]}, "4": {"fourier": [16.57661795684372, 17.299453767326916, 49.85687121003866]}, "5": {"fourier": [17.67110307728135, 18.0033109877173, 28.98954063653946]}, "6": {"fourier": [14.663422722019, 14.969953093262012, 54.406657479703426]}, "7": {"fourier": [14.204074898298188, 14.277652261845196, 79.67640671133995]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [2.8163180839787914, 3.844786555035324, 20.918269142508507]}, "1": {"fourier": [6.443584861413389, 7.649579389682289, 50.59932716190815]}, "2": {"fourier": [8.585132003980306, 9.909891939195251, 11.232725522664024]}, "3": {"fourier": [12.576459948231195, 13.58517412522855, 20.118618607521057]}, "4": {"fourier": [24.54721142940171, 25.964716402287802, 122.6391836553812]}, "5": {"fourier": [12.313443330509816, 13.359112799834943, 25.911948069930077]}, "6": {"fourier": [8.998873410788326, 9.233452709655069, 25.738298069685698]}, "7": {"fourier": [6.101421610336196, 6.454744683804869, 13.474716931581497]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [14.633004748778525, 15.608729545145295, 26.441697254776955]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.28555, -0.585842, -0.75365, 0.223227, -0.318473], [0.390674, -0.547687, -0.289123, 0.483498, -0.494426], [0.063819, 0.8327, -0.013864, 0.040511, 0.2056], [-0.125027, 0.864264, 0.673288, 0.105641, -0.345485], [-0.274279, 0.563073, 0.007496, -0.860526, 0.190974], [-0.11775, 0.958508, 0.663092, 0.066207, 0.497201], [-0.022728, 0.587926, 0.072356, 0.552019, 0.141062], [0.389843, -0.175592, 0.188674, 0.31038, -0.000399]], "network.0.bias": [-0.033013, 0.330157, 0.789219, 0.659598, 0.292383, 0.447408, -0.393794, -0.015652], "network.2.weight": [[0.155608, -0.058904, -0.821688, -1.022754, 0.257736, -0.270561, 0.125554, -0.086035], [-0.11311, -0.098404, -0.69032, -0.139635, -0.273691, -0.319631, -0.457735, -0.326293], [-0.432644, 0.207913, -0.306255, 0.21515, 0.088273, 0.365568, -0.552945, 0.158325], [0.507438, 0.171937, -0.612509, -0.101586, 0.213935, -0.549051, -0.304922, 0.228154], [-0.405909, 0.062907, -0.166579, -0.165713, -0.715047, 0.016667, -0.088264, 0.155718], [-0.254419, -0.4901, -0.452683, -0.396663, -0.211995, -0.227873, -0.641117, -0.912921], [-0.323057, -0.132185, -0.476141, 0.365602, -0.596992, 0.396842, 0.436044, 0.401694], [0.352967, 0.516298, -0.532285, -0.311629, 0.027794, -0.621049, -0.058326, 0.459311]], "network.2.bias": [0.055204, -0.153831, -0.243659, 0.128319, -0.398743, -0.43483, -0.147643, 0.299864], "network.4.weight": [[0.416816, 0.038007, 0.116814, 0.694459, -0.377417, 0.126791, -0.333282, 0.682632], [-0.032255, 0.34944, 0.319036, -0.263415, 0.066047, 0.350672, 0.260194, -0.581387], [0.030874, 0.701526, 0.310916, 0.607645, 0.030159, -0.404569, -0.338526, 0.178454], [-0.17792, 0.378919, 0.718673, 0.113415, 0.037629, -0.422878, 0.023785, 0.354603], [0.080875, 0.170766, -0.69538, -0.004985, 0.128942, 0.3107, 0.398145, -0.598106], [0.221196, -0.014504, -0.82754, -0.216401, -0.104368, 0.380573, 0.541412, -0.677297], [-0.806997, -0.363915, -0.21169, 0.124288, -0.015158, 0.315729, -0.578132, -0.230187], [0.26194, 0.120044, -0.244206, 0.201601, -0.022065, -0.047956, 0.387993, -0.214002]], "network.4.bias": [0.281042, 0.169975, -0.24208, 0.279367, -0.000279, 0.134996, -0.700738, -0.057568], "network.6.weight": [[-0.111728, 0.360191, -0.036835, -0.108012, 0.256062, 0.56136, -0.093863, 0.192866], [-0.151732, 0.085939, 0.273134, -0.297613, -0.116976, 0.089507, 0.448955, -0.326165], [-0.341048, 0.074102, -0.351854, 0.015842, 0.269465, 0.394833, -0.134617, 0.170126], [0.270858, 0.226148, 0.3568, 0.54347, -0.043089, -0.148902, -0.564998, -0.427032], [0.706572, -0.085923, 0.022287, 0.28483, -0.291831, -0.368317, -0.586737, -0.091869], [0.36832, 0.209231, 0.137012, 0.32513, -0.222233, -0.535954, -0.478629, -0.161856], [-0.40172, -0.051807, 0.050888, -0.204599, 0.305241, 0.397133, 0.598573, -0.009383], [0.109591, 0.400216, 0.494332, 0.032112, 0.193637, 0.100241, 0.397715, 0.315627]], "network.6.bias": [-0.128859, -0.148539, 0.05003, -0.319375, 0.131063, 0.295449, 0.065541, 0.1174], "network.8.weight": [[-0.276623, 0.283873, 0.351986, 0.058593, -0.329713, -0.249562, -0.154653, 0.317008], [-0.267166, 0.31809, -0.034193, -0.36067, -0.358363, -0.434219, 0.483574, -0.34291], [-0.142642, -0.038954, -0.669077, 0.124354, 0.504207, 0.211518, 0.224927, 0.209702], [-0.390305, -0.363273, -0.301053, 0.029567, 0.728059, 0.096461, -0.193203, 0.388256], [0.276055, -0.013297, 0.449237, -0.201499, 0.07606, -0.482161, 0.394831, 0.299453], [0.301715, 0.200831, 0.159707, -0.048514, -0.572869, -0.234166, 0.288475, -0.202855], [-0.376849, -0.144325, 0.02382, 0.285778, 0.275034, 0.1251, -0.410248, 0.456349], [0.196569, -0.345602, -0.031006, -0.14999, -0.108604, -0.272771, 0.234914, -0.190938]], "network.8.bias": [0.12415, -0.166943, 0.524987, 0.216289, 0.242227, -0.135871, -0.045749, -0.044547], "network.10.weight": [[0.001183, -0.03051, 0.246116, 0.19549, -0.364823, -0.222811, 0.274562, -0.243259]], "network.10.bias": [0.234619]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6828401982784271, "train_acc": 0.56, "val_loss": 0.7498663067817688, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6914920210838318, "train_acc": 0.605, "val_loss": 0.6856942176818848, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6473208665847778, "train_acc": 0.63, "val_loss": 0.6439201235771179, "val_acc": 0.66}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6624739766120911, "train_acc": 0.58, "val_loss": 0.6628423929214478, "val_acc": 0.52}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6117184460163116, "train_acc": 0.635, "val_loss": 0.47310179471969604, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.6075247824192047, "train_acc": 0.72, "val_loss": 0.523557722568512, "val_acc": 0.8}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.5501480102539062, "train_acc": 0.725, "val_loss": 0.5391753911972046, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.47812631726264954, "train_acc": 0.78, "val_loss": 0.6680401563644409, "val_acc": 0.62}], "summary": {"total_epochs": 8, "degraded_epochs": 2, "improved_epochs": 6, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.7498663067817688, "final_val_loss": 0.6856942176818848, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.6439201235771179, "final_val_loss": 0.6680401563644409, "initial_val_acc": 0.66, "final_val_acc": 0.62, "best_val_acc": 0.82, "best_epoch": 4}, "improvement": 0.2799999999999999, "first_improvement_epoch": 1}} |
55 | {"target_pattern": "starts_with", "degraded_accuracy": 0.62, "improved_accuracy": 0.8, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5609, "learning_rate": 0.04155050612345397, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.bias": [
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}
## Activation Signature
### 0
fourier: [[49.117815, 53.755822, 156.044204], [29.953877, 31.714832, 38.857228], [38.882452, 42.833324, 122.454365], [29.687239, 30.240255, 55.078020], [31.211182, 33.550010, 156.551609]]
### 2
fourier: [[30.921098, 32.021070, 208.659713], [50.184823, 50.999480, 93.021193], [38.946552, 40.252014, 41.000012], [46.076442, 46.178512, 86.698846], [63.874545, 70.515442, 267.060197]]
### 4
fourier: [[49.095740, 53.550392, 213.534436], [42.027909, 45.641997, 186.531335], [26.771939, 28.171716, 162.299069], [51.413750, 53.075105, 102.775375], [37.288656, 39.068676, 40.143562]]
### 6
fourier: [[34.970646, 38.316890, 116.033712], [14.483786, 14.634918, 96.332936], [16.923744, 18.872049, 18.926958], [64.946946, 69.022041, 280.870469], [47.478199, 48.478043, 71.504896]]
### 8
fourier: [[37.731310, 38.312436, 89.952149], [38.360169, 42.735766, 216.389348], [49.812599, 52.065442, 154.397953], [70.767097, 74.643488, 225.112700], [36.962474, 40.453164, 184.075358]]
### 10
fourier: [[11.891939, 12.620869, 41.860061]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
1.199316,
0.346023,
0.118716,
-0.090623,
-0.313053
],
[
0.33699,
0.110098,
0.106995,
-0.011822,
-1.023327
],
[
0.875188,
0.46311,
0.092592,
-0.127461,
-0.277123
],
[
0.103128,
-0.903653,
0.01748,
0.259915,
0.248211
],
[
-0.678456,
0.805619,
0.360814,
-0.245232,
0.418553
]
],
"network.0.bias": [
-0.056738,
0.301644,
-0.150702,
0.00633,
0.371716
],
"network.2.weight": [
[
0.011806,
-0.713898,
-0.226646,
0.470132,
-0.770876
],
[
-0.462608,
-0.687542,
-0.494703,
-0.537144,
0.417811
],
[
0.531417,
0.464928,
0.129131,
0.016394,
-0.506493
],
[
-0.497279,
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-0.377308,
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0.346321
],
[
0.813826,
0.673252,
0.612856,
-0.206453,
0.02385
]
],
"network.2.bias": [
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0.421734,
-0.269917,
0.397352,
0.088315
],
"network.4.weight": [
[
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0.058327,
0.054716,
0.714583
],
[
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-0.287707,
0.627278
],
[
-0.41191,
0.188738,
0.226671,
-0.538232,
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],
[
0.267107,
0.710451,
-0.05924,
0.090857,
-0.659862
],
[
0.160904,
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]
],
"network.4.bias": [
0.28752,
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-0.337747,
0.569682,
0.341279
],
"network.6.weight": [
[
0.457667,
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0.075668
],
[
-0.168516,
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0.143311,
-0.262053
],
[
-0.281143,
0.415985,
0.280862,
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-0.697183
],
[
0.722503,
0.544831,
0.108565,
-0.33238,
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],
[
-0.295347,
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-0.197181,
0.608934,
0.691389
]
],
"network.6.bias": [
-0.214792,
-0.226145,
0.302102,
0.60196,
0.019671
],
"network.8.weight": [
[
-0.520216,
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0.178966,
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0.672861
],
[
-0.344243,
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-0.264751,
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],
[
0.241657,
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],
[
-0.114834,
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0.542533
],
[
-0.435454,
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]
],
"network.8.bias": [
-0.116593,
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0.439108,
0.386635,
-0.118129
],
"network.10.weight": [
[
0.366371,
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0.396457,
0.316845,
-0.048581
]
],
"network.10.bias": [
-0.778853
]
}
## Activation Signature
### 0
fourier: [[49.117815, 53.755822, 156.044204], [29.953877, 31.714832, 38.857228], [38.882452, 42.833324, 122.454365], [29.687239, 30.240255, 55.078020], [31.211182, 33.550010, 156.551609]]
### 2
fourier: [[30.921098, 32.021070, 208.659713], [50.184823, 50.999480, 93.021193], [38.946552, 40.252014, 41.000012], [46.076442, 46.178512, 86.698846], [63.874545, 70.515442, 267.060197]]
### 4
fourier: [[49.095740, 53.550392, 213.534436], [42.027909, 45.641997, 186.531335], [26.771939, 28.171716, 162.299069], [51.413750, 53.075105, 102.775375], [37.288656, 39.068676, 40.143562]]
### 6
fourier: [[34.970646, 38.316890, 116.033712], [14.483786, 14.634918, 96.332936], [16.923744, 18.872049, 18.926958], [64.946946, 69.022041, 280.870469], [47.478199, 48.478043, 71.504896]]
### 8
fourier: [[37.731310, 38.312436, 89.952149], [38.360169, 42.735766, 216.389348], [49.812599, 52.065442, 154.397953], [70.767097, 74.643488, 225.112700], [36.962474, 40.453164, 184.075358]]
### 10
fourier: [[11.891939, 12.620869, 41.860061]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [49.11781511530454, 53.7558216593179, 156.04420355707407]}, "1": {"fourier": [29.953876619557718, 31.714832079073755, 38.857228103178244]}, "2": {"fourier": [38.88245159476519, 42.833324003965274, 122.45436516404152]}, "3": {"fourier": [29.6872392356136, 30.24025463734684, 55.07801981922239]}, "4": {"fourier": [31.211181701519454, 33.55000962269357, 156.5516091287136]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [30.921097665290905, 32.02106977173684, 208.65971302986145]}, "1": {"fourier": [50.184822986410815, 50.99948019580759, 93.02119329571724]}, "2": {"fourier": [38.94655216464244, 40.25201352981607, 41.00001196085369]}, "3": {"fourier": [46.076441710914, 46.178512360044486, 86.69884563982487]}, "4": {"fourier": [63.87454518696414, 70.51544197400476, 267.0601969882846]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [49.095740364076846, 53.5503921291193, 213.5344357341528]}, "1": {"fourier": [42.02790878648714, 45.64199744234807, 186.5313346683979]}, "2": {"fourier": [26.771938549905734, 28.171715593888244, 162.29906886816025]}, "3": {"fourier": [51.413749578087916, 53.07510473892992, 102.77537542581558]}, "4": {"fourier": [37.288655920749086, 39.068676138421715, 40.14356184719285]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [34.970645577378285, 38.31689049438891, 116.03371166437864]}, "1": {"fourier": [14.48378625718166, 14.634917744450723, 96.33293631672859]}, "2": {"fourier": [16.92374412726628, 18.872048674783567, 18.92695823124482]}, "3": {"fourier": [64.94694614574703, 69.02204057650927, 280.870469301939]}, "4": {"fourier": [47.47819903922763, 48.478043459757416, 71.50489643681794]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [37.7313098863389, 38.31243602507206, 89.95214875787497]}, "1": {"fourier": [38.36016924641723, 42.735766039286986, 216.3893479704857]}, "2": {"fourier": [49.81259879918104, 52.06544215175405, 154.39795315265656]}, "3": {"fourier": [70.76709718417848, 74.64348796577603, 225.11270035803318]}, "4": {"fourier": [36.96247370793383, 40.453163581656135, 184.07535821199417]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [11.891938852606017, 12.620869483663325, 41.86006140708923]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[1.199316, 0.346023, 0.118716, -0.090623, -0.313053], [0.33699, 0.110098, 0.106995, -0.011822, -1.023327], [0.875188, 0.46311, 0.092592, -0.127461, -0.277123], [0.103128, -0.903653, 0.01748, 0.259915, 0.248211], [-0.678456, 0.805619, 0.360814, -0.245232, 0.418553]], "network.0.bias": [-0.056738, 0.301644, -0.150702, 0.00633, 0.371716], "network.2.weight": [[0.011806, -0.713898, -0.226646, 0.470132, -0.770876], [-0.462608, -0.687542, -0.494703, -0.537144, 0.417811], [0.531417, 0.464928, 0.129131, 0.016394, -0.506493], [-0.497279, -0.594569, -0.377308, -0.361685, 0.346321], [0.813826, 0.673252, 0.612856, -0.206453, 0.02385]], "network.2.bias": [-0.249789, 0.421734, -0.269917, 0.397352, 0.088315], "network.4.weight": [[-0.348403, -0.292447, 0.058327, 0.054716, 0.714583], [-0.349616, -0.010489, -0.008079, -0.287707, 0.627278], [-0.41191, 0.188738, 0.226671, -0.538232, -0.521621], [0.267107, 0.710451, -0.05924, 0.090857, -0.659862], [0.160904, 0.769523, -0.485709, 0.688509, -0.218014]], "network.4.bias": [0.28752, 0.313592, -0.337747, 0.569682, 0.341279], "network.6.weight": [[0.457667, 0.25694, -0.04986, -0.37988, 0.075668], [-0.168516, -0.160791, -0.523988, 0.143311, -0.262053], [-0.281143, 0.415985, 0.280862, -0.31033, -0.697183], [0.722503, 0.544831, 0.108565, -0.33238, -0.279909], [-0.295347, -0.40276, -0.197181, 0.608934, 0.691389]], "network.6.bias": [-0.214792, -0.226145, 0.302102, 0.60196, 0.019671], "network.8.weight": [[-0.520216, -0.007706, 0.178966, -0.187276, 0.672861], [-0.344243, -0.139729, -0.264751, -0.430239, -0.072981], [0.241657, -0.256911, -0.489947, -0.793095, 0.338745], [-0.114834, -0.244875, -0.136765, -0.936168, 0.542533], [-0.435454, 0.187248, -0.108815, -0.37282, -0.135924]], "network.8.bias": [-0.116593, -0.410874, 0.439108, 0.386635, -0.118129], "network.10.weight": [[0.366371, -0.055765, 0.396457, 0.316845, -0.048581]], "network.10.bias": [-0.778853]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6971242725849152, "train_acc": 0.46, "val_loss": 0.6922775506973267, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6808365881443024, "train_acc": 0.58, "val_loss": 0.6968615055084229, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6779224872589111, "train_acc": 0.58, "val_loss": 0.6950721740722656, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6728082597255707, "train_acc": 0.58, "val_loss": 0.6883139610290527, "val_acc": 0.5}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6614308059215546, "train_acc": 0.58, "val_loss": 0.6515952348709106, "val_acc": 0.62}, {"stage": "improved", "epoch": 0, 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"train_acc": 0.805, "val_loss": 0.5156558752059937, "val_acc": 0.8}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.5075401365756989, "train_acc": 0.82, "val_loss": 0.5256995558738708, "val_acc": 0.78}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.48595456779003143, "train_acc": 0.825, "val_loss": 0.535417914390564, "val_acc": 0.72}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.4711920917034149, "train_acc": 0.82, "val_loss": 0.5190434455871582, "val_acc": 0.76}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.6922775506973267, "final_val_loss": 0.6515952348709106, "initial_val_acc": 0.5, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.6131184101104736, "final_val_loss": 0.5190434455871582, "initial_val_acc": 0.68, "final_val_acc": 0.76, "best_val_acc": 0.8, "best_epoch": 11}, "improvement": 0.18000000000000005, "first_improvement_epoch": 4}} |
56 | {"target_pattern": "palindrome", "degraded_accuracy": 0.72, "improved_accuracy": 0.88, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2987, "learning_rate": 0.01022236864752753, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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[
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[
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[
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[
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[
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"network.4.weight": [
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[
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[
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0.095304,
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0.087496,
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[
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[
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0.451597,
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0.609555,
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]
],
"network.8.bias": [
-0.084119
]
}
## Activation Signature
### 0
fourier: [[20.931184, 25.215925, 188.924049], [24.086308, 24.957924, 57.726382], [22.715803, 28.267973, 36.917548], [27.604825, 29.290956, 97.439948], [10.037771, 10.917644, 108.247097], [33.131574, 36.471809, 47.030337], [37.939021, 41.021600, 147.178184]]
### 2
fourier: [[10.943251, 13.588142, 16.457443], [19.314277, 21.030232, 101.397426], [9.001711, 10.802812, 65.560063], [11.405170, 13.902458, 87.061895], [13.348150, 14.304478, 19.412293], [25.978691, 27.075626, 27.585849], [26.776161, 31.166895, 35.197602]]
### 4
fourier: [[13.786717, 14.096518, 16.685674], [2.240568, 3.486877, 60.644402], [9.590088, 10.612439, 41.807933], [11.504252, 12.029601, 25.391395], [10.911405, 11.124083, 59.806616], [16.724732, 18.958361, 21.646177], [16.335304, 17.506651, 19.338412]]
### 6
fourier: [[3.546786, 3.994871, 50.370107], [10.957522, 11.175189, 83.775760], [17.864180, 20.460317, 20.604215], [16.147692, 18.224677, 20.879113], [9.284747, 11.598136, 13.297070], [16.696253, 19.089867, 20.124338], [21.607383, 23.812970, 78.450215]]
### 8
fourier: [[30.439268, 33.994825, 52.132434]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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],
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],
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],
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],
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],
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]
],
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],
"network.2.weight": [
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],
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]
],
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],
"network.4.weight": [
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[
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],
"network.8.weight": [
[
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0.609555,
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]
],
"network.8.bias": [
-0.084119
]
}
## Activation Signature
### 0
fourier: [[20.931184, 25.215925, 188.924049], [24.086308, 24.957924, 57.726382], [22.715803, 28.267973, 36.917548], [27.604825, 29.290956, 97.439948], [10.037771, 10.917644, 108.247097], [33.131574, 36.471809, 47.030337], [37.939021, 41.021600, 147.178184]]
### 2
fourier: [[10.943251, 13.588142, 16.457443], [19.314277, 21.030232, 101.397426], [9.001711, 10.802812, 65.560063], [11.405170, 13.902458, 87.061895], [13.348150, 14.304478, 19.412293], [25.978691, 27.075626, 27.585849], [26.776161, 31.166895, 35.197602]]
### 4
fourier: [[13.786717, 14.096518, 16.685674], [2.240568, 3.486877, 60.644402], [9.590088, 10.612439, 41.807933], [11.504252, 12.029601, 25.391395], [10.911405, 11.124083, 59.806616], [16.724732, 18.958361, 21.646177], [16.335304, 17.506651, 19.338412]]
### 6
fourier: [[3.546786, 3.994871, 50.370107], [10.957522, 11.175189, 83.775760], [17.864180, 20.460317, 20.604215], [16.147692, 18.224677, 20.879113], [9.284747, 11.598136, 13.297070], [16.696253, 19.089867, 20.124338], [21.607383, 23.812970, 78.450215]]
### 8
fourier: [[30.439268, 33.994825, 52.132434]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [20.931184075114047, 25.215925236198157, 188.92404943704605]}, "1": {"fourier": [24.086308382505415, 24.957924369529525, 57.7263822555542]}, "2": {"fourier": [22.715803003054408, 28.26797340087627, 36.91754846274853]}, "3": {"fourier": [27.60482477699358, 29.29095646151863, 97.43994788080454]}, "4": {"fourier": [10.037770602467715, 10.91764449491202, 108.24709665775299]}, "5": {"fourier": [33.1315743978474, 36.47180885625822, 47.0303370654583]}, "6": {"fourier": [37.93902061636706, 41.02160049097092, 147.1781843751669]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [10.943250918606827, 13.588142233824517, 16.45744302123785]}, "1": {"fourier": [19.3142768122323, 21.030232183376086, 101.39742647111416]}, "2": {"fourier": [9.001710515414782, 10.802811598986825, 65.56006273627281]}, "3": {"fourier": [11.405169616145681, 13.902457945062324, 87.0618950650096]}, "4": {"fourier": [13.348149569532762, 14.304477742824421, 19.412293434143066]}, "5": {"fourier": [25.978690513209138, 27.075625909980182, 27.58584902409926]}, "6": {"fourier": [26.77616057696135, 31.16689547476985, 35.19760225759598]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [13.786717161536217, 14.096517684414263, 16.68567409683047]}, "1": {"fourier": [2.240567596074035, 3.4868769045961754, 60.64440155029297]}, "2": {"fourier": [9.590088110345617, 10.612438767175252, 41.807933285832405]}, "3": {"fourier": [11.504251680519964, 12.029600616491187, 25.3913952447474]}, "4": {"fourier": [10.911404862526172, 11.124082927864073, 59.80661576986313]}, "5": {"fourier": [16.72473178938123, 18.958360608203947, 21.646176814246626]}, "6": {"fourier": [16.3353039039583, 17.50665099259371, 19.338412197502954]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [3.546785857629442, 3.994870762471807, 50.37010742723942]}, "1": {"fourier": [10.957522177245012, 11.175189108071818, 83.77575995028019]}, "2": {"fourier": [17.864179524669538, 20.460316881292638, 20.6042148321867]}, "3": {"fourier": [16.147691696347067, 18.22467730969061, 20.879112576884108]}, "4": {"fourier": [9.284746858886532, 11.598135830099837, 13.29707027016378]}, "5": {"fourier": [16.696252585688853, 19.089867163151112, 20.124337777495384]}, "6": {"fourier": [21.607382702188204, 23.812970225198377, 78.45021511614323]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [30.439267726635883, 33.99482513747507, 52.1324335411191]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.149192, 0.187407, 0.460893, 0.018637, 0.044154], [-0.235778, 0.428793, 0.49593, -0.359947, -0.22616], [0.269656, 0.390936, -0.367926, 0.032698, -0.20413], [0.511372, 0.288534, -0.010094, -0.160405, 0.332055], [-0.107126, -0.051134, 0.197752, 0.214929, -0.001931], [-0.368504, 0.27373, -0.33224, 0.270069, -0.580542], [0.531364, -0.244383, 0.058409, 0.404011, 0.623384]], "network.0.bias": [0.514823, 0.168335, 0.312447, -0.123953, 0.557631, 0.26809, -0.337848], "network.2.weight": [[0.065042, -0.299011, 0.269159, -0.021287, -0.323326, 0.055421, 0.207364], [0.319675, -0.342685, -0.175352, -0.098236, 0.542035, 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13, "train_loss": 0.2844424247741699, "train_acc": 0.89, "val_loss": 0.3741168975830078, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.3078360855579376, "train_acc": 0.895, "val_loss": 0.37230464816093445, "val_acc": 0.84}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6973820328712463, "final_val_loss": 0.6487495303153992, "initial_val_acc": 0.46, "final_val_acc": 0.72, "best_val_acc": 0.72}, "improved_stage": {"initial_val_loss": 0.6128571033477783, "final_val_loss": 0.37230464816093445, "initial_val_acc": 0.74, "final_val_acc": 0.84, "best_val_acc": 0.88, "best_epoch": 13}, "improvement": 0.16000000000000003, "first_improvement_epoch": 4}} |
57 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.54, "improved_accuracy": 0.82, "improvement": 0.2799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3433, "learning_rate": 0.016118345119958435, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[29.040985, 29.061996, 115.498647], [32.366981, 33.802955, 201.069969], [20.208598, 20.570877, 22.662027], [40.064768, 48.209095, 317.131246], [22.953734, 26.186296, 53.924678], [35.841089, 36.356049, 40.146226], [21.700579, 24.671739, 160.856576], [19.887067, 19.964699, 22.173340]]
### 2
fourier: [[10.194065, 11.022768, 35.527340], [16.053305, 19.669518, 132.905620], [15.603656, 15.967296, 130.656025], [22.162431, 22.458648, 140.246214], [27.004899, 29.162999, 199.922319], [15.047214, 15.398997, 70.468143], [17.906731, 20.278773, 131.300056], [33.227863, 34.711208, 207.210749]]
### 4
fourier: [[19.940381, 21.130335, 129.171749], [33.139899, 34.871848, 162.989337], [1.179699, 1.312971, 36.030857], [16.514908, 17.556627, 123.049000], [11.804962, 12.312385, 78.253791], [31.088574, 32.812398, 168.734663], [5.540443, 5.955743, 24.526125], [7.796777, 8.295202, 30.385697]]
### 6
fourier: [[38.543068, 41.602634, 194.070740], [16.608907, 17.799916, 69.598567], [21.107186, 22.480594, 121.758345], [2.602288, 2.868040, 30.044256], [1.498881, 1.537371, 31.090934], [6.558422, 7.013866, 53.694161], [29.999513, 32.408103, 142.876848], [1.902864, 2.222999, 46.707229]]
### 8
fourier: [[39.942312, 44.288212, 151.870863]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[29.040985, 29.061996, 115.498647], [32.366981, 33.802955, 201.069969], [20.208598, 20.570877, 22.662027], [40.064768, 48.209095, 317.131246], [22.953734, 26.186296, 53.924678], [35.841089, 36.356049, 40.146226], [21.700579, 24.671739, 160.856576], [19.887067, 19.964699, 22.173340]]
### 2
fourier: [[10.194065, 11.022768, 35.527340], [16.053305, 19.669518, 132.905620], [15.603656, 15.967296, 130.656025], [22.162431, 22.458648, 140.246214], [27.004899, 29.162999, 199.922319], [15.047214, 15.398997, 70.468143], [17.906731, 20.278773, 131.300056], [33.227863, 34.711208, 207.210749]]
### 4
fourier: [[19.940381, 21.130335, 129.171749], [33.139899, 34.871848, 162.989337], [1.179699, 1.312971, 36.030857], [16.514908, 17.556627, 123.049000], [11.804962, 12.312385, 78.253791], [31.088574, 32.812398, 168.734663], [5.540443, 5.955743, 24.526125], [7.796777, 8.295202, 30.385697]]
### 6
fourier: [[38.543068, 41.602634, 194.070740], [16.608907, 17.799916, 69.598567], [21.107186, 22.480594, 121.758345], [2.602288, 2.868040, 30.044256], [1.498881, 1.537371, 31.090934], [6.558422, 7.013866, 53.694161], [29.999513, 32.408103, 142.876848], [1.902864, 2.222999, 46.707229]]
### 8
fourier: [[39.942312, 44.288212, 151.870863]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [29.04098450677332, 29.061995791977647, 115.49864688515663]}, "1": {"fourier": [32.36698067772084, 33.80295529417779, 201.06996935233474]}, "2": {"fourier": [20.208597614191962, 20.570876798111122, 22.66202699863919]}, "3": {"fourier": [40.06476794161783, 48.20909456611097, 317.1312463879585]}, "4": {"fourier": [22.953734072511967, 26.186296416442733, 53.924678404815495]}, "5": {"fourier": [35.84108921478699, 36.356049417596424, 40.1462262570858]}, "6": {"fourier": [21.70057939296672, 24.67173906904014, 160.8565757572651]}, "7": {"fourier": [19.887066855660194, 19.964699365951013, 22.173339996218097]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [10.194065209438666, 11.022767646616664, 35.527339830994606]}, "1": {"fourier": [16.05330491254514, 19.669517999289027, 132.90561974048615]}, "2": {"fourier": [15.60365600012992, 15.967295735137712, 130.6560247540474]}, "3": {"fourier": [22.16243098347298, 22.458648302180197, 140.24621395766735]}, "4": {"fourier": [27.004899275291663, 29.162999369364684, 199.9223192036152]}, "5": {"fourier": [15.047214290459815, 15.398997153020748, 70.46814335882664]}, "6": {"fourier": [17.906730567840757, 20.278772666950655, 131.3000562787056]}, "7": {"fourier": [33.22786265026005, 34.71120845631427, 207.21074881404638]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [19.940381202561273, 21.1303346104312, 129.1717494726181]}, "1": {"fourier": [33.13989922687317, 34.871848397502006, 162.9893372952938]}, "2": {"fourier": [1.1796986305517692, 1.3129711920062364, 36.03085681796074]}, "3": {"fourier": [16.514907672794102, 17.5566272431705, 123.04899954795837]}, "4": {"fourier": [11.804961517125875, 12.312384576974788, 78.2537913993001]}, "5": {"fourier": [31.088574003083625, 32.81239754494904, 168.73466285318136]}, "6": {"fourier": [5.540443148375879, 5.955743421582662, 24.526125218719244]}, "7": {"fourier": [7.79677748028478, 8.295202389566933, 30.385697420686483]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [38.54306795250461, 41.60263441612021, 194.0707402303815]}, "1": {"fourier": [16.608906934980343, 17.799916447657612, 69.59856654703617]}, "2": {"fourier": [21.10718614527459, 22.480593625059807, 121.75834514200687]}, "3": {"fourier": [2.602288171414669, 2.8680402747633127, 30.044255673885345]}, "4": {"fourier": [1.4988808243262863, 1.5373708489313205, 31.09093403816223]}, "5": {"fourier": [6.558422186034775, 7.013865676086177, 53.69416135549545]}, "6": {"fourier": [29.999513314540938, 32.40810288122821, 142.87684807181358]}, "7": {"fourier": [1.9028643114868737, 2.222999025177553, 46.7072294652462]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [39.94231174074263, 44.28821197794515, 151.8708626627922]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.68436, -0.019756, -0.121784, 0.429257, 0.116215], [-0.402463, -0.353811, -0.432328, 0.022364, -0.128114], [0.101972, 0.308938, -0.506301, 0.104073, 0.022251], [0.578442, 0.593871, 0.228058, 0.20191, 0.355481], [-0.590763, -0.26277, 0.190671, -0.058234, 0.267062], [-0.715438, 0.227613, -0.231693, 0.292304, 0.332203], [0.059215, 0.401225, 0.014408, 0.306793, -0.159819], [-0.516211, -0.041872, 0.018552, -0.221272, 0.354459]], "network.0.bias": [-0.341788, -0.075411, 0.282879, 0.373879, 0.012044, 0.369066, 0.491597, 0.703733], "network.2.weight": [[-0.256438, -0.040772, -0.457626, 0.034767, 0.015452, 0.163665, 0.04741, 0.385981], [-0.022582, 0.130821, 0.175246, -0.437046, 0.19509, -0.221286, 0.141887, -0.061561], [-0.01673, -0.002251, 0.133785, -0.214749, -0.142444, -0.239578, -0.248544, -0.040662], [0.338577, -0.111474, 0.13405, 0.240138, 0.306886, -0.23002, 0.12762, -0.319353], [0.087097, -0.094645, 0.174516, 0.236213, -0.033813, 0.302956, 0.528813, -0.337424], [-0.207083, 0.159594, -0.311711, -0.23044, 0.468363, -0.243798, 0.180295, 0.085079], [-0.057264, 0.243562, -0.143159, -0.392205, -0.2754, 0.036909, 0.014331, -0.285062], [0.462806, -0.116902, 0.345971, 0.318858, -0.109469, -0.102194, 0.292228, -0.272108]], "network.2.bias": [0.441604, -0.04927, -0.016172, 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-0.366665, 0.287514, 0.104942, 0.353278], [-0.25488, 0.036499, -0.159973, -0.279683, -0.155927, 0.540443, 0.083607, 0.565316], [0.055845, -0.037351, -0.111787, -0.007683, -0.28769, -0.025916, -0.298586, 0.143645], [-0.299826, 0.191123, -0.327253, 0.093521, -0.19115, -0.195882, -0.106299, -0.086281], [0.262601, 0.168497, -0.023285, -0.005692, -0.317178, -0.253946, -0.465025, -0.268907], [0.339713, 0.343545, -0.168347, 0.247097, 0.264657, 0.559974, 9.6e-05, 0.442464], [-0.160654, -0.263067, -0.086483, -0.238982, -0.020579, 0.228524, -0.265604, 0.119976]], "network.6.bias": [-0.097287, -0.071146, 0.107474, 0.533059, -0.138439, -0.194544, -0.196877, -0.394144], "network.8.weight": [[-0.537191, -0.126413, -0.248335, 0.319543, -0.198714, 0.06393, -0.428811, 0.222545]], "network.8.bias": [0.52156]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7291630506515503, "train_acc": 0.445, "val_loss": 0.705742597579956, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7045414447784424, "train_acc": 0.445, "val_loss": 0.6868487000465393, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6834805309772491, "train_acc": 0.59, "val_loss": 0.6656372547149658, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6684944033622742, "train_acc": 0.485, "val_loss": 0.6365644931793213, "val_acc": 0.68}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6337035894393921, "train_acc": 0.725, "val_loss": 0.5998058915138245, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.5948713719844818, "train_acc": 0.75, "val_loss": 0.5521020889282227, "val_acc": 0.7}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.5634015500545502, "train_acc": 0.735, "val_loss": 0.5244699120521545, "val_acc": 0.68}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 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"degraded_stage": {"initial_val_loss": 0.705742597579956, "final_val_loss": 0.6656372547149658, "initial_val_acc": 0.46, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.6365644931793213, "final_val_loss": 0.36958563327789307, "initial_val_acc": 0.68, "final_val_acc": 0.82, "best_val_acc": 0.82, "best_epoch": 11}, "improvement": 0.2799999999999999, "first_improvement_epoch": 2}} |
58 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.46, "improved_accuracy": 0.92, "improvement": 0.46, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9301, "learning_rate": 0.0794152084668348, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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"network.10.weight": [
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"network.12.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[32.318389, 38.134742, 72.308004], [23.688912, 23.692558, 24.359842], [33.392527, 47.620157, 74.091963], [23.706316, 25.810056, 59.840277], [42.211068, 46.387470, 61.797328], [28.299637, 38.492995, 170.562092], [16.217843, 16.596833, 24.211944], [28.353230, 28.703935, 124.111553]]
### 2
fourier: [[22.311398, 28.715410, 133.728594], [49.079297, 53.327691, 181.678055], [12.137505, 12.671824, 105.589492], [57.004432, 58.698644, 234.180116], [20.198767, 21.203988, 136.753029], [53.550067, 60.058966, 201.113975], [21.746798, 22.462470, 24.285672], [47.692532, 52.444104, 105.163675]]
### 4
fourier: [[46.049316, 48.951006, 209.107375], [56.957160, 59.032554, 325.365048], [88.370153, 94.886449, 386.552964], [29.665052, 30.227225, 211.175385], [64.785329, 69.202122, 234.524338], [76.957048, 83.365920, 417.086949], [73.925298, 76.984051, 347.123297], [58.902903, 62.346747, 321.443425]]
### 6
fourier: [[35.084025, 35.427103, 293.183944], [38.731480, 40.976228, 293.303717], [29.857721, 30.467457, 251.150574], [40.102165, 41.909665, 200.553823], [82.902683, 87.642316, 396.200158], [12.505028, 13.532511, 94.023767], [76.148630, 79.901480, 377.502585], [59.177850, 61.728514, 365.287315]]
### 8
fourier: [[108.125151, 113.418042, 621.701025], [106.144799, 111.345456, 599.127663], [37.255304, 39.058626, 233.519200], [1.748500, 1.926072, 47.450214], [64.990987, 68.262954, 364.738191], [1.665940, 1.697162, 15.722380], [26.677076, 27.955815, 169.965787], [22.158280, 23.257396, 133.588517]]
### 10
fourier: [[11.162833, 11.703050, 76.997407], [19.176817, 20.120212, 118.215685], [8.924246, 9.374750, 79.729200], [50.538376, 53.006187, 316.616563], [11.571979, 12.138663, 92.400434], [135.811073, 142.497980, 773.188485], [55.055724, 57.752699, 343.702521], [107.093082, 112.370578, 600.442583]]
### 12
fourier: [[78.859265, 82.741054, 411.368712]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[32.318389, 38.134742, 72.308004], [23.688912, 23.692558, 24.359842], [33.392527, 47.620157, 74.091963], [23.706316, 25.810056, 59.840277], [42.211068, 46.387470, 61.797328], [28.299637, 38.492995, 170.562092], [16.217843, 16.596833, 24.211944], [28.353230, 28.703935, 124.111553]]
### 2
fourier: [[22.311398, 28.715410, 133.728594], [49.079297, 53.327691, 181.678055], [12.137505, 12.671824, 105.589492], [57.004432, 58.698644, 234.180116], [20.198767, 21.203988, 136.753029], [53.550067, 60.058966, 201.113975], [21.746798, 22.462470, 24.285672], [47.692532, 52.444104, 105.163675]]
### 4
fourier: [[46.049316, 48.951006, 209.107375], [56.957160, 59.032554, 325.365048], [88.370153, 94.886449, 386.552964], [29.665052, 30.227225, 211.175385], [64.785329, 69.202122, 234.524338], [76.957048, 83.365920, 417.086949], [73.925298, 76.984051, 347.123297], [58.902903, 62.346747, 321.443425]]
### 6
fourier: [[35.084025, 35.427103, 293.183944], [38.731480, 40.976228, 293.303717], [29.857721, 30.467457, 251.150574], [40.102165, 41.909665, 200.553823], [82.902683, 87.642316, 396.200158], [12.505028, 13.532511, 94.023767], [76.148630, 79.901480, 377.502585], [59.177850, 61.728514, 365.287315]]
### 8
fourier: [[108.125151, 113.418042, 621.701025], [106.144799, 111.345456, 599.127663], [37.255304, 39.058626, 233.519200], [1.748500, 1.926072, 47.450214], [64.990987, 68.262954, 364.738191], [1.665940, 1.697162, 15.722380], [26.677076, 27.955815, 169.965787], [22.158280, 23.257396, 133.588517]]
### 10
fourier: [[11.162833, 11.703050, 76.997407], [19.176817, 20.120212, 118.215685], [8.924246, 9.374750, 79.729200], [50.538376, 53.006187, 316.616563], [11.571979, 12.138663, 92.400434], [135.811073, 142.497980, 773.188485], [55.055724, 57.752699, 343.702521], [107.093082, 112.370578, 600.442583]]
### 12
fourier: [[78.859265, 82.741054, 411.368712]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [32.31838866321962, 38.13474196174899, 72.30800390988588]}, "1": {"fourier": [23.688912242650986, 23.69255757533708, 24.35984227308768]}, "2": {"fourier": [33.392527363741024, 47.62015650920921, 74.09196271002293]}, "3": {"fourier": [23.70631573868208, 25.81005578757216, 59.84027686715126]}, "4": {"fourier": [42.211068022084966, 46.38747046495166, 61.79732811450958]}, "5": {"fourier": [28.2996372590905, 38.49299487144453, 170.56209164857864]}, "6": {"fourier": [16.217843204932134, 16.59683290104372, 24.211944475769997]}, "7": {"fourier": [28.353230089534375, 28.703934588741593, 124.11155327409506]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [22.31139820176955, 28.71541010367703, 133.72859381139278]}, "1": {"fourier": [49.07929671415335, 53.327691478224615, 181.67805491387844]}, "2": {"fourier": [12.13750481332513, 12.671823699637843, 105.58949157595634]}, "3": {"fourier": [57.00443230792348, 58.69864371374174, 234.18011578917503]}, "4": {"fourier": [20.198767488479504, 21.203988230183487, 136.75302904844284]}, "5": {"fourier": [53.55006663123903, 60.05896583141356, 201.11397501826286]}, "6": {"fourier": [21.746797779010702, 22.462470103163156, 24.285671892062176]}, "7": {"fourier": [47.6925322800116, 52.444103762682886, 105.16367501020432]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [46.049316246781586, 48.9510063591053, 209.10737463831902]}, "1": {"fourier": [56.95715969257732, 59.03255352864771, 325.3650484085083]}, "2": {"fourier": [88.37015345469118, 94.88644856215187, 386.5529642999172]}, "3": {"fourier": [29.665051539671747, 30.227224644763336, 211.1753848195076]}, "4": {"fourier": [64.78532915219853, 69.20212242227754, 234.52433787286282]}, "5": {"fourier": [76.9570477826186, 83.36592039539859, 417.08694940805435]}, "6": {"fourier": [73.92529795020752, 76.98405121699125, 347.1232967078686]}, "7": {"fourier": [58.90290274638084, 62.34674686017993, 321.4434245824814]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [35.08402463723216, 35.42710261431957, 293.1839437484741]}, "1": {"fourier": [38.73148002395494, 40.97622790331369, 293.3037168979645]}, "2": {"fourier": [29.857720835184217, 30.467456597629457, 251.15057373046875]}, "3": {"fourier": [40.10216469235524, 41.90966451486719, 200.55382269620895]}, "4": {"fourier": [82.90268310805722, 87.64231632217124, 396.2001583278179]}, "5": {"fourier": [12.505027912716868, 13.532511360874807, 94.02376708388329]}, "6": {"fourier": [76.14863024559057, 79.9014801036738, 377.5025851428509]}, "7": {"fourier": [59.1778495810948, 61.72851425287378, 365.2873148918152]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [108.12515074068985, 113.41804230109707, 621.701024572365]}, "1": {"fourier": [106.14479871170683, 111.34545632190522, 599.1276632137597]}, "2": {"fourier": [37.255303772400275, 39.05862561292361, 233.5191996395588]}, "3": {"fourier": [1.7484995766158706, 1.9260718967205983, 47.450213730335236]}, "4": {"fourier": [64.99098743375795, 68.26295403753268, 364.73819057643414]}, "5": {"fourier": [1.6659395471219758, 1.6971619400472444, 15.72238027304411]}, "6": {"fourier": [26.67707553027521, 27.95581512481886, 169.96578705310822]}, "7": {"fourier": [22.15827951255351, 23.257395775184857, 133.5885166451335]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [11.162833390518161, 11.703050476913898, 76.99740670621395]}, "1": {"fourier": [19.17681684976299, 20.120212282841823, 118.21568503975868]}, "2": {"fourier": [8.924245658066535, 9.374749713894936, 79.72919964790344]}, "3": {"fourier": [50.538375540560665, 53.006186841741915, 316.61656311154366]}, "4": {"fourier": [11.571979190224202, 12.1386629184733, 92.40043419599533]}, "5": {"fourier": [135.81107271296995, 142.49797981696776, 773.1884849239141]}, "6": {"fourier": [55.05572402198005, 57.752698694917626, 343.7025208771229]}, "7": {"fourier": [107.09308159985481, 112.37057848978361, 600.4425825402141]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [78.85926485754085, 82.74105358819857, 411.3687119781971]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.426262, 0.009798, -0.357191, 0.704963, 0.372493], [-0.597995, 0.130851, 0.291564, -0.256211, 0.415637], [-0.41921, -0.339106, 0.503574, -0.138, 0.787878], [-0.557291, 0.128957, 0.434382, 0.137637, 0.349375], [0.970065, 0.324808, 0.014612, -0.416489, -0.114985], [0.690094, -0.355958, -0.139854, -0.51995, -0.121299], [-0.435053, 0.19057, 0.330369, -0.044914, 0.032169], [-0.298786, 0.437976, -0.176366, 0.225865, 0.657501]], "network.0.bias": [0.090998, -0.329712, 0.23516, -0.510003, -0.107996, -0.548537, -0.170303, 0.025885], "network.2.weight": [[-0.204787, -0.351619, -0.58306, -0.260747, -0.229546, -0.091166, 0.061335, 0.327849], [0.619952, 0.398606, 0.298149, 0.274739, -0.460133, -0.216798, 0.209981, 0.572877], [-0.322318, -0.043712, 0.076783, -0.406948, -0.055226, -0.311244, -0.061083, 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[0.036517, 0.483597, 0.134653, 0.398543, -0.371219, 0.75939, 0.418338, -0.107846], [-0.099349, 0.190024, 0.274613, 0.729965, 0.020223, 0.544336, 0.337799, -0.344772], [-0.076547, -0.626904, 0.264474, -0.178884, -0.487167, -0.561106, 0.454657, -0.11585]], "network.4.bias": [-0.134323, -0.357774, 0.21907, -0.306621, 0.364333, 0.229915, -0.116792, -0.302292], "network.6.weight": [[-0.238195, -0.076474, -0.31624, -0.025379, -0.846392, -0.668265, 0.126598, -0.23226], [-0.572276, 0.278873, -0.198225, -0.319128, -0.119616, -0.473481, -0.085135, -0.611348], [-0.214552, 0.228377, -0.24939, 0.251282, -0.190576, -0.182249, -0.270256, -0.835845], [0.204036, 0.016016, -0.587285, -0.012478, -0.427468, 0.24526, 0.19823, 0.028445], [0.112278, -0.010083, -0.339097, -0.444104, -0.651437, 0.492387, 0.53692, 0.059808], [-0.180255, -0.069241, -0.228916, -0.156148, -0.505495, -0.079808, -0.017843, -0.393082], [0.261839, 0.12405, -0.593423, -0.101366, -0.423475, 0.240602, 0.731641, -0.142384], [0.023588, 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"network.10.weight": [[-0.031548, -0.098092, -0.253439, -0.344392, 0.176811, 0.152696, -0.079656, -0.394272], [-0.162143, 0.014568, 0.112638, 0.238497, -0.083106, -0.143778, -0.102679, 0.097597], [-0.001426, 0.012384, -0.331332, 0.180097, -0.218588, 0.311007, -0.142893, 0.180666], [-0.331984, -0.19091, -0.092273, -0.32926, 0.11677, 0.153864, -0.068567, -0.086159], [-0.090058, -0.011356, -0.314621, 0.054928, 0.015215, -0.066865, -0.31765, -0.072712], [0.54139, 0.460802, 0.174296, -0.015036, 0.41334, 0.182705, -0.098884, 0.078258], [0.047519, -0.557216, -0.085444, -0.317783, 0.128555, -0.192928, 0.213643, -0.421315], [0.425939, 0.330715, -0.036989, 0.153605, 0.396673, 0.040247, 0.260294, 0.017102]], "network.10.bias": [-0.119699, -0.096644, -0.336095, -0.301477, -0.282989, -0.016771, -0.336191, -0.113941], "network.12.weight": [[0.01245, -0.039165, 0.240217, -0.182419, 0.171105, -0.41548, -0.135958, -0.210197]], "network.12.bias": [0.404045]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6899471879005432, "train_acc": 0.555, "val_loss": 0.7204413414001465, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6895598471164703, "train_acc": 0.58, "val_loss": 0.666134774684906, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.7290333211421967, "train_acc": 0.51, "val_loss": 0.592848002910614, "val_acc": 0.46}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5998221337795258, "train_acc": 0.635, "val_loss": 0.653597891330719, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6512810289859772, "train_acc": 0.77, "val_loss": 0.6286223530769348, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.590295135974884, "train_acc": 0.83, "val_loss": 0.5161682367324829, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 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"degraded_stage": {"initial_val_loss": 0.7204413414001465, "final_val_loss": 0.666134774684906, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.592848002910614, "final_val_loss": 0.2885231375694275, "initial_val_acc": 0.46, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 7}, "improvement": 0.46, "first_improvement_epoch": 1}} |
59 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.48, "improved_accuracy": 0.76, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8264, "learning_rate": 0.06745739206568764, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[49.528402, 51.002952, 95.731892], [35.864043, 37.405000, 39.561733], [28.651434, 35.376331, 230.778799], [25.934924, 33.985775, 37.520360], [41.553555, 43.611757, 308.546937], [37.916120, 41.691326, 301.696049], [18.260107, 19.998877, 53.013810], [33.256637, 34.653120, 114.607570]]
### 2
fourier: [[41.230556, 43.618937, 334.824179], [22.957894, 25.076336, 174.875357], [22.121400, 22.280859, 94.756832], [28.507412, 29.680768, 76.479960], [21.021697, 21.318899, 28.158617], [26.262394, 27.167316, 153.855382], [17.107925, 17.569107, 160.025446], [42.821158, 47.978481, 143.466614]]
### 4
fourier: [[14.808855, 19.925063, 81.214324], [3.190076, 3.536993, 39.008960], [28.262033, 29.969318, 128.659355], [27.568961, 28.469382, 202.560421], [20.732928, 21.582662, 138.021704], [6.836854, 7.063752, 76.760973], [46.225387, 52.866394, 127.087495], [46.048091, 46.950302, 64.190409]]
### 6
fourier: [[20.758645, 25.785134, 89.622998], [11.258643, 12.311030, 13.290232], [28.814522, 31.940591, 73.635044], [14.304841, 18.033682, 22.512421], [31.636643, 39.765905, 105.352835], [5.084576, 5.338842, 16.700176], [65.737245, 81.531725, 181.160795], [8.491713, 9.931268, 11.872852]]
### 8
fourier: [[69.018112, 86.083529, 153.133637], [3.641249, 4.611162, 11.335584], [63.498815, 78.983902, 129.782463], [1.967133, 2.096056, 8.382712], [22.037820, 27.497117, 97.487522], [27.413063, 34.433981, 84.351875], [20.265260, 24.596981, 67.215620], [67.496413, 83.744777, 176.381409]]
### 10
fourier: [[63.580254, 79.728414, 176.965197], [17.341258, 21.924513, 52.920818], [11.679686, 14.813553, 47.401511], [37.456564, 46.938300, 68.229680], [53.452683, 68.062103, 90.844405], [29.266730, 36.699728, 102.163081], [54.831946, 68.814559, 122.628708], [41.703883, 52.331555, 75.086024]]
### 12
fourier: [[41.436439, 52.598805, 69.929222]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[49.528402, 51.002952, 95.731892], [35.864043, 37.405000, 39.561733], [28.651434, 35.376331, 230.778799], [25.934924, 33.985775, 37.520360], [41.553555, 43.611757, 308.546937], [37.916120, 41.691326, 301.696049], [18.260107, 19.998877, 53.013810], [33.256637, 34.653120, 114.607570]]
### 2
fourier: [[41.230556, 43.618937, 334.824179], [22.957894, 25.076336, 174.875357], [22.121400, 22.280859, 94.756832], [28.507412, 29.680768, 76.479960], [21.021697, 21.318899, 28.158617], [26.262394, 27.167316, 153.855382], [17.107925, 17.569107, 160.025446], [42.821158, 47.978481, 143.466614]]
### 4
fourier: [[14.808855, 19.925063, 81.214324], [3.190076, 3.536993, 39.008960], [28.262033, 29.969318, 128.659355], [27.568961, 28.469382, 202.560421], [20.732928, 21.582662, 138.021704], [6.836854, 7.063752, 76.760973], [46.225387, 52.866394, 127.087495], [46.048091, 46.950302, 64.190409]]
### 6
fourier: [[20.758645, 25.785134, 89.622998], [11.258643, 12.311030, 13.290232], [28.814522, 31.940591, 73.635044], [14.304841, 18.033682, 22.512421], [31.636643, 39.765905, 105.352835], [5.084576, 5.338842, 16.700176], [65.737245, 81.531725, 181.160795], [8.491713, 9.931268, 11.872852]]
### 8
fourier: [[69.018112, 86.083529, 153.133637], [3.641249, 4.611162, 11.335584], [63.498815, 78.983902, 129.782463], [1.967133, 2.096056, 8.382712], [22.037820, 27.497117, 97.487522], [27.413063, 34.433981, 84.351875], [20.265260, 24.596981, 67.215620], [67.496413, 83.744777, 176.381409]]
### 10
fourier: [[63.580254, 79.728414, 176.965197], [17.341258, 21.924513, 52.920818], [11.679686, 14.813553, 47.401511], [37.456564, 46.938300, 68.229680], [53.452683, 68.062103, 90.844405], [29.266730, 36.699728, 102.163081], [54.831946, 68.814559, 122.628708], [41.703883, 52.331555, 75.086024]]
### 12
fourier: [[41.436439, 52.598805, 69.929222]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [49.528402390062, 51.002951769272244, 95.73189249634743]}, "1": {"fourier": [35.86404305367724, 37.40500035481556, 39.56173344374088]}, "2": {"fourier": [28.65143425741387, 35.37633147475484, 230.7787987291813]}, "3": {"fourier": [25.934924011158223, 33.9857754079327, 37.520359605550766]}, "4": {"fourier": [41.55355464038035, 43.61175659367347, 308.5469368696213]}, "5": {"fourier": [37.91612047559584, 41.69132584354004, 301.6960487961769]}, "6": {"fourier": [18.26010677261791, 19.998877124206345, 53.013810485601425]}, "7": {"fourier": [33.25663746889237, 34.6531199709456, 114.60756969451904]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [41.23055629247507, 43.618937390688494, 334.82417941093445]}, "1": {"fourier": [22.9578940841959, 25.07633633269616, 174.87535712122917]}, "2": {"fourier": [22.1213998568788, 22.28085949708679, 94.75683182477951]}, "3": {"fourier": [28.50741155979443, 29.680767632291914, 76.47995967417955]}, "4": {"fourier": [21.021697261230575, 21.318899300572216, 28.15861694026013]}, "5": {"fourier": [26.26239371907885, 27.1673157063089, 153.85538184642792]}, "6": {"fourier": [17.10792498156062, 17.569106682957685, 160.02544558048248]}, "7": {"fourier": [42.82115810248496, 47.97848090150135, 143.46661449456587]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [14.80885508116462, 19.92506312956724, 81.21432438492775]}, "1": {"fourier": [3.1900756233448693, 3.536993161184416, 39.00895978137851]}, "2": {"fourier": [28.262033022615892, 29.96931825156015, 128.659354865551]}, "3": {"fourier": [27.568961289389392, 28.469381945319597, 202.56042116880417]}, "4": {"fourier": [20.73292834278574, 21.582661670173234, 138.02170360088348]}, "5": {"fourier": [6.836854305926824, 7.063751825035372, 76.76097279787064]}, "6": {"fourier": [46.22538686476684, 52.86639418556933, 127.08749501407146]}, "7": {"fourier": [46.04809064416562, 46.9503020171763, 64.19040924107259]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [20.75864460888389, 25.785133947195963, 89.62299835681915]}, "1": {"fourier": [11.258643477672456, 12.311029837851253, 13.290232121944427]}, "2": {"fourier": [28.814521826869086, 31.94059069425531, 73.63504368066788]}, "3": {"fourier": [14.30484063345487, 18.03368249963619, 22.512420922517776]}, "4": {"fourier": [31.6366433213631, 39.76590467708178, 105.35283529758453]}, "5": {"fourier": [5.0845760395261115, 5.338841709036221, 16.700176076963544]}, "6": {"fourier": [65.73724481582077, 81.53172497487338, 181.16079545021057]}, "7": {"fourier": [8.491712945040286, 9.931268290625647, 11.872852275247311]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [69.01811186754941, 86.08352889039773, 153.13363674283028]}, "1": {"fourier": [3.6412493482948536, 4.6111620499314725, 11.335583686828613]}, "2": {"fourier": [63.49881497966952, 78.98390174565989, 129.78246255218983]}, "3": {"fourier": [1.9671333932483352, 2.0960556034982614, 8.382711976766586]}, "4": {"fourier": [22.037820255242146, 27.497116977317642, 97.48752203583717]}, "5": {"fourier": [27.413062936538132, 34.433981346458054, 84.35187485814095]}, "6": {"fourier": [20.265259651062152, 24.596980552025357, 67.2156198322773]}, "7": {"fourier": [67.49641263026655, 83.74477697094127, 176.38140852749348]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [63.58025397972235, 79.72841376548917, 176.965196788311]}, "1": {"fourier": [17.341258040855333, 21.924513381968612, 52.920817732810974]}, "2": {"fourier": [11.679685911973753, 14.813552592153373, 47.40151144564152]}, "3": {"fourier": [37.45656384699006, 46.938299948999635, 68.22967974841595]}, "4": {"fourier": [53.45268263687619, 68.06210298198852, 90.8444053530693]}, "5": {"fourier": [29.266730330161234, 36.69972837641405, 102.16308099031448]}, "6": {"fourier": [54.83194606284961, 68.81455881043934, 122.62870813161135]}, "7": {"fourier": [41.703882759408174, 52.33155478808931, 75.0860241651535]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [41.43643931589825, 52.59880541951902, 69.92922240495682]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-1.062776, -0.582598, 0.137048, 0.063917, 0.811969], [-0.751025, -0.136458, 0.014484, -0.015327, 1.079204], [-0.216142, -0.395608, -0.35785, -0.244309, -0.305778], [-0.242149, -0.226093, 0.180718, -0.20398, 0.693744], [-0.409887, -0.277577, -0.01932, -0.471375, -0.68898], [0.693366, 0.471491, 0.156193, 0.205103, 0.091194], [-0.282922, 0.208775, 0.133193, 0.109811, -0.36082], [-0.627492, 0.312877, -0.416099, 0.125835, 0.073092]], "network.0.bias": [-0.104272, 0.163294, 0.074195, -0.499254, -0.511474, 0.751587, -0.686093, -0.553479], "network.2.weight": [[-0.524995, -0.376504, -0.300763, -0.444088, -0.400801, -0.718894, -0.085947, -0.411875], [-0.113717, -0.247869, -0.0833, 0.253251, 0.055407, 0.540782, 0.485641, 0.221856], [-0.353755, -0.615504, -0.0079, 0.211631, 0.137017, -0.091332, 0.034913, 0.055345], [-0.647768, -0.377582, 0.029983, -0.287097, -0.234683, 0.05287, -0.166355, -0.711959], [0.334793, 0.521789, 0.046629, 0.006724, 0.066369, -0.158557, -0.33995, -0.048564], [0.71926, 0.389375, -0.200069, 0.181382, -0.34695, 0.087407, 0.245376, -0.161657], [-0.06297, -0.070665, 0.079392, -0.336544, 0.241526, -0.335032, -0.074308, -0.553012], [0.544937, 0.994289, -0.136961, 0.419785, -0.250951, 0.074593, -0.489783, 0.144668]], "network.2.bias": [-0.436851, 0.211496, -0.095318, -0.113498, -0.253541, 0.604853, -0.329419, 0.006855], "network.4.weight": [[0.019648, 0.138752, -0.258586, 0.203333, -0.347458, -0.44649, 0.136728, 0.063014], [-0.160896, -0.093632, -0.379638, -0.28894, 0.125454, -0.284203, -0.473974, 0.134472], [-0.027275, -0.119247, -0.001152, -0.499436, -0.641116, -0.323974, 0.018429, -0.225835], [-0.490524, -0.512795, -0.104485, 0.494024, -0.065048, -0.316327, 0.044433, -0.337028], [-0.221368, -0.063171, 0.114581, -0.604014, -0.220972, -0.600161, 0.131276, -0.036249], [-0.341716, -0.146992, 0.039076, -0.667044, -0.065209, -0.525217, 0.335515, 0.224203], [0.170236, -0.344659, 0.086177, 0.130332, 0.072356, 0.580028, -0.3082, 0.649098], [0.07101, -0.935919, -0.418053, 0.024031, 0.426166, -0.121853, -0.19379, 0.819656]], "network.4.bias": [-0.379247, -0.020925, -0.009207, -0.16419, -0.217383, 0.020478, 0.015188, 0.15485], "network.6.weight": [[-0.294536, -0.151575, 0.068544, 0.138185, -0.315163, 0.125892, -0.23007, -0.302583], [-0.148352, -0.154811, -0.008297, 0.073114, -0.265115, -0.164496, 0.274116, -0.039811], [0.311241, -0.043116, 0.099644, -0.435421, 0.062416, 0.421788, -0.665621, 0.052163], [-0.310074, -0.331169, 0.091716, -0.105178, 0.773336, 0.255292, 0.179106, -0.592834], [0.039692, -0.196073, -0.39601, 0.513855, 0.575915, 0.000679, -0.242899, -0.592157], [-0.021989, -0.103461, 0.518131, -0.21356, 0.07487, 0.224581, -0.142127, 0.043358], [-0.011782, -0.16436, -0.173533, -0.227878, 0.007494, 0.253824, 0.756885, 0.923772], [0.21282, 0.141041, 0.09536, 0.160994, 0.028164, -0.3882, -0.208854, 0.492212]], "network.6.bias": [-0.389028, -0.522719, 0.131226, 0.497677, -0.292979, -0.010838, 0.078983, -0.096865], "network.8.weight": [[-0.137726, 0.393943, 0.182557, -0.854261, -0.243457, -0.272459, 0.947819, 0.062435], [0.269555, 0.312908, 0.244109, 0.116396, 0.63553, -0.040697, -0.01514, -0.611414], [0.100668, 0.153782, 0.205478, -0.51281, 0.001647, 0.211453, 0.925885, -0.060837], [0.076847, -0.599934, -0.405433, 0.294844, 0.024958, -0.038671, 0.156566, -0.558759], [-0.087536, 0.046048, 0.301124, -0.080291, 0.131746, -0.05887, -0.295475, -0.438255], [-0.505984, -0.213786, 0.113037, 0.184483, -0.240867, 0.123203, -0.322015, -0.533184], [-0.136759, -0.240346, -0.223569, -0.154711, -0.058773, -0.12493, -0.317776, 0.29923], [-0.115777, 0.202612, -0.242451, -0.515833, -0.130133, -0.157092, 0.990781, -0.183854]], "network.8.bias": [0.103078, -0.118069, -0.208332, -0.133752, -0.399779, -0.25114, -0.028458, 0.213531], "network.10.weight": [[-0.409721, -0.79051, -0.083073, 0.098727, -0.208597, -0.193628, 0.345529, -0.455203], [0.090074, -0.453936, -0.336461, -0.055889, -0.007064, 0.091411, -0.217199, -0.039967], [-0.185261, -0.250562, -0.149713, -0.310794, -0.116257, 0.251797, 0.016701, 0.152577], [0.204155, -0.407589, 0.023287, -0.098062, 0.100267, 0.123229, 0.146604, 0.329561], [0.334492, 0.193658, 0.53577, -0.307162, -0.318919, 0.107876, -0.283256, -0.030039], [-0.098393, -0.29393, -0.09544, 0.091718, -0.309536, 0.128559, -0.307865, -0.248463], [0.219844, -0.187545, 0.314683, 0.206408, -0.201806, 0.07778, -0.224763, 0.302632], [0.277821, -0.128135, 0.079651, 0.011816, -0.116458, -0.074013, 0.253648, 0.265978]], "network.10.bias": [-0.211868, -0.11998, -0.217628, -0.282662, -0.371519, -0.325552, -0.157603, -0.317217], "network.12.weight": [[0.214864, -0.015266, 0.027294, -0.142515, -0.319025, -0.069746, -0.298878, -0.090165]], "network.12.bias": [0.283537]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6807601451873779, "train_acc": 0.575, "val_loss": 0.7482194304466248, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6847920417785645, "train_acc": 0.575, "val_loss": 0.6960969567298889, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.7809063196182251, "train_acc": 0.505, "val_loss": 0.7308866381645203, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.7009685337543488, "train_acc": 0.505, "val_loss": 0.6917961239814758, "val_acc": 0.56}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6966330409049988, "train_acc": 0.525, "val_loss": 0.6912455558776855, "val_acc": 0.52}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.6914148330688477, "train_acc": 0.495, "val_loss": 0.6832075715065002, "val_acc": 0.52}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.6799335479736328, "train_acc": 0.545, "val_loss": 0.6388636231422424, "val_acc": 0.7}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.600528746843338, "train_acc": 0.675, "val_loss": 0.5641230940818787, "val_acc": 0.56}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.5295516848564148, "train_acc": 0.665, "val_loss": 0.5101473927497864, "val_acc": 0.76}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.5008559376001358, "train_acc": 0.735, "val_loss": 0.5080903172492981, "val_acc": 0.74}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.4835844039916992, "train_acc": 0.74, "val_loss": 0.4889506995677948, "val_acc": 0.76}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.5062121450901031, "train_acc": 0.745, "val_loss": 0.4828397035598755, "val_acc": 0.76}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.7482194304466248, "final_val_loss": 0.6960969567298889, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.7308866381645203, "final_val_loss": 0.4828397035598755, "initial_val_acc": 0.48, "final_val_acc": 0.76, "best_val_acc": 0.76, "best_epoch": 8}, "improvement": 0.28, "first_improvement_epoch": 1}} |
60 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.46, "improved_accuracy": 0.9, "improvement": 0.44, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7048, "learning_rate": 0.04198946419763812, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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],
"network.0.bias": [
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],
"network.2.weight": [
[
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[
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],
[
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],
[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
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],
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[
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[
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[
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],
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],
"network.6.weight": [
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[
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[
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],
"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[22.130885, 22.135982, 153.684371], [32.220803, 36.100684, 189.479284], [20.967229, 26.032974, 185.955068], [15.306636, 18.310711, 18.322331], [30.276889, 30.346845, 196.965898]]
### 2
fourier: [[4.986571, 5.403397, 70.492575], [22.872539, 23.839154, 157.054066], [5.382048, 5.795616, 45.474227], [15.353911, 15.830317, 102.863294], [4.233110, 4.454133, 54.300488]]
### 4
fourier: [[17.048134, 17.151651, 120.454181], [12.188384, 12.318022, 25.939881], [14.692564, 15.445526, 139.711018], [0.574169, 0.583909, 0.695850], [18.590138, 19.217272, 116.174114]]
### 6
fourier: [[6.566099, 6.616258, 8.970893], [21.743184, 22.220878, 136.041242], [1.742128, 1.766975, 12.300685], [0.642459, 0.711618, 41.521786], [25.895987, 26.507920, 165.508415]]
### 8
fourier: [[29.870444, 29.953289, 189.269020]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.042616
],
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[
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[
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[
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[
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"network.2.bias": [
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"network.4.weight": [
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[
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[
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[
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],
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],
"network.6.weight": [
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],
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[
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],
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],
"network.8.weight": [
[
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]
],
"network.8.bias": [
-0.281625
]
}
## Activation Signature
### 0
fourier: [[22.130885, 22.135982, 153.684371], [32.220803, 36.100684, 189.479284], [20.967229, 26.032974, 185.955068], [15.306636, 18.310711, 18.322331], [30.276889, 30.346845, 196.965898]]
### 2
fourier: [[4.986571, 5.403397, 70.492575], [22.872539, 23.839154, 157.054066], [5.382048, 5.795616, 45.474227], [15.353911, 15.830317, 102.863294], [4.233110, 4.454133, 54.300488]]
### 4
fourier: [[17.048134, 17.151651, 120.454181], [12.188384, 12.318022, 25.939881], [14.692564, 15.445526, 139.711018], [0.574169, 0.583909, 0.695850], [18.590138, 19.217272, 116.174114]]
### 6
fourier: [[6.566099, 6.616258, 8.970893], [21.743184, 22.220878, 136.041242], [1.742128, 1.766975, 12.300685], [0.642459, 0.711618, 41.521786], [25.895987, 26.507920, 165.508415]]
### 8
fourier: [[29.870444, 29.953289, 189.269020]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [22.130884842592312, 22.135982288179626, 153.68437147513032]}, "1": {"fourier": [32.2208031250751, 36.10068390940935, 189.47928428649902]}, "2": {"fourier": [20.967228633572798, 26.03297412736466, 185.95506817102432]}, "3": {"fourier": [15.306635972949259, 18.310711171129057, 18.32233060244491]}, "4": {"fourier": [30.2768885621871, 30.346844813613483, 196.96589770168066]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [4.98657117106861, 5.403397348360756, 70.4925751388073]}, "1": {"fourier": [22.872539478858187, 23.83915395500959, 157.0540660917759]}, "2": {"fourier": [5.382047624075183, 5.795615989221597, 45.47422740608454]}, "3": {"fourier": [15.353911303939087, 15.830316675251247, 102.86329352110624]}, "4": {"fourier": [4.233109713586992, 4.454132931447722, 54.300488010048866]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [17.048133755207722, 17.151650770206594, 120.4541811645031]}, "1": {"fourier": [12.18838429443565, 12.31802232905306, 25.9398812353611]}, "2": {"fourier": [14.692563523968, 15.445525655735622, 139.7110177576542]}, "3": {"fourier": [0.5741694801054058, 0.5839094610294941, 0.6958495248109102]}, "4": {"fourier": [18.59013762547169, 19.217271940195094, 116.17411441355944]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [6.56609922778485, 6.616257511616603, 8.97089347988367]}, "1": {"fourier": [21.743183670287195, 22.220877553284613, 136.041241645813]}, "2": {"fourier": [1.7421284368894525, 1.7669753223870996, 12.300685480237007]}, "3": {"fourier": [0.6424586230943202, 0.7116182642797337, 41.5217864215374]}, "4": {"fourier": [25.89598740398486, 26.50791988177919, 165.5084147527814]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [29.870443897320545, 29.953288989259626, 189.2690196186304]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.010575, -0.416981, -0.255672, -0.167333, -0.042616], [0.500119, 0.476046, 0.132549, 0.213441, -0.469151], [-0.280247, -0.116799, -0.218709, -0.288266, -0.177852], [-0.2152, 0.032935, -0.247587, 0.272758, 0.00372], [0.194031, -0.595528, -0.557746, -0.152456, 0.022365]], "network.0.bias": [0.010853, 0.45952, -0.210202, 0.161306, 0.119634], "network.2.weight": [[-0.004313, -0.090201, 0.186035, -0.410127, -0.441787], [-0.311564, 0.722931, -0.345858, -0.292171, -0.151221], [0.277229, 0.14464, -0.093119, 0.19428, 0.233272], [0.121802, 0.477673, 0.257957, -0.232182, -0.306708], [0.195656, -0.133051, -0.263849, 0.181387, -0.221525]], "network.2.bias": [-0.416259, 0.308613, 0.111207, 0.213673, -0.384136], "network.4.weight": [[0.21244, 0.558322, -0.360642, 0.365791, 0.202898], [-0.080652, -0.377952, 0.18871, -0.275653, -0.018787], [-0.131014, 0.42921, 0.363221, 0.222793, -0.637302], [0.249221, 0.01065, -0.068663, -0.030004, 0.09854], [-0.002303, 0.3578, 0.231107, 0.614805, 0.44023]], "network.4.bias": [0.125831, 0.592732, 0.363521, 0.042732, -0.155657], "network.6.weight": [[0.014019, 0.740456, 0.219814, 0.145556, -0.415224], [0.551433, -0.22069, 0.438173, -0.099346, 0.279488], [0.032535, -0.193719, 0.183863, -0.136968, -0.115989], [0.119641, -0.161252, 0.050136, -0.002298, -0.191873], [0.559813, -0.16749, 0.383297, 0.083085, 0.549375]], "network.6.bias": [0.186176, -0.24094, -0.291026, -0.431543, -0.196669], "network.8.weight": [[0.572038, -0.608325, 0.344857, -0.05087, -0.546771]], "network.8.bias": [-0.281625]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6727138459682465, "train_acc": 0.59, "val_loss": 0.705595076084137, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6498412489891052, "train_acc": 0.59, "val_loss": 0.676525890827179, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.5967642366886139, "train_acc": 0.59, "val_loss": 0.5791502594947815, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5325459837913513, "train_acc": 0.61, "val_loss": 0.4838458299636841, "val_acc": 0.9}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.45925477147102356, "train_acc": 0.845, "val_loss": 0.41320809721946716, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.38404515385627747, "train_acc": 0.835, "val_loss": 0.4227367639541626, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.37929728627204895, "train_acc": 0.82, "val_loss": 0.43649521470069885, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.3708961606025696, "train_acc": 0.83, "val_loss": 0.39699217677116394, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.37236133217811584, "train_acc": 0.83, "val_loss": 0.3657534718513489, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3699638694524765, "train_acc": 0.83, "val_loss": 0.33802321553230286, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.3481704294681549, "train_acc": 0.84, "val_loss": 0.3627801537513733, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.36851218342781067, "train_acc": 0.875, "val_loss": 0.33443373441696167, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.34698882699012756, "train_acc": 0.85, "val_loss": 0.40432366728782654, "val_acc": 0.8}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.705595076084137, "final_val_loss": 0.5791502594947815, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.4838458299636841, "final_val_loss": 0.40432366728782654, "initial_val_acc": 0.9, "final_val_acc": 0.8, "best_val_acc": 0.9, "best_epoch": 3}, "improvement": 0.44, "first_improvement_epoch": 2}} |
61 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.48, "improved_accuracy": 0.82, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1250, "learning_rate": 0.054650206537940234, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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],
"network.0.bias": [
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"network.2.weight": [
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[
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[
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[
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],
"network.2.bias": [
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],
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[
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[
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[
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[
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[
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],
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[
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[
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[
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[
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],
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[
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],
"network.8.bias": [
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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[50.391135, 52.843447, 64.343955], [38.768604, 38.940754, 39.901493], [53.171120, 54.205318, 292.919007], [23.312767, 26.373836, 212.393375], [55.342655, 60.763403, 338.690566]]
### 2
fourier: [[24.616413, 26.358540, 187.113975], [32.747147, 34.992890, 221.085519], [30.613916, 36.212300, 267.506672], [29.843098, 30.232735, 44.899806], [85.270593, 88.700561, 424.734913]]
### 4
fourier: [[20.067281, 21.137129, 154.078652], [7.660215, 8.390686, 77.598132], [79.854437, 90.521714, 404.814089], [36.754239, 50.889245, 69.525796], [43.607168, 48.467701, 197.896974]]
### 6
fourier: [[20.879746, 21.712455, 148.047683], [5.290091, 5.591400, 55.438411], [23.130547, 30.752831, 33.839941], [119.077477, 133.762783, 601.174375], [7.876883, 8.503925, 82.502250]]
### 8
fourier: [[40.770087, 40.914966, 259.678511], [41.340979, 47.904845, 184.909580], [130.359787, 141.830575, 643.148948], [55.508072, 58.360206, 327.215550], [134.930566, 146.521654, 666.324478]]
### 10
fourier: [[203.194255, 214.517865, 967.563169]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-1.308423,
-0.370466,
-0.052404,
0.37422,
0.84064
],
[
0.906277,
0.601205,
-0.382885,
-0.355078,
0.007058
],
[
0.774286,
0.706164,
0.661692,
0.060268,
-0.440036
],
[
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-0.446782,
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-0.171
],
[
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],
"network.0.bias": [
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"network.2.weight": [
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"network.6.weight": [
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"network.10.bias": [
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}
## Activation Signature
### 0
fourier: [[50.391135, 52.843447, 64.343955], [38.768604, 38.940754, 39.901493], [53.171120, 54.205318, 292.919007], [23.312767, 26.373836, 212.393375], [55.342655, 60.763403, 338.690566]]
### 2
fourier: [[24.616413, 26.358540, 187.113975], [32.747147, 34.992890, 221.085519], [30.613916, 36.212300, 267.506672], [29.843098, 30.232735, 44.899806], [85.270593, 88.700561, 424.734913]]
### 4
fourier: [[20.067281, 21.137129, 154.078652], [7.660215, 8.390686, 77.598132], [79.854437, 90.521714, 404.814089], [36.754239, 50.889245, 69.525796], [43.607168, 48.467701, 197.896974]]
### 6
fourier: [[20.879746, 21.712455, 148.047683], [5.290091, 5.591400, 55.438411], [23.130547, 30.752831, 33.839941], [119.077477, 133.762783, 601.174375], [7.876883, 8.503925, 82.502250]]
### 8
fourier: [[40.770087, 40.914966, 259.678511], [41.340979, 47.904845, 184.909580], [130.359787, 141.830575, 643.148948], [55.508072, 58.360206, 327.215550], [134.930566, 146.521654, 666.324478]]
### 10
fourier: [[203.194255, 214.517865, 967.563169]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [50.39113465461621, 52.84344678401045, 64.34395493566565]}, "1": {"fourier": [38.76860447227955, 38.940753807067395, 39.901493425546235]}, "2": {"fourier": [53.17111980447414, 54.20531752501239, 292.91900735348463]}, "3": {"fourier": [23.31276660183647, 26.373836477561245, 212.39337539672852]}, "4": {"fourier": [55.34265527487904, 60.763403013582774, 338.6905664280057]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [24.61641347696797, 26.358539581418754, 187.11397472023964]}, "1": {"fourier": [32.74714726161084, 34.992890475006504, 221.08551859855652]}, "2": {"fourier": [30.613915827654, 36.212299921185306, 267.50667160749435]}, "3": {"fourier": [29.84309753191824, 30.232734761442977, 44.899805821120395]}, "4": {"fourier": [85.2705929486049, 88.70056131248919, 424.7349129617214]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [20.06728093813536, 21.137129191221906, 154.07865190505981]}, "1": {"fourier": [7.660215002850657, 8.390685608503452, 77.5981320142746]}, "2": {"fourier": [79.85443667275621, 90.52171374301736, 404.8140889406204]}, "3": {"fourier": [36.7542392231466, 50.889244560441355, 69.52579587697983]}, "4": {"fourier": [43.60716848074888, 48.467701174830324, 197.89697421342134]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [20.879746142498483, 21.712455455031243, 148.04768288135529]}, "1": {"fourier": [5.290090955028193, 5.591399910985582, 55.43841090798378]}, "2": {"fourier": [23.130547137836825, 30.752830528530346, 33.839940667152405]}, "3": {"fourier": [119.07747741031211, 133.76278288146148, 601.1743751764297]}, "4": {"fourier": [7.876883414235642, 8.503925077165835, 82.50225016474724]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [40.770087254087436, 40.91496551195438, 259.6785106062889]}, "1": {"fourier": [41.34097871950365, 47.90484520749576, 184.90957951545715]}, "2": {"fourier": [130.35978665763625, 141.83057489768035, 643.1489475816488]}, "3": {"fourier": [55.50807204862274, 58.36020622470141, 327.2155504822731]}, "4": {"fourier": [134.93056637418263, 146.5216543556191, 666.324478417635]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [203.1942550520096, 214.5178654826026, 967.5631686449051]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-1.308423, -0.370466, -0.052404, 0.37422, 0.84064], [0.906277, 0.601205, -0.382885, -0.355078, 0.007058], [0.774286, 0.706164, 0.661692, 0.060268, -0.440036], [-0.094519, -0.194738, -0.446782, -0.24664, -0.171], [1.166911, 0.567477, 0.333464, 0.170583, 0.07318]], "network.0.bias": [0.319721, -0.240032, 0.035581, -0.214362, 0.124373], "network.2.weight": [[-0.131963, -0.092834, 0.027991, 0.050634, -0.410087], [-0.266577, -0.397301, 0.129814, -0.116945, -0.457602], [-0.228231, 0.199446, -0.469628, 0.25806, -0.267079], [0.688255, -0.257773, -0.239857, -0.082394, -0.011114], [-0.418828, 0.619712, 0.706937, 0.154323, 0.421349]], "network.2.bias": [-0.396273, -0.46716, -0.399771, 0.131018, 0.530432], "network.4.weight": [[-0.065375, -0.091983, 0.143375, -0.052563, -0.250656], [-0.089483, 0.311284, -0.059541, -0.290253, -0.092015], [0.297861, 0.187015, 0.256772, -0.616361, 0.879466], [0.264929, -0.106503, 0.044911, 0.801069, -0.360613], [-0.152481, -0.535544, -0.21201, -0.282897, 0.484758]], "network.4.bias": [-0.48604, -0.259165, 0.648682, 0.496204, 0.045066], "network.6.weight": [[0.183714, -0.128109, -0.234535, -0.526886, -0.145615], [-0.097168, -0.050539, 0.142074, 0.03896, -0.378356], [-0.008053, 0.260598, -0.1733, 0.515762, -0.13105], [-0.180953, -0.352103, 1.161116, -0.689986, 0.544916], [-0.049795, -0.069921, -0.173712, -0.416044, 0.129959]], "network.6.bias": [0.036336, -0.43058, 0.464838, 0.414942, -0.200279], "network.8.weight": [[0.441881, -0.035055, -0.362642, -0.367282, -0.148325], [0.1079, -0.246139, 0.619982, -0.319956, 0.149073], [0.458985, -0.034271, -0.58274, 1.080953, -0.441328], [-0.36324, 0.429394, -0.049929, -0.475696, -0.234511], [-0.083546, 0.078757, -0.561645, 1.121013, -0.41718]], "network.8.bias": [-0.241859, -0.089189, -0.03892, -0.363332, -0.063082], "network.10.weight": [[-0.038997, 0.485049, -0.730827, 0.224091, -0.808396]], "network.10.bias": [0.596292]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7019431293010712, "train_acc": 0.42, "val_loss": 0.6993151903152466, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6804072558879852, "train_acc": 0.575, "val_loss": 0.7106826305389404, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6504930555820465, "train_acc": 0.575, "val_loss": 0.659527063369751, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.613209068775177, "train_acc": 0.505, "val_loss": 0.5415555834770203, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5010044127702713, "train_acc": 0.6, "val_loss": 0.6144959926605225, "val_acc": 0.7}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.48089708387851715, "train_acc": 0.8, "val_loss": 0.4866079092025757, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.4506503790616989, "train_acc": 0.815, "val_loss": 0.4916752278804779, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.45320960879325867, "train_acc": 0.79, "val_loss": 0.4719017446041107, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4077502638101578, "train_acc": 0.795, "val_loss": 0.45410996675491333, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3942558765411377, "train_acc": 0.815, "val_loss": 0.40765953063964844, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.39054614305496216, "train_acc": 0.84, "val_loss": 0.7655561566352844, "val_acc": 0.74}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4860672354698181, "train_acc": 0.82, "val_loss": 0.4404202401638031, "val_acc": 0.8}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.37876616418361664, "train_acc": 0.845, "val_loss": 0.4788753390312195, "val_acc": 0.78}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6993151903152466, "final_val_loss": 0.659527063369751, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5415555834770203, "final_val_loss": 0.4788753390312195, "initial_val_acc": 0.48, "final_val_acc": 0.78, "best_val_acc": 0.82, "best_epoch": 9}, "improvement": 0.33999999999999997, "first_improvement_epoch": 2}} |
62 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.66, "improved_accuracy": 0.98, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6942, "learning_rate": 0.039815314088510245, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
-0.196965,
0.109786,
-0.125568,
0.447886,
0.263874,
0.414812,
0.435537
],
[
0.140084,
0.196255,
-0.366234,
0.448874,
0.348905,
0.322383,
0.415712
],
[
0.422564,
0.203507,
-0.423176,
0.151049,
-0.217669,
0.563498,
0.117551
]
],
"network.8.bias": [
-0.06857,
-0.15361,
-0.026895,
-0.022716,
0.221899,
0.419629,
0.654688
],
"network.10.weight": [
[
0.248326,
-0.13477,
0.136456,
0.468797,
-0.266785,
-0.56126,
-0.344372
]
],
"network.10.bias": [
-0.099054
]
}
## Activation Signature
### 0
fourier: [[48.571776, 51.173610, 385.214403], [20.821535, 21.154061, 66.752599], [24.297499, 29.036316, 67.720511], [55.225194, 57.874128, 286.111669], [26.298668, 27.386699, 29.390102], [28.480301, 34.840703, 76.164420], [36.724413, 42.459257, 106.624459]]
### 2
fourier: [[37.065548, 37.137289, 58.967441], [19.171747, 21.382044, 100.380725], [20.706907, 24.264023, 141.953197], [8.833590, 9.135530, 10.018557], [14.634860, 16.456062, 110.928723], [16.483227, 18.002888, 87.535901], [29.628935, 33.175100, 218.061087]]
### 4
fourier: [[8.471399, 8.600782, 110.071211], [4.779419, 5.167911, 67.947198], [10.455556, 10.809131, 25.213511], [33.637531, 34.381133, 34.520572], [22.659248, 23.761590, 102.906326], [11.057797, 13.165169, 47.215967], [16.630323, 19.396471, 151.154876]]
### 6
fourier: [[4.449704, 4.859763, 38.125073], [15.822778, 15.954026, 47.874332], [24.462114, 26.041855, 55.602363], [23.154791, 24.032989, 151.521243], [12.063915, 12.218280, 12.557646], [17.920364, 19.686407, 115.534557], [12.684583, 12.981551, 61.147870]]
### 8
fourier: [[17.095079, 17.221373, 18.283065], [14.240316, 17.906080, 108.768996], [7.589433, 7.807550, 8.214995], [22.112448, 22.805412, 35.295322], [21.371826, 25.048728, 158.518077], [26.500826, 29.549096, 164.727912], [23.079818, 25.408265, 149.938217]]
### 10
fourier: [[35.192948, 38.825076, 199.438058]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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],
[
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],
[
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]
],
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],
"network.2.weight": [
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],
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],
"network.4.weight": [
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"network.6.weight": [
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"network.8.weight": [
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[
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]
],
"network.10.bias": [
-0.099054
]
}
## Activation Signature
### 0
fourier: [[48.571776, 51.173610, 385.214403], [20.821535, 21.154061, 66.752599], [24.297499, 29.036316, 67.720511], [55.225194, 57.874128, 286.111669], [26.298668, 27.386699, 29.390102], [28.480301, 34.840703, 76.164420], [36.724413, 42.459257, 106.624459]]
### 2
fourier: [[37.065548, 37.137289, 58.967441], [19.171747, 21.382044, 100.380725], [20.706907, 24.264023, 141.953197], [8.833590, 9.135530, 10.018557], [14.634860, 16.456062, 110.928723], [16.483227, 18.002888, 87.535901], [29.628935, 33.175100, 218.061087]]
### 4
fourier: [[8.471399, 8.600782, 110.071211], [4.779419, 5.167911, 67.947198], [10.455556, 10.809131, 25.213511], [33.637531, 34.381133, 34.520572], [22.659248, 23.761590, 102.906326], [11.057797, 13.165169, 47.215967], [16.630323, 19.396471, 151.154876]]
### 6
fourier: [[4.449704, 4.859763, 38.125073], [15.822778, 15.954026, 47.874332], [24.462114, 26.041855, 55.602363], [23.154791, 24.032989, 151.521243], [12.063915, 12.218280, 12.557646], [17.920364, 19.686407, 115.534557], [12.684583, 12.981551, 61.147870]]
### 8
fourier: [[17.095079, 17.221373, 18.283065], [14.240316, 17.906080, 108.768996], [7.589433, 7.807550, 8.214995], [22.112448, 22.805412, 35.295322], [21.371826, 25.048728, 158.518077], [26.500826, 29.549096, 164.727912], [23.079818, 25.408265, 149.938217]]
### 10
fourier: [[35.192948, 38.825076, 199.438058]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [48.57177627068388, 51.1736097516226, 385.2144031971693]}, "1": {"fourier": [20.821534508091865, 21.15406069157412, 66.75259933620691]}, "2": {"fourier": [24.297498833936345, 29.0363163646157, 67.72051145136356]}, "3": {"fourier": [55.22519436733489, 57.87412790375939, 286.11166870594025]}, "4": {"fourier": [26.29866761107866, 27.386698995196785, 29.39010150070829]}, "5": {"fourier": [28.48030065105314, 34.84070313820505, 76.1644196510315]}, "6": {"fourier": [36.72441317243694, 42.459256903314085, 106.62445917725563]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [37.0655477330954, 37.137288857900195, 58.96744067966938]}, "1": {"fourier": [19.17174710529546, 21.382043607974893, 100.38072492182255]}, "2": {"fourier": [20.706906578345382, 24.264023435692405, 141.95319718122482]}, "3": {"fourier": [8.833589802238702, 9.135530396475358, 10.018556843684664]}, "4": {"fourier": [14.634860140759647, 16.45606177085736, 110.9287226125598]}, "5": {"fourier": [16.48322721326439, 18.002888480348542, 87.53590095043182]}, "6": {"fourier": [29.62893527469613, 33.17510046259179, 218.0610868036747]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [8.471398851129871, 8.600782161227572, 110.07121083140373]}, "1": {"fourier": [4.779418958544265, 5.167911087933112, 67.94719815254211]}, "2": {"fourier": [10.455556305055444, 10.809130777243762, 25.213510870933533]}, "3": {"fourier": [33.6375310717642, 34.381132871935115, 34.52057165501312]}, "4": {"fourier": [22.659247609476854, 23.76159032272582, 102.90632586181164]}, "5": {"fourier": [11.05779738410205, 13.165168805574298, 47.21596683561802]}, "6": {"fourier": [16.630322726414235, 19.396470689090677, 151.15487584471703]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [4.44970404012788, 4.8597627751404495, 38.12507313489914]}, "1": {"fourier": [15.822778369796435, 15.9540259891743, 47.87433233857155]}, "2": {"fourier": [24.46211430457013, 26.041855391295304, 55.602363254874945]}, "3": {"fourier": [23.154791341201, 24.032989395743733, 151.52124318480492]}, "4": {"fourier": [12.06391518785205, 12.218280412514092, 12.557646366239588]}, "5": {"fourier": [17.920364494186046, 19.68640651982295, 115.53455662727356]}, "6": {"fourier": [12.684583107683336, 12.981550646080331, 61.147869631648064]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [17.095078898842733, 17.22137280273263, 18.283065470156142]}, "1": {"fourier": [14.240316118410394, 17.906080384773706, 108.76899566501379]}, "2": {"fourier": [7.589433036486937, 7.807549756226494, 8.21499542801387]}, "3": {"fourier": [22.1124477556014, 22.80541190337779, 35.295322224497795]}, "4": {"fourier": [21.371826333794257, 25.048727642698896, 158.5180774256587]}, "5": {"fourier": [26.50082579305093, 29.5490959189357, 164.72791227698326]}, "6": {"fourier": [23.079818209882237, 25.408264974587777, 149.93821740150452]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [35.192947652349815, 38.825076440976666, 199.43805840611458]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": 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0.410673, 0.443203, 0.431732, -0.15323], [0.581847, -0.117171, 0.295027, -0.158818, -0.268434, 0.049382, 0.549003], [0.135335, -0.175865, -0.117894, -0.356766, -0.106239, 0.089976, -0.022016], [0.350099, -0.483183, -0.351847, -0.433764, 0.144167, -0.689366, 0.528603], [-0.102507, -0.499743, 0.202596, -0.496495, 0.317676, 0.009137, 0.343615]], "network.6.bias": [-0.271459, -0.045313, -0.090754, 0.430909, 0.161715, 0.168586, 0.113751], "network.8.weight": [[0.181599, -0.140813, 0.525662, 0.28756, -0.466987, -0.430774, -0.44703], [0.292723, 0.265953, 0.080071, 0.190954, 0.222451, 0.53225, 0.048275], [0.06521, 0.236277, -0.250595, -0.085456, 0.076608, 0.105039, 0.048495], [0.120009, 0.026131, 0.596743, -0.141652, -0.457566, -0.340623, -0.142981], [-0.196965, 0.109786, -0.125568, 0.447886, 0.263874, 0.414812, 0.435537], [0.140084, 0.196255, -0.366234, 0.448874, 0.348905, 0.322383, 0.415712], [0.422564, 0.203507, -0.423176, 0.151049, -0.217669, 0.563498, 0.117551]], "network.8.bias": [-0.06857, -0.15361, -0.026895, -0.022716, 0.221899, 0.419629, 0.654688], "network.10.weight": [[0.248326, -0.13477, 0.136456, 0.468797, -0.266785, -0.56126, -0.344372]], "network.10.bias": [-0.099054]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6840048432350159, "train_acc": 0.59, "val_loss": 0.7063709497451782, "val_acc": 0.44}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6545540392398834, "train_acc": 0.59, "val_loss": 0.6063823699951172, "val_acc": 0.66}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5230938941240311, "train_acc": 0.73, "val_loss": 0.26630860567092896, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.28151747584342957, "train_acc": 0.915, "val_loss": 0.12418270111083984, "val_acc": 0.96}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.3454822450876236, "train_acc": 0.88, "val_loss": 0.3736569881439209, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3581801950931549, "train_acc": 0.845, "val_loss": 0.0617281049489975, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2174004763364792, "train_acc": 0.915, "val_loss": 0.07989981770515442, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.23413047939538956, "train_acc": 0.92, "val_loss": 0.09430530667304993, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.2018783763051033, "train_acc": 0.915, "val_loss": 0.11378765106201172, "val_acc": 0.98}], "summary": {"total_epochs": 9, "degraded_epochs": 2, "improved_epochs": 7, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7063709497451782, "final_val_loss": 0.6063823699951172, "initial_val_acc": 0.44, "final_val_acc": 0.66, "best_val_acc": 0.66}, "improved_stage": {"initial_val_loss": 0.26630860567092896, "final_val_loss": 0.11378765106201172, "initial_val_acc": 0.94, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 8}, "improvement": 0.31999999999999995, "first_improvement_epoch": 1}} |
63 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.74, "improved_accuracy": 0.9, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6754, "learning_rate": 0.09550147353470761, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.8.bias": [
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}
## Activation Signature
### 0
fourier: [[38.272835, 41.213398, 230.292563], [65.095244, 65.864403, 192.027388], [44.284709, 51.406462, 349.742279], [53.245057, 53.409336, 166.198195], [38.081002, 38.772927, 177.253775], [31.002734, 34.870820, 224.517093]]
### 2
fourier: [[11.867635, 14.936126, 101.686386], [4.391929, 5.035936, 83.875926], [10.036917, 12.542321, 105.347768], [7.880384, 10.997876, 44.691275], [8.829287, 8.848800, 44.379891], [5.316519, 7.613612, 8.445724]]
### 4
fourier: [[11.813088, 12.715784, 85.623271], [2.544980, 3.432877, 7.318956], [2.245353, 2.791254, 11.889976], [1.571827, 2.018621, 102.178030], [5.808162, 6.751041, 160.263501], [9.540815, 10.157952, 130.383713]]
### 6
fourier: [[10.049141, 10.247051, 40.413801], [6.602085, 7.090271, 73.927842], [5.204473, 5.943115, 68.568729], [9.670911, 10.549945, 42.217764], [5.897272, 6.428061, 50.022261], [6.009968, 6.270616, 45.957368]]
### 8
fourier: [[18.040732, 19.175137, 100.402354]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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],
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]
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],
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],
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-0.352968,
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],
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[
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]
],
"network.8.bias": [
-0.630066
]
}
## Activation Signature
### 0
fourier: [[38.272835, 41.213398, 230.292563], [65.095244, 65.864403, 192.027388], [44.284709, 51.406462, 349.742279], [53.245057, 53.409336, 166.198195], [38.081002, 38.772927, 177.253775], [31.002734, 34.870820, 224.517093]]
### 2
fourier: [[11.867635, 14.936126, 101.686386], [4.391929, 5.035936, 83.875926], [10.036917, 12.542321, 105.347768], [7.880384, 10.997876, 44.691275], [8.829287, 8.848800, 44.379891], [5.316519, 7.613612, 8.445724]]
### 4
fourier: [[11.813088, 12.715784, 85.623271], [2.544980, 3.432877, 7.318956], [2.245353, 2.791254, 11.889976], [1.571827, 2.018621, 102.178030], [5.808162, 6.751041, 160.263501], [9.540815, 10.157952, 130.383713]]
### 6
fourier: [[10.049141, 10.247051, 40.413801], [6.602085, 7.090271, 73.927842], [5.204473, 5.943115, 68.568729], [9.670911, 10.549945, 42.217764], [5.897272, 6.428061, 50.022261], [6.009968, 6.270616, 45.957368]]
### 8
fourier: [[18.040732, 19.175137, 100.402354]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [38.27283488545699, 41.21339812242142, 230.2925629466772]}, "1": {"fourier": [65.09524422485045, 65.86440291094749, 192.02738842368126]}, "2": {"fourier": [44.28470897400824, 51.40646241368454, 349.742279201746]}, "3": {"fourier": [53.24505666963284, 53.40933596047914, 166.19819544255733]}, "4": {"fourier": [38.081002241053795, 38.772927005603655, 177.25377514958382]}, "5": {"fourier": [31.00273360713681, 34.87081960457146, 224.51709333062172]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [11.86763471783596, 14.936126274608513, 101.68638634681702]}, "1": {"fourier": [4.391929461098148, 5.035936061143695, 83.87592625617981]}, "2": {"fourier": [10.036917390658573, 12.542321425175668, 105.3477678000927]}, "3": {"fourier": [7.880383678630765, 10.997876001189404, 44.6912747323513]}, "4": {"fourier": [8.82928713561779, 8.848799773666391, 44.379891484975815]}, "5": {"fourier": [5.316518679913575, 7.613611800047581, 8.445724215358496]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [11.81308755613829, 12.715784474734868, 85.62327116727829]}, "1": {"fourier": [2.5449802181119687, 3.4328770893848466, 7.318955615162849]}, "2": {"fourier": [2.2453534258399843, 2.791254155854663, 11.8899757117033]}, "3": {"fourier": [1.5718269917924452, 2.018620722715092, 102.17802965641022]}, "4": {"fourier": [5.808161579364076, 6.751040767799634, 160.26350098848343]}, "5": {"fourier": [9.540815109787552, 10.157952060757253, 130.3837128356099]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [10.049141492300963, 10.247050765766252, 40.41380077600479]}, "1": {"fourier": [6.602084682146039, 7.090271401771334, 73.92784243822098]}, "2": {"fourier": [5.204472645765471, 5.943115323361265, 68.56872928142548]}, "3": {"fourier": [9.670911077571438, 10.549944666113854, 42.21776387095451]}, "4": {"fourier": [5.897271871646116, 6.428060624349146, 50.02226125448942]}, "5": {"fourier": [6.009967603511119, 6.270616477223813, 45.95736788213253]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [18.04073245285207, 19.175136554975044, 100.40235361456871]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.780781, -0.078713, -0.301783, -0.302477, -0.08032], [-1.58317, -0.758481, 0.266006, 0.226899, -0.168717], [-0.65729, -0.235388, -0.36892, -0.43016, -0.394657], [-1.111646, -0.918557, 0.146354, 0.071437, 0.464162], [0.181533, -0.676888, 0.077198, -0.621832, 0.301816], [-0.169534, -0.486407, -0.435139, -0.285087, 0.333684]], "network.0.bias": [-0.065637, 0.384508, -0.459305, 0.179174, -0.161969, -0.288549], "network.2.weight": [[-0.102237, -0.472445, -0.605638, -1.005598, -0.532607, 0.46791], [-1.03448, -0.566671, -0.777247, 0.177954, 0.122791, -0.396017], [0.215778, -0.756453, -0.584927, -0.695207, -0.40704, 0.005206], [-0.659435, -0.442579, -0.601835, -0.617272, -0.319239, -0.419069], [-0.057636, -0.107211, -1.368711, -0.702955, 0.031477, -0.560911], [-0.662088, -0.272621, -0.199781, -0.402353, -0.358754, 0.357587]], "network.2.bias": [-0.804592, 0.908347, -0.861312, 0.660293, 0.588046, 0.038405], "network.4.weight": [[0.396149, -0.830072, 0.17653, -0.782617, -1.717352, -0.454933], [-0.072979, -0.256268, 0.115822, 0.799195, -0.263392, -0.208425], [-0.024603, 0.27108, -0.218257, -0.711587, 0.231135, 0.209587], [0.423454, -0.201306, 0.34579, 0.615198, -0.353258, 0.120598], [0.475162, -0.276937, 1.173647, -0.507416, -0.388038, -0.26576], [-1.028253, 0.87659, -0.763553, 0.592179, 0.808222, 0.630881]], "network.4.bias": [0.842574, -0.113332, 0.099975, -0.992067, -0.950506, -0.086677], "network.6.weight": [[0.543768, 0.042788, 0.099163, -0.620997, -0.813252, -0.830452], [-0.952181, 0.636018, 0.440547, 0.709033, 0.357454, 0.306673], [0.590852, 0.303273, 0.325413, -0.402933, -0.36089, -0.350309], [0.891936, -0.23716, 0.23813, -0.027731, -0.752075, -0.668692], [0.577024, 0.631064, 0.01222, -0.106281, 0.317648, -0.516471], [0.566477, -0.9265, 0.298704, -0.094118, -0.478972, -0.30232]], "network.6.bias": [0.562911, -1.176441, -0.352968, 0.409069, 0.204782, -0.166487], "network.8.weight": [[0.979997, 0.608171, 0.653275, 0.814218, 0.973638, 1.173386]], "network.8.bias": [-0.630066]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6952185928821564, "train_acc": 0.445, "val_loss": 0.6975794434547424, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6865369081497192, "train_acc": 0.56, "val_loss": 0.6976040601730347, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6819860637187958, "train_acc": 0.56, "val_loss": 0.6797705292701721, "val_acc": 0.52}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6691661775112152, "train_acc": 0.56, "val_loss": 0.6463996767997742, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.661910742521286, "train_acc": 0.665, "val_loss": 0.618229329586029, "val_acc": 0.72}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5670814514160156, "train_acc": 0.765, "val_loss": 0.5173481106758118, "val_acc": 0.8}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.49617719650268555, "train_acc": 0.79, "val_loss": 0.4544874429702759, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.5050658881664276, "train_acc": 0.79, "val_loss": 0.4168272912502289, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.5042176991701126, "train_acc": 0.82, "val_loss": 0.5665152072906494, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.38553486764431, "train_acc": 0.865, "val_loss": 0.42111170291900635, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.3720230907201767, "train_acc": 0.825, "val_loss": 0.3997170329093933, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.32709455490112305, "train_acc": 0.88, "val_loss": 0.4723529517650604, "val_acc": 0.84}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.3278135657310486, "train_acc": 0.875, "val_loss": 0.3967851400375366, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.3035300225019455, "train_acc": 0.865, "val_loss": 0.3388371765613556, "val_acc": 0.88}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6975794434547424, "final_val_loss": 0.6463996767997742, "initial_val_acc": 0.52, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.618229329586029, "final_val_loss": 0.3388371765613556, "initial_val_acc": 0.72, "final_val_acc": 0.88, "best_val_acc": 0.9, "best_epoch": 10}, "improvement": 0.16000000000000003, "first_improvement_epoch": 3}} |
64 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.44, "improved_accuracy": 0.98, "improvement": 0.54, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9339, "learning_rate": 0.028907412749536947, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[27.776712, 32.841675, 137.870709], [34.299136, 34.614614, 59.992955], [29.604496, 30.573889, 32.092125], [24.423365, 24.448565, 33.397376], [34.276765, 41.645636, 87.058151], [13.586618, 14.702038, 72.224533]]
### 2
fourier: [[46.107891, 46.184886, 282.091449], [18.899460, 20.826583, 81.463670], [42.130493, 43.555851, 264.932625], [12.868228, 12.888447, 56.868693], [18.941077, 18.950137, 59.650958], [25.029277, 25.991015, 101.009218]]
### 4
fourier: [[64.049239, 64.690340, 342.572092], [55.953924, 59.717365, 322.397733], [27.786858, 29.363767, 72.339297], [22.889545, 24.178414, 85.677989], [23.667692, 24.696814, 81.764242], [7.040149, 7.392671, 7.523738]]
### 6
fourier: [[57.555980, 61.104879, 190.544050], [55.347349, 58.526751, 186.836794], [70.371877, 74.865906, 382.289750], [43.705699, 46.367703, 214.765727], [44.307814, 46.280763, 142.557797], [54.593265, 58.108125, 304.315175]]
### 8
fourier: [[77.286059, 83.484801, 248.688685], [27.837283, 28.139849, 49.242159], [79.366933, 85.629201, 239.614514], [95.306159, 102.487241, 447.458744], [61.976290, 66.978565, 236.840071], [94.276844, 101.664160, 436.064206]]
### 10
fourier: [[88.493950, 96.330787, 413.184077], [70.816626, 77.605936, 322.327997], [67.787238, 72.387304, 138.031293], [146.065963, 159.580399, 734.447992], [127.295182, 139.460243, 607.129203], [67.251807, 73.743803, 305.202018]]
### 12
fourier: [[284.728322, 313.595510, 1459.360817]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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],
[
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]
],
"network.0.bias": [
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[
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-0.443118,
0.361847
],
[
0.375748,
0.208125,
0.784377,
-0.638341,
-0.300464,
0.568755
],
[
-0.101473,
-0.193282,
-0.36265,
0.682436,
0.805548,
-0.625461
],
[
-0.342225,
-0.326199,
0.028713,
0.768819,
0.018861,
-0.737559
],
[
-0.502365,
-0.179153,
0.130623,
-0.030886,
0.628431,
-0.605913
],
[
0.340144,
-0.24019,
-0.155486,
-0.368683,
-0.142155,
0.369212
]
],
"network.4.bias": [
-0.113977,
-0.045584,
0.708734,
0.357057,
0.39276,
-0.457541
],
"network.6.weight": [
[
-0.438087,
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0.574188,
0.464996,
-0.699592
],
[
-0.639763,
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0.618898,
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0.465902,
-0.729634
],
[
0.586535,
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-0.358072,
-0.53551,
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],
[
0.101983,
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-0.105836,
-0.67997,
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],
[
-0.520682,
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0.831033,
0.661367,
-0.064293
],
[
0.164796,
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]
],
"network.6.bias": [
0.607438,
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0.109368,
0.429727,
0.421475
],
"network.8.weight": [
[
0.572596,
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-0.373309,
0.328783,
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],
[
-0.209103,
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0.14952,
0.346512,
-0.70131,
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],
[
0.814735,
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],
[
-0.408155,
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],
[
-0.659292,
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],
[
-0.391663,
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]
],
"network.8.bias": [
0.425354,
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0.275698,
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],
"network.10.weight": [
[
-0.201799,
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],
[
-0.052202,
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0.077751,
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],
[
0.560686,
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],
[
-0.43478,
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0.555584,
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],
[
-0.305647,
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0.623978,
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],
[
-0.12575,
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0.278386,
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]
],
"network.10.bias": [
0.070145,
0.007501,
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0.225023,
0.475009,
0.09682
],
"network.12.weight": [
[
-0.533296,
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0.629114,
-0.614348,
-0.668051,
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]
],
"network.12.bias": [
0.040569
]
}
## Activation Signature
### 0
fourier: [[27.776712, 32.841675, 137.870709], [34.299136, 34.614614, 59.992955], [29.604496, 30.573889, 32.092125], [24.423365, 24.448565, 33.397376], [34.276765, 41.645636, 87.058151], [13.586618, 14.702038, 72.224533]]
### 2
fourier: [[46.107891, 46.184886, 282.091449], [18.899460, 20.826583, 81.463670], [42.130493, 43.555851, 264.932625], [12.868228, 12.888447, 56.868693], [18.941077, 18.950137, 59.650958], [25.029277, 25.991015, 101.009218]]
### 4
fourier: [[64.049239, 64.690340, 342.572092], [55.953924, 59.717365, 322.397733], [27.786858, 29.363767, 72.339297], [22.889545, 24.178414, 85.677989], [23.667692, 24.696814, 81.764242], [7.040149, 7.392671, 7.523738]]
### 6
fourier: [[57.555980, 61.104879, 190.544050], [55.347349, 58.526751, 186.836794], [70.371877, 74.865906, 382.289750], [43.705699, 46.367703, 214.765727], [44.307814, 46.280763, 142.557797], [54.593265, 58.108125, 304.315175]]
### 8
fourier: [[77.286059, 83.484801, 248.688685], [27.837283, 28.139849, 49.242159], [79.366933, 85.629201, 239.614514], [95.306159, 102.487241, 447.458744], [61.976290, 66.978565, 236.840071], [94.276844, 101.664160, 436.064206]]
### 10
fourier: [[88.493950, 96.330787, 413.184077], [70.816626, 77.605936, 322.327997], [67.787238, 72.387304, 138.031293], [146.065963, 159.580399, 734.447992], [127.295182, 139.460243, 607.129203], [67.251807, 73.743803, 305.202018]]
### 12
fourier: [[284.728322, 313.595510, 1459.360817]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [27.77671212061191, 32.84167507507783, 137.87070852518082]}, "1": {"fourier": [34.2991361236357, 34.61461421424435, 59.99295464158058]}, "2": {"fourier": [29.604496344923973, 30.573889402942644, 32.09212452391073]}, "3": {"fourier": [24.42336505137793, 24.44856452528472, 33.397376490875736]}, "4": {"fourier": [34.27676465644308, 41.64563554794157, 87.05815099924803]}, "5": {"fourier": [13.586617939957861, 14.702038406984379, 72.22453335672617]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [46.10789148095049, 46.184886375412574, 282.09144869074225]}, "1": {"fourier": [18.89945978698748, 20.82658316983007, 81.46367044746876]}, "2": {"fourier": [42.13049291152296, 43.555850558954354, 264.93262518942356]}, "3": {"fourier": [12.868228093454196, 12.888446912918381, 56.868692725896835]}, "4": {"fourier": [18.94107730694977, 18.950136839028847, 59.65095818042755]}, "5": {"fourier": [25.029276615950717, 25.991014958249, 101.00921793282032]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [64.04923857865352, 64.69034020302551, 342.5720924735069]}, "1": {"fourier": [55.953924172130534, 59.717364968855215, 322.397732719779]}, "2": {"fourier": [27.786857524325605, 29.363766589530748, 72.3392972946167]}, "3": {"fourier": [22.889545325925578, 24.178413558570902, 85.67798937857151]}, "4": {"fourier": [23.667691947936316, 24.696813903896217, 81.76424184441566]}, "5": {"fourier": [7.040149015318388, 7.392671383357047, 7.5237376121305655]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [57.55598031421659, 61.10487880970842, 190.5440497994423]}, "1": {"fourier": [55.34734937817018, 58.52675078903024, 186.83679446578026]}, "2": {"fourier": [70.37187698335617, 74.86590625317855, 382.2897498309612]}, "3": {"fourier": [43.70569900467095, 46.367702751943334, 214.76572735607624]}, "4": {"fourier": [44.307814078693596, 46.28076275214408, 142.55779714882374]}, "5": {"fourier": [54.59326527082647, 58.10812498604048, 304.31517469882965]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [77.28605932199906, 83.48480054263189, 248.68868473172188]}, "1": {"fourier": [27.837282932630334, 28.139848574260697, 49.24215932190418]}, "2": {"fourier": [79.36693303415701, 85.62920089159549, 239.6145136654377]}, "3": {"fourier": [95.30615938241631, 102.4872410058711, 447.4587442725897]}, "4": {"fourier": [61.976290200257075, 66.97856521777027, 236.8400707244873]}, "5": {"fourier": [94.27684361818959, 101.6641602458567, 436.0642064213753]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [88.49394988892837, 96.33078746275135, 413.1840771883726]}, "1": {"fourier": [70.81662594687455, 77.60593593236547, 322.32799678109586]}, "2": {"fourier": [67.78723787708643, 72.38730373911353, 138.03129264712334]}, "3": {"fourier": [146.06596306252789, 159.58039917451475, 734.4479924440384]}, "4": {"fourier": [127.29518202563798, 139.46024274096774, 607.129203170538]}, "5": {"fourier": [67.2518074548381, 73.74380325395794, 305.2020181119442]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [284.7283219898692, 313.5955099444548, 1459.3608169928193]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.559779, -0.006415, 0.175278, 0.655136, -0.230604], [-0.639627, 0.122629, -0.204776, 0.423442, 0.115976], [-0.233528, -0.040362, -0.499713, 0.528798, 0.179983], [-0.5889, -0.095118, 0.411732, -0.154862, 0.503633], [-0.795892, 0.229366, 0.075063, 0.539707, 0.144767], [-0.20533, -0.253492, -0.086257, 0.011386, 0.131639]], "network.0.bias": [0.753571, 0.61578, 0.380989, -0.007071, 0.047085, -0.091645], "network.2.weight": [[0.611343, 0.649537, 0.533542, 0.31444, 0.542742, -0.568502], [0.024534, 0.150796, 0.378143, 0.598321, 0.243066, -0.5126], [0.41384, 0.352342, 0.245024, 0.667747, 0.780598, -0.109747], [-0.497659, -0.302812, -0.208666, -0.07448, 0.339756, 0.511412], [-0.655627, 0.118178, -0.610785, -0.12992, 0.179871, 0.622598], [0.029477, -0.414688, -0.440996, 0.629933, -0.312401, -0.3214]], "network.2.bias": [0.105534, -0.306903, 0.265985, 0.295468, 0.655344, -0.421953], "network.4.weight": [[0.571194, 0.609842, 0.560368, -0.568372, -0.443118, 0.361847], [0.375748, 0.208125, 0.784377, -0.638341, -0.300464, 0.568755], [-0.101473, -0.193282, -0.36265, 0.682436, 0.805548, -0.625461], [-0.342225, -0.326199, 0.028713, 0.768819, 0.018861, -0.737559], [-0.502365, -0.179153, 0.130623, -0.030886, 0.628431, -0.605913], [0.340144, -0.24019, -0.155486, -0.368683, -0.142155, 0.369212]], "network.4.bias": [-0.113977, -0.045584, 0.708734, 0.357057, 0.39276, -0.457541], "network.6.weight": [[-0.438087, -0.351072, 0.719223, 0.574188, 0.464996, -0.699592], [-0.639763, -0.103383, 0.618898, 0.559532, 0.465902, -0.729634], [0.586535, 0.525025, -0.358072, -0.53551, 0.029315, 0.387698], [0.101983, 0.574888, -0.388636, -0.105836, -0.67997, -0.135617], [-0.520682, -0.064734, 0.442057, 0.831033, 0.661367, -0.064293], [0.164796, 0.697046, -0.408698, -0.160659, -0.604569, -0.037429]], "network.6.bias": [0.607438, 0.560352, 0.212296, 0.109368, 0.429727, 0.421475], "network.8.weight": [[0.572596, 0.587785, -0.204174, -0.373309, 0.328783, -0.59447], [-0.209103, -0.156186, 0.14952, 0.346512, -0.70131, -0.18017], [0.814735, 0.391963, -0.29765, -0.708962, 0.452951, -0.218616], [-0.408155, -0.0608, 0.48377, 0.597617, -0.499451, 0.516215], [-0.659292, -0.313863, 0.332682, 0.200328, -0.389195, 0.29921], [-0.391663, -0.579771, 0.687682, 0.321147, -0.543055, 0.334328]], "network.8.bias": [0.425354, 0.08723, 0.39907, 0.043055, 0.275698, 0.587247], "network.10.weight": [[-0.201799, -0.493384, -0.302411, 0.676944, 0.460226, 0.059609], [-0.052202, -0.670576, -0.406484, 0.077751, 0.494057, 0.48935], [0.560686, -0.355375, 0.445543, -0.126245, -0.287326, -0.192239], [-0.43478, 0.231388, -0.17606, 0.604993, 0.555584, 0.615323], [-0.305647, -0.013262, -0.547044, 0.302753, 0.623978, 0.645978], [-0.12575, -0.062864, -0.339586, 0.102718, 0.278386, 0.437653]], "network.10.bias": [0.070145, 0.007501, 0.56474, 0.225023, 0.475009, 0.09682], "network.12.weight": [[-0.533296, -0.510505, 0.629114, -0.614348, -0.668051, -0.580195]], "network.12.bias": [0.040569]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6984916031360626, "train_acc": 0.585, "val_loss": 0.7583299279212952, "val_acc": 0.44}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.682537168264389, "train_acc": 0.585, "val_loss": 0.7314627170562744, "val_acc": 0.44}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6714454293251038, "train_acc": 0.585, "val_loss": 0.7044888138771057, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6668539047241211, "train_acc": 0.515, "val_loss": 0.6222271919250488, "val_acc": 0.44}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5623001456260681, "train_acc": 0.635, "val_loss": 0.4588010907173157, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.409513458609581, "train_acc": 0.875, "val_loss": 0.33154982328414917, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.30423836410045624, "train_acc": 0.915, "val_loss": 0.261812299489975, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.24197807908058167, "train_acc": 0.92, "val_loss": 0.22690723836421967, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.2053944319486618, "train_acc": 0.925, "val_loss": 0.14673824608325958, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.14428333193063736, "train_acc": 0.95, "val_loss": 0.10013547539710999, "val_acc": 0.98}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.3697284385561943, "train_acc": 0.93, "val_loss": 0.08890508860349655, "val_acc": 0.98}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.1895393505692482, "train_acc": 0.955, "val_loss": 0.09042507410049438, "val_acc": 0.98}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.1735616847872734, "train_acc": 0.955, "val_loss": 0.09105491638183594, "val_acc": 0.98}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7583299279212952, "final_val_loss": 0.7044888138771057, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.6222271919250488, "final_val_loss": 0.09105491638183594, "initial_val_acc": 0.44, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 9}, "improvement": 0.54, "first_improvement_epoch": 2}} |
65 | {"target_pattern": "ends_with", "degraded_accuracy": 0.46, "improved_accuracy": 0.82, "improvement": 0.35999999999999993, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 6958, "learning_rate": 0.08815082734579661, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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],
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[
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[
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[
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[
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],
[
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[
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],
"network.0.bias": [
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"network.2.weight": [
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[
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## Activation Signature
### 0
fourier: [[33.707095, 35.281255, 47.918882], [30.565379, 32.009338, 38.376557], [36.160628, 38.446273, 285.160211], [30.999982, 39.321719, 63.905630], [29.466178, 29.744797, 35.686859], [24.378771, 24.555727, 45.349533], [37.879686, 49.196586, 128.336297], [26.364178, 26.516246, 28.274746]]
### 2
fourier: [[20.439002, 23.736369, 91.107862], [52.722340, 53.275477, 152.790862], [41.012362, 57.339023, 110.668568], [52.743732, 59.958352, 277.750171], [24.480519, 24.714765, 149.012864], [14.961711, 16.155926, 17.527319], [25.312396, 25.532813, 28.010234], [8.364257, 8.688118, 90.583066]]
### 4
fourier: [[51.347034, 55.949145, 65.544736], [14.536898, 16.038354, 84.956935], [26.135294, 27.306950, 32.275219], [21.455992, 21.707983, 23.938670], [54.123496, 54.951427, 87.642503], [34.018615, 39.740661, 93.811274], [16.746996, 17.195617, 143.837926], [26.768151, 30.107204, 36.295540]]
### 6
fourier: [[16.316784, 19.161046, 53.154112], [71.743793, 72.115705, 99.151707], [32.525837, 35.715613, 36.849908], [42.051334, 44.096481, 45.344920], [42.688396, 46.695816, 57.181090], [22.231768, 26.479923, 141.511610], [54.856857, 59.958968, 114.168239], [4.005277, 4.280314, 78.381756]]
### 8
fourier: [[8.151403, 8.524253, 58.815642], [35.947347, 41.776981, 196.203060], [85.100683, 86.820279, 127.465373], [13.030009, 14.456801, 108.761515], [67.519117, 68.039742, 68.216809], [18.996171, 20.738976, 115.348445], [42.845199, 42.847324, 44.066242], [11.267200, 13.084530, 55.506206]]
### 10
fourier: [[51.570013, 52.870748, 59.059800]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[33.707095, 35.281255, 47.918882], [30.565379, 32.009338, 38.376557], [36.160628, 38.446273, 285.160211], [30.999982, 39.321719, 63.905630], [29.466178, 29.744797, 35.686859], [24.378771, 24.555727, 45.349533], [37.879686, 49.196586, 128.336297], [26.364178, 26.516246, 28.274746]]
### 2
fourier: [[20.439002, 23.736369, 91.107862], [52.722340, 53.275477, 152.790862], [41.012362, 57.339023, 110.668568], [52.743732, 59.958352, 277.750171], [24.480519, 24.714765, 149.012864], [14.961711, 16.155926, 17.527319], [25.312396, 25.532813, 28.010234], [8.364257, 8.688118, 90.583066]]
### 4
fourier: [[51.347034, 55.949145, 65.544736], [14.536898, 16.038354, 84.956935], [26.135294, 27.306950, 32.275219], [21.455992, 21.707983, 23.938670], [54.123496, 54.951427, 87.642503], [34.018615, 39.740661, 93.811274], [16.746996, 17.195617, 143.837926], [26.768151, 30.107204, 36.295540]]
### 6
fourier: [[16.316784, 19.161046, 53.154112], [71.743793, 72.115705, 99.151707], [32.525837, 35.715613, 36.849908], [42.051334, 44.096481, 45.344920], [42.688396, 46.695816, 57.181090], [22.231768, 26.479923, 141.511610], [54.856857, 59.958968, 114.168239], [4.005277, 4.280314, 78.381756]]
### 8
fourier: [[8.151403, 8.524253, 58.815642], [35.947347, 41.776981, 196.203060], [85.100683, 86.820279, 127.465373], [13.030009, 14.456801, 108.761515], [67.519117, 68.039742, 68.216809], [18.996171, 20.738976, 115.348445], [42.845199, 42.847324, 44.066242], [11.267200, 13.084530, 55.506206]]
### 10
fourier: [[51.570013, 52.870748, 59.059800]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [33.70709548358122, 35.28125509435573, 47.91888217335043]}, "1": {"fourier": [30.565379099711716, 32.00933786417841, 38.37655708032969]}, "2": {"fourier": [36.16062765583894, 38.44627275314237, 285.16021090745926]}, "3": {"fourier": [30.999982106819036, 39.32171924927062, 63.90562954545021]}, "4": {"fourier": [29.466177692087086, 29.744797370455526, 35.68685852204679]}, "5": {"fourier": [24.37877075398166, 24.55572688010036, 45.349533066153526]}, "6": {"fourier": [37.879685561565125, 49.19658611625865, 128.33629673719406]}, "7": {"fourier": [26.364177618297816, 26.51624558501188, 28.27474551230156]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [20.439002059068926, 23.736369415091787, 91.10786229372025]}, "1": {"fourier": [52.72233974219877, 53.27547731204019, 152.79086177051067]}, "2": {"fourier": [41.01236155752829, 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"8": {"neuron_profiles": {"0": {"fourier": [8.151403478893082, 8.524253472828699, 58.81564179062843]}, "1": {"fourier": [35.947347231535225, 41.77698089326927, 196.20306038856506]}, "2": {"fourier": [85.1006829949051, 86.8202791836366, 127.46537306904793]}, "3": {"fourier": [13.030008859341066, 14.4568008180502, 108.76151531934738]}, "4": {"fourier": [67.51911682340878, 68.03974217729508, 68.21680943024839]}, "5": {"fourier": [18.996170850801096, 20.738976285333713, 115.34844499826431]}, "6": {"fourier": [42.845198612558015, 42.84732439556444, 44.06624172924828]}, "7": {"fourier": [11.267199550019708, 13.084530073501583, 55.50620572268963]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [51.57001267540877, 52.87074798193151, 59.05980043113232]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.922671, -0.231093, -0.14393, -0.284238, 0.306533], [0.621179, -0.068939, -0.209219, -0.324398, 0.560517], [-0.256047, -0.670645, -0.157623, -0.220294, -0.213989], [0.187402, 0.141136, -0.271991, 0.602249, -0.682499], [-0.656722, -0.04295, -0.163823, 0.131678, 0.786188], [0.12003, -0.456766, 0.348575, 0.117969, 0.261889], [0.837593, -0.127003, 0.024039, -0.147151, 0.508853], [-0.565996, -0.042526, 0.03633, -0.059045, 0.768605]], "network.0.bias": [0.005744, -0.214546, -0.562162, 0.338088, -0.121996, -0.117267, 0.252804, 0.049642], "network.2.weight": [[-0.12222, -0.371182, 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0.47812584042549133, "initial_val_acc": 0.78, "final_val_acc": 0.8, "best_val_acc": 0.82, "best_epoch": 4}, "improvement": 0.35999999999999993, "first_improvement_epoch": 2}} |
66 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.62, "improved_accuracy": 0.98, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7617, "learning_rate": 0.01839529955470709, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.077867
],
"network.12.weight": [
[
0.253455,
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0.177639,
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"network.12.bias": [
-0.047728
]
}
## Activation Signature
### 0
fourier: [[14.877933, 21.321644, 38.943789], [19.469300, 22.146203, 23.023207], [16.167504, 17.790599, 68.391038], [26.161118, 30.457722, 82.095027], [17.428817, 19.033519, 49.056390], [36.075652, 39.171547, 264.832357], [21.423243, 22.019793, 87.104168]]
### 2
fourier: [[6.098908, 6.641013, 39.820616], [19.469187, 21.778881, 164.016025], [8.499824, 9.190594, 11.673995], [15.117690, 16.602098, 69.615813], [25.021531, 26.042285, 114.950077], [13.408329, 16.112410, 20.286268], [8.945604, 9.340486, 10.135153]]
### 4
fourier: [[3.914691, 3.961027, 29.912162], [8.324889, 9.260640, 33.371821], [6.751006, 7.447216, 57.699130], [11.254383, 11.918162, 13.585580], [2.107645, 2.378668, 18.010114], [12.861018, 13.580195, 42.275536], [7.767520, 8.038337, 9.161099]]
### 6
fourier: [[7.225938, 7.304218, 20.112863], [3.424836, 3.853283, 7.323380], [8.247635, 9.518849, 22.619016], [7.653117, 7.879665, 35.665505], [4.860102, 5.637199, 46.318580], [9.178902, 9.299690, 44.873969], [8.094158, 8.504436, 69.247619]]
### 8
fourier: [[6.233034, 6.304611, 30.966186], [4.777220, 4.833955, 15.119102], [6.487207, 6.622437, 18.563077], [1.661565, 1.839435, 11.991906], [12.419938, 12.771118, 91.057472], [6.703622, 6.946301, 62.300922], [8.577654, 8.863921, 78.749656]]
### 10
fourier: [[6.508229, 6.684885, 29.892828], [6.236019, 6.500191, 44.954141], [4.248874, 4.528305, 4.739171], [13.696144, 14.162826, 111.280704], [6.162113, 6.431430, 48.707274], [7.097904, 7.382819, 63.801525], [6.634179, 6.780389, 37.640369]]
### 12
fourier: [[12.324601, 12.753108, 84.305371]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[14.877933, 21.321644, 38.943789], [19.469300, 22.146203, 23.023207], [16.167504, 17.790599, 68.391038], [26.161118, 30.457722, 82.095027], [17.428817, 19.033519, 49.056390], [36.075652, 39.171547, 264.832357], [21.423243, 22.019793, 87.104168]]
### 2
fourier: [[6.098908, 6.641013, 39.820616], [19.469187, 21.778881, 164.016025], [8.499824, 9.190594, 11.673995], [15.117690, 16.602098, 69.615813], [25.021531, 26.042285, 114.950077], [13.408329, 16.112410, 20.286268], [8.945604, 9.340486, 10.135153]]
### 4
fourier: [[3.914691, 3.961027, 29.912162], [8.324889, 9.260640, 33.371821], [6.751006, 7.447216, 57.699130], [11.254383, 11.918162, 13.585580], [2.107645, 2.378668, 18.010114], [12.861018, 13.580195, 42.275536], [7.767520, 8.038337, 9.161099]]
### 6
fourier: [[7.225938, 7.304218, 20.112863], [3.424836, 3.853283, 7.323380], [8.247635, 9.518849, 22.619016], [7.653117, 7.879665, 35.665505], [4.860102, 5.637199, 46.318580], [9.178902, 9.299690, 44.873969], [8.094158, 8.504436, 69.247619]]
### 8
fourier: [[6.233034, 6.304611, 30.966186], [4.777220, 4.833955, 15.119102], [6.487207, 6.622437, 18.563077], [1.661565, 1.839435, 11.991906], [12.419938, 12.771118, 91.057472], [6.703622, 6.946301, 62.300922], [8.577654, 8.863921, 78.749656]]
### 10
fourier: [[6.508229, 6.684885, 29.892828], [6.236019, 6.500191, 44.954141], [4.248874, 4.528305, 4.739171], [13.696144, 14.162826, 111.280704], [6.162113, 6.431430, 48.707274], [7.097904, 7.382819, 63.801525], [6.634179, 6.780389, 37.640369]]
### 12
fourier: [[12.324601, 12.753108, 84.305371]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [14.877933436670698, 21.321643550027407, 38.94378939270973]}, "1": {"fourier": [19.469299525022507, 22.146203236053303, 23.023206887355244]}, "2": {"fourier": [16.167504004835163, 17.7905988502551, 68.39103849232197]}, "3": {"fourier": [26.16111833915375, 30.457721964796264, 82.09502722322941]}, "4": {"fourier": [17.428816567527722, 19.03351898686753, 49.056390315294266]}, "5": {"fourier": [36.07565174796018, 39.171547293145885, 264.8323573321104]}, "6": {"fourier": [21.423243314614126, 22.019793429609344, 87.10416775941849]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [6.098908024235237, 6.641012912049709, 39.82061644643545]}, "1": {"fourier": [19.46918745630794, 21.778880541014548, 164.0160252302885]}, "2": {"fourier": [8.499824391953984, 9.19059364790539, 11.673995481070625]}, "3": {"fourier": [15.117689567694075, 16.602097612919714, 69.61581317335367]}, "4": {"fourier": [25.02153121801668, 26.04228534855517, 114.95007694512606]}, "5": {"fourier": [13.408328723406015, 16.11241028000869, 20.28626823425293]}, "6": {"fourier": [8.945604314513789, 9.340486249270189, 10.135153330604403]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [3.9146913297958497, 3.961027313646819, 29.912162482738495]}, "1": {"fourier": [8.324889166524708, 9.260639809279066, 33.371821232140064]}, "2": {"fourier": [6.751006173807299, 7.4472164958039215, 57.69912973046303]}, "3": {"fourier": [11.25438328603252, 11.918162157061627, 13.585580271311429]}, "4": {"fourier": [2.1076452946970146, 2.3786682189937434, 18.010114088654518]}, "5": {"fourier": [12.861017842712881, 13.58019540604588, 42.27553607523441]}, "6": {"fourier": [7.767520067129015, 8.0383370988969, 9.161099025882514]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [7.225937683826735, 7.304217682772505, 20.112862572073936]}, "1": {"fourier": [3.4248364187408296, 3.8532832880913364, 7.323380269110203]}, "2": {"fourier": [8.247635129387666, 9.51884897503192, 22.619016207754612]}, "3": {"fourier": [7.653117169412068, 7.879665210313479, 35.66550526022911]}, "4": {"fourier": [4.860102268366507, 5.637198717828431, 46.31857971847057]}, "5": {"fourier": [9.178901663987572, 9.299689524530661, 44.87396914511919]}, "6": {"fourier": [8.094158206966704, 8.504435629304744, 69.24761936068535]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [6.233033580662506, 6.304610605763339, 30.966185986995697]}, "1": {"fourier": [4.777220352471647, 4.833954596100933, 15.119101539254189]}, "2": {"fourier": [6.48720740609935, 6.622437163112828, 18.56307728588581]}, "3": {"fourier": 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"num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [12.32460104394028, 12.753107749477888, 84.30537134408951]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.123236, -0.182556, 0.143932, -0.138155, 0.365391], [-0.272537, 0.385595, -0.150616, -0.211023, -0.299084], [-0.351313, 0.073131, 0.489847, -0.066616, -0.099353], [0.506821, 0.302292, 0.201738, -0.273405, -0.043115], [-0.307451, -0.215044, -0.078782, -0.122569, 0.238693], [0.236968, -0.167553, 0.45003, 0.481743, 0.547], [-0.067871, 0.251104, -0.229707, 0.438526, -0.109242]], "network.0.bias": [0.463685, 0.556208, 0.305983, -0.051318, 0.362414, 0.305239, 0.268887], "network.2.weight": [[-0.020006, 0.168318, 0.086198, -0.119897, -0.061813, -0.035073, -0.208489], [0.029757, 0.166499, 0.284334, -0.489081, 0.181728, 0.458327, 0.349935], [-0.123236, -0.2519, -0.046009, 0.073894, 0.371241, 0.204419, -0.113632], [0.388349, 0.11218, 0.237006, -0.336233, -0.049979, -0.264976, -0.005838], [-0.57941, -0.057215, 0.30543, -0.135988, -0.289723, -0.433758, 0.290788], [-0.563005, -0.252835, -0.345196, 0.399058, 0.164475, 0.05662, 0.040581], [-0.051749, -0.127278, 0.021775, 0.393252, 0.084797, -0.122286, -0.109299]], "network.2.bias": [-0.094585, 0.362093, -0.390973, -0.046106, -0.104633, 0.19074, 0.193816], "network.4.weight": [[0.107535, -0.030808, 0.362527, 0.057791, 0.069132, -0.307951, -0.180546], [0.035083, 0.301272, 0.078857, -0.432194, 0.026272, -0.014256, 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0.14729, 0.514988, -0.17128]], "network.6.bias": [0.139724, 0.14814, 0.108468, -0.192595, 0.399038, 0.087428, 0.488451], "network.8.weight": [[0.148435, -0.193792, 0.469888, -0.143542, 0.521733, 0.228865, 0.063738], [0.244042, -0.176354, 0.194485, -0.284638, 0.345864, 0.257289, 0.082296], [0.372583, -0.188322, -0.408905, 0.401179, -0.229729, -0.085183, -0.249999], [-0.027724, -0.003456, 0.030017, -0.542832, 0.011823, -0.225723, -0.160298], [-0.33378, -0.156133, 0.488392, -0.550342, 0.377266, 0.457225, 0.481061], [0.07386, -0.24208, 0.020736, -0.5252, 0.108421, 0.413179, 0.278751], [-0.030365, -0.246445, 0.272935, -0.241067, 0.288172, 0.302442, 0.430375]], "network.8.bias": [-0.103886, -0.178387, 0.230969, 0.281667, 0.20017, 0.266395, 0.285936], "network.10.weight": [[-0.269958, -0.285763, 0.360955, -0.322091, -0.250844, 0.085705, -0.164819], [-0.219188, 0.374428, -0.153021, -0.095055, 0.442125, -0.208141, 0.212603], [0.213797, -0.196248, -0.350394, -0.404213, 0.28662, -0.202921, 0.106298], [0.376936, -0.081774, -0.279005, -0.152243, 0.365325, 0.543005, 0.43671], [-0.283177, 0.042659, -0.443024, 0.149046, 0.188747, 0.220386, 0.341946], [-0.402167, 0.11504, 0.438634, 0.396668, -0.474021, -0.122391, 0.248748], [0.285655, 0.31334, -0.223435, 0.298924, 0.083795, 0.426843, 0.046307]], "network.10.bias": [0.121018, 0.057203, -0.254086, 0.177599, 0.025942, -0.310053, -0.077867], "network.12.weight": [[0.253455, -0.40003, -0.369222, -0.425375, -0.296481, 0.177639, -0.230032]], "network.12.bias": [-0.047728]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6925990581512451, "train_acc": 0.55, "val_loss": 0.6800563931465149, "val_acc": 0.62}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6862382292747498, "train_acc": 0.55, "val_loss": 0.6720321774482727, "val_acc": 0.62}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.683437168598175, "train_acc": 0.55, "val_loss": 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"improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.23302293568849564, "train_acc": 0.925, "val_loss": 0.1365663856267929, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.20128801465034485, "train_acc": 0.935, "val_loss": 0.11909469962120056, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.1946491077542305, "train_acc": 0.935, "val_loss": 0.11610188335180283, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.1661064699292183, "train_acc": 0.93, "val_loss": 0.12031945586204529, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.18541884422302246, "train_acc": 0.935, "val_loss": 0.12689706683158875, "val_acc": 0.96}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6800563931465149, "final_val_loss": 0.6175773739814758, "initial_val_acc": 0.62, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.5103480815887451, "final_val_loss": 0.12689706683158875, "initial_val_acc": 0.62, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 5}, "improvement": 0.36, "first_improvement_epoch": 3}} |
67 | {"target_pattern": "has_majority", "degraded_accuracy": 0.44, "improved_accuracy": 0.88, "improvement": 0.44, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7511, "learning_rate": 0.058202799735515814, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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],
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[
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[
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],
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[
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],
[
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[
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],
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],
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[
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]
],
"network.8.bias": [
1.005421
]
}
## Activation Signature
### 0
fourier: [[23.037814, 26.604670, 223.996380], [37.728966, 39.068386, 44.209545], [69.818484, 70.909956, 89.502612], [33.481955, 33.726597, 247.438273], [38.842366, 39.234084, 206.964284]]
### 2
fourier: [[11.671191, 11.722423, 27.491271], [8.872848, 10.003354, 116.017977], [14.324894, 14.775585, 64.589530], [24.434996, 25.619174, 71.527377], [17.534581, 21.061178, 120.388003]]
### 4
fourier: [[3.580651, 3.681949, 57.929061], [11.821634, 14.215521, 45.855696], [21.892634, 23.182570, 83.320631], [25.630795, 27.335041, 175.204665], [22.772069, 24.390919, 130.361711]]
### 6
fourier: [[18.135390, 19.216154, 47.662108], [19.106401, 20.112257, 115.590155], [1.974897, 1.977879, 48.759417], [18.034688, 19.061092, 46.584580], [20.017645, 21.211105, 52.800765]]
### 8
fourier: [[28.485118, 30.196292, 30.265756]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.218909,
-0.139166,
-0.410866,
-0.189458,
-0.144562
],
[
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-0.012578,
0.661087,
-0.748673
],
[
-1.629925,
-0.235516,
0.053759,
0.491663,
0.158244
],
[
-0.275775,
-0.120306,
-0.344774,
-0.047736,
-0.559401
],
[
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0.420808,
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]
],
"network.0.bias": [
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0.101232,
-0.674415,
-0.744768
],
"network.2.weight": [
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0.095381,
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],
[
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-0.340297,
-0.241758
],
[
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0.598173,
0.003529,
-0.361043,
0.189028
],
[
0.129635,
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0.570915,
-0.21327,
0.615395
],
[
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-0.227387
]
],
"network.2.bias": [
0.014287,
-0.620729,
-0.091992,
-0.35568,
-0.125348
],
"network.4.weight": [
[
-0.118089,
-0.1402,
-0.245145,
-0.012331,
-0.023531
],
[
0.103643,
0.257642,
0.370203,
-0.638234,
-0.529092
],
[
0.221692,
-0.067152,
-0.088158,
0.987855,
-0.039249
],
[
-0.232843,
0.00292,
-1.080644,
-0.796238,
0.16544
],
[
0.077449,
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-0.992013,
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0.328089
]
],
"network.4.bias": [
-0.399192,
-0.154976,
-0.148336,
-0.220735,
0.084267
],
"network.6.weight": [
[
-0.089762,
-0.556288,
0.835569,
0.518819,
-0.220826
],
[
0.08986,
0.03797,
-0.932049,
-0.095642,
0.108665
],
[
0.341852,
-0.429884,
-0.05998,
-0.268395,
0.252624
],
[
-0.034759,
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0.871048,
-0.164628,
0.135163
],
[
-0.035388,
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0.912784,
0.15142,
-0.381664
]
],
"network.6.bias": [
-0.259139,
-0.353888,
-0.447487,
-0.3429,
-0.266053
],
"network.8.weight": [
[
-0.83814,
0.090644,
0.191403,
-0.727209,
-0.27931
]
],
"network.8.bias": [
1.005421
]
}
## Activation Signature
### 0
fourier: [[23.037814, 26.604670, 223.996380], [37.728966, 39.068386, 44.209545], [69.818484, 70.909956, 89.502612], [33.481955, 33.726597, 247.438273], [38.842366, 39.234084, 206.964284]]
### 2
fourier: [[11.671191, 11.722423, 27.491271], [8.872848, 10.003354, 116.017977], [14.324894, 14.775585, 64.589530], [24.434996, 25.619174, 71.527377], [17.534581, 21.061178, 120.388003]]
### 4
fourier: [[3.580651, 3.681949, 57.929061], [11.821634, 14.215521, 45.855696], [21.892634, 23.182570, 83.320631], [25.630795, 27.335041, 175.204665], [22.772069, 24.390919, 130.361711]]
### 6
fourier: [[18.135390, 19.216154, 47.662108], [19.106401, 20.112257, 115.590155], [1.974897, 1.977879, 48.759417], [18.034688, 19.061092, 46.584580], [20.017645, 21.211105, 52.800765]]
### 8
fourier: [[28.485118, 30.196292, 30.265756]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [23.03781371696415, 26.604669917334896, 223.99638044834137]}, "1": {"fourier": [37.728966424621525, 39.06838620807806, 44.20954516530037]}, "2": {"fourier": [69.81848360658825, 70.90995641498337, 89.50261165201664]}, "3": {"fourier": [33.48195460279055, 33.72659697500368, 247.4382734298706]}, "4": {"fourier": [38.842365500443094, 39.23408408379923, 206.96428427100182]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [11.671191215176941, 11.72242349820309, 27.491271451115608]}, "1": {"fourier": [8.87284823900422, 10.003353576244965, 116.01797652244568]}, "2": {"fourier": [14.324893994778959, 14.775585216341824, 64.58953040093184]}, "3": {"fourier": [24.434995879083147, 25.619173783847792, 71.52737675607204]}, "4": {"fourier": [17.53458108708815, 21.06117830719629, 120.38800287246704]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [3.580650925791065, 3.6819485834273213, 57.929060995578766]}, "1": {"fourier": [11.821633640135902, 14.215521101192751, 45.85569637268782]}, "2": {"fourier": [21.892634458411315, 23.182570493572797, 83.32063076645136]}, "3": {"fourier": [25.630795086008895, 27.335041022839917, 175.20466461777687]}, "4": {"fourier": [22.77206931093328, 24.390918515721538, 130.36171109229326]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [18.13538989979283, 19.21615441864138, 47.662107810378075]}, "1": {"fourier": [19.10640073260972, 20.11225687214169, 115.59015539288521]}, "2": {"fourier": [1.9748967409082416, 1.9778786978522014, 48.75941699743271]}, "3": {"fourier": [18.03468834115203, 19.061091565444674, 46.58457958698273]}, "4": {"fourier": [20.017644928011478, 21.211104509783688, 52.80076503753662]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [28.48511751283666, 30.196291764090923, 30.26575642808138]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.218909, -0.139166, -0.410866, -0.189458, -0.144562], [0.455054, -1.031851, -0.012578, 0.661087, -0.748673], [-1.629925, -0.235516, 0.053759, 0.491663, 0.158244], [-0.275775, -0.120306, -0.344774, -0.047736, -0.559401], [0.501103, 0.002386, 0.420808, 0.785618, -0.119438]], "network.0.bias": [-0.520008, 0.354726, 0.101232, -0.674415, -0.744768], "network.2.weight": [[-0.453533, -0.701882, 0.068312, 0.095381, 0.272092], [-0.132805, -0.008575, -0.111097, -0.340297, -0.241758], [-0.261651, 0.598173, 0.003529, -0.361043, 0.189028], [0.129635, -1.273559, 0.570915, -0.21327, 0.615395], [0.081506, -0.469451, -0.527539, 0.18651, -0.227387]], "network.2.bias": [0.014287, -0.620729, -0.091992, -0.35568, -0.125348], "network.4.weight": [[-0.118089, -0.1402, -0.245145, -0.012331, -0.023531], [0.103643, 0.257642, 0.370203, -0.638234, -0.529092], [0.221692, -0.067152, -0.088158, 0.987855, -0.039249], [-0.232843, 0.00292, -1.080644, -0.796238, 0.16544], [0.077449, -0.660933, -0.992013, -0.807695, 0.328089]], "network.4.bias": [-0.399192, -0.154976, -0.148336, -0.220735, 0.084267], "network.6.weight": [[-0.089762, -0.556288, 0.835569, 0.518819, -0.220826], [0.08986, 0.03797, -0.932049, -0.095642, 0.108665], [0.341852, -0.429884, -0.05998, -0.268395, 0.252624], [-0.034759, -0.167732, 0.871048, -0.164628, 0.135163], [-0.035388, -0.697178, 0.912784, 0.15142, -0.381664]], "network.6.bias": [-0.259139, -0.353888, -0.447487, -0.3429, -0.266053], "network.8.weight": [[-0.83814, 0.090644, 0.191403, -0.727209, -0.27931]], "network.8.bias": [1.005421]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6900487244129181, "train_acc": 0.495, "val_loss": 0.710564374923706, "val_acc": 0.44}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.642049252986908, "train_acc": 0.595, "val_loss": 0.8331036567687988, "val_acc": 0.44}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6645365953445435, "train_acc": 0.595, "val_loss": 0.7497547268867493, "val_acc": 0.44}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6431227326393127, "train_acc": 0.595, "val_loss": 0.699270486831665, "val_acc": 0.44}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6242098808288574, "train_acc": 0.595, "val_loss": 0.6653643846511841, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6203830540180206, "train_acc": 0.56, "val_loss": 0.5995685458183289, "val_acc": 0.62}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5815898776054382, "train_acc": 0.715, "val_loss": 0.5395770072937012, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5457005798816681, "train_acc": 0.755, "val_loss": 0.5284205079078674, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5256235301494598, "train_acc": 0.77, "val_loss": 0.4890058934688568, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5264388024806976, "train_acc": 0.785, "val_loss": 0.46596962213516235, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.4966884106397629, "train_acc": 0.78, "val_loss": 0.4520336985588074, "val_acc": 0.8}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.5106630176305771, "train_acc": 0.765, "val_loss": 0.43835771083831787, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.5140398144721985, "train_acc": 0.78, "val_loss": 0.4105800688266754, "val_acc": 0.84}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.4980398863554001, "train_acc": 0.77, "val_loss": 0.42503470182418823, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.4878149628639221, "train_acc": 0.78, "val_loss": 0.38192611932754517, "val_acc": 0.88}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.710564374923706, "final_val_loss": 0.6653643846511841, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.5995685458183289, "final_val_loss": 0.38192611932754517, "initial_val_acc": 0.62, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 14}, "improvement": 0.44, "first_improvement_epoch": 4}} |
68 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.8, "improved_accuracy": 0.98, "improvement": 0.17999999999999994, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1256, "learning_rate": 0.06504650220298641, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[26.900243, 29.563913, 157.499262], [31.314794, 33.618976, 146.517468], [19.777054, 21.928201, 48.561374], [25.903330, 26.617744, 164.804384], [21.412010, 26.669752, 29.017326], [37.331400, 39.805113, 104.998677], [20.012441, 20.763330, 22.151158], [15.636544, 15.888378, 71.620524]]
### 2
fourier: [[32.714065, 35.973394, 138.994930], [18.256958, 18.505560, 19.353260], [18.906807, 20.266491, 87.705866], [27.107227, 29.087566, 129.287982], [23.683536, 24.315727, 128.365341], [12.925756, 13.557097, 14.522572], [8.829054, 9.769132, 97.944318], [23.416683, 25.676756, 137.343539]]
### 4
fourier: [[23.814305, 24.628128, 113.662792], [11.702816, 13.040324, 68.695256], [37.601275, 40.314869, 106.691930], [36.689605, 38.186722, 167.200798], [34.845840, 35.386787, 38.152984], [14.159787, 14.545996, 76.837672], [13.168426, 13.289668, 14.052449], [37.774796, 38.188265, 41.313125]]
### 6
fourier: [[28.411547, 29.101783, 30.058220], [31.858077, 32.400307, 117.835644], [43.435978, 44.809166, 45.470573], [3.703408, 4.144351, 17.720708], [51.073505, 52.174887, 181.964784], [23.115285, 23.465641, 24.113372], [44.428351, 45.400706, 71.952271], [59.239280, 61.291839, 158.688371]]
### 8
fourier: [[60.083729, 60.888894, 118.372139], [31.991781, 32.761196, 128.792480], [48.314081, 48.677900, 195.503571], [42.438043, 42.690579, 146.907507], [36.969556, 38.085188, 155.602127], [27.680465, 27.768248, 144.497437], [88.881176, 90.674512, 240.455794], [60.071287, 60.891390, 174.928150]]
### 10
fourier: [[82.612912, 82.999133, 408.075989]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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## Activation Signature
### 0
fourier: [[26.900243, 29.563913, 157.499262], [31.314794, 33.618976, 146.517468], [19.777054, 21.928201, 48.561374], [25.903330, 26.617744, 164.804384], [21.412010, 26.669752, 29.017326], [37.331400, 39.805113, 104.998677], [20.012441, 20.763330, 22.151158], [15.636544, 15.888378, 71.620524]]
### 2
fourier: [[32.714065, 35.973394, 138.994930], [18.256958, 18.505560, 19.353260], [18.906807, 20.266491, 87.705866], [27.107227, 29.087566, 129.287982], [23.683536, 24.315727, 128.365341], [12.925756, 13.557097, 14.522572], [8.829054, 9.769132, 97.944318], [23.416683, 25.676756, 137.343539]]
### 4
fourier: [[23.814305, 24.628128, 113.662792], [11.702816, 13.040324, 68.695256], [37.601275, 40.314869, 106.691930], [36.689605, 38.186722, 167.200798], [34.845840, 35.386787, 38.152984], [14.159787, 14.545996, 76.837672], [13.168426, 13.289668, 14.052449], [37.774796, 38.188265, 41.313125]]
### 6
fourier: [[28.411547, 29.101783, 30.058220], [31.858077, 32.400307, 117.835644], [43.435978, 44.809166, 45.470573], [3.703408, 4.144351, 17.720708], [51.073505, 52.174887, 181.964784], [23.115285, 23.465641, 24.113372], [44.428351, 45.400706, 71.952271], [59.239280, 61.291839, 158.688371]]
### 8
fourier: [[60.083729, 60.888894, 118.372139], [31.991781, 32.761196, 128.792480], [48.314081, 48.677900, 195.503571], [42.438043, 42.690579, 146.907507], [36.969556, 38.085188, 155.602127], [27.680465, 27.768248, 144.497437], [88.881176, 90.674512, 240.455794], [60.071287, 60.891390, 174.928150]]
### 10
fourier: [[82.612912, 82.999133, 408.075989]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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[18.90680731599291, 20.266491476837835, 87.70586597919464]}, "3": {"fourier": [27.107226738657936, 29.087566412190732, 129.28798206150532]}, "4": {"fourier": [23.683535910280323, 24.315726895061495, 128.36534118652344]}, "5": {"fourier": [12.925755986963024, 13.557096605328523, 14.522572291737301]}, "6": {"fourier": [8.829053753747159, 9.769131518253909, 97.9443176984787]}, "7": {"fourier": [23.41668292400171, 25.676755875947112, 137.34353850781918]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [23.814304664862302, 24.628127627419342, 113.66279167681932]}, "1": {"fourier": [11.702816267254713, 13.040323639837732, 68.69525629281998]}, "2": {"fourier": [37.60127485046535, 40.314868556869875, 106.69192978739738]}, "3": {"fourier": [36.68960482308425, 38.18672196618898, 167.20079815387726]}, "4": {"fourier": [34.84584013584341, 35.38678711261893, 38.15298417632486]}, "5": {"fourier": [14.159787303160469, 14.545996210788672, 76.83767229318619]}, "6": {"fourier": [13.168425626690166, 13.289667644018309, 14.052448910788078]}, "7": {"fourier": [37.77479589535594, 38.18826456676162, 41.31312470124511]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [28.41154747091748, 29.101783322745835, 30.058219647519124]}, "1": {"fourier": [31.858076645441212, 32.40030707004902, 117.83564428985119]}, "2": {"fourier": [43.43597805753693, 44.80916564879279, 45.47057255357504]}, "3": {"fourier": [3.703407717670378, 4.144351023123535, 17.720707967877388]}, "4": {"fourier": [51.07350484492333, 52.17488702413126, 181.9647836983204]}, "5": {"fourier": [23.11528485595332, 23.465640819386735, 24.113372407117097]}, "6": {"fourier": [44.42835069174555, 45.400706181777075, 71.95227134227753]}, "7": {"fourier": [59.239280293849774, 61.29183928982846, 158.68837118148804]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [60.08372942690652, 60.888893760004365, 118.37213855981827]}, "1": {"fourier": [31.99178114642147, 32.761195713142406, 128.7924799695611]}, "2": {"fourier": [48.314081188729695, 48.67789953650239, 195.50357088446617]}, "3": {"fourier": [42.438043375243176, 42.69057859602631, 146.90750743448734]}, "4": {"fourier": [36.96955607078522, 38.08518767776917, 155.6021272316575]}, "5": {"fourier": [27.680464734558694, 27.76824797272159, 144.49743665754795]}, "6": {"fourier": [88.88117593839209, 90.67451224727684, 240.4557935744524]}, "7": {"fourier": [60.07128656388412, 60.891389883063695, 174.92815017700195]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [82.61291190927979, 82.99913289307696, 408.0759893208742]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 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0.507338, -0.516563, -0.466888, 0.537194], [-0.40626, 0.085595, 0.026109, 0.102987, 0.333405, -0.426527, -0.433712, 0.603357]], "network.8.bias": [0.31101, -0.160468, 0.283581, 0.223941, 0.149017, -0.198597, 0.236432, 0.140071], "network.10.weight": [[0.270746, -0.123024, -0.374353, 0.231973, -0.172803, 0.352092, -0.548568, -0.55429]], "network.10.bias": [0.158551]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7026453018188477, "train_acc": 0.445, "val_loss": 0.6509823799133301, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6007198393344879, "train_acc": 0.575, "val_loss": 0.39959633350372314, "val_acc": 0.8}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.4010734409093857, "train_acc": 0.785, "val_loss": 0.12947005033493042, "val_acc": 0.98}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.32154275476932526, "train_acc": 0.91, "val_loss": 0.10970264673233032, "val_acc": 0.98}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.32425881922245026, "train_acc": 0.91, "val_loss": 0.14544883370399475, "val_acc": 0.98}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.27558185160160065, "train_acc": 0.9, "val_loss": 0.19401352107524872, "val_acc": 0.98}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2897745668888092, "train_acc": 0.92, "val_loss": 0.189613938331604, "val_acc": 0.98}], "summary": {"total_epochs": 7, "degraded_epochs": 2, "improved_epochs": 5, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6509823799133301, "final_val_loss": 0.39959633350372314, "initial_val_acc": 0.54, "final_val_acc": 0.8, "best_val_acc": 0.8}, "improved_stage": {"initial_val_loss": 0.12947005033493042, "final_val_loss": 0.189613938331604, "initial_val_acc": 0.98, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 2}, "improvement": 0.17999999999999994, "first_improvement_epoch": 1}} |
69 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.5, "improved_accuracy": 0.84, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2617, "learning_rate": 0.03671955834795707, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[45.313152, 46.551446, 305.088340], [30.371625, 31.107174, 208.275920], [24.161045, 29.535144, 42.150080], [22.812477, 25.039548, 59.102051], [35.168359, 37.293712, 184.744237], [23.916017, 24.965609, 99.967955], [27.393668, 28.998551, 210.379587]]
### 2
fourier: [[20.062945, 22.017113, 24.172365], [4.270999, 5.987343, 51.197678], [16.303854, 17.744975, 142.638189], [18.942955, 20.953689, 66.051243], [6.062526, 6.949074, 10.593602], [18.458748, 23.535359, 47.432738], [10.208748, 13.310338, 89.584888]]
### 4
fourier: [[9.412886, 10.763980, 33.829875], [14.722164, 15.787936, 58.821153], [13.262992, 14.865261, 15.704700], [13.428840, 14.363183, 110.715531], [15.277035, 17.293243, 39.463317], [10.158004, 11.906296, 58.372527], [21.717249, 23.645599, 24.634551]]
### 6
fourier: [[23.484321, 24.544091, 71.427895], [12.555848, 12.667808, 13.307587], [20.663062, 20.791892, 22.245521], [40.023145, 40.296912, 107.905630], [10.450540, 13.045201, 14.902327], [22.196307, 23.806115, 25.742944], [13.602970, 13.781140, 36.202887]]
### 8
fourier: [[40.613265, 41.559627, 103.332657], [41.106945, 41.243509, 117.405387], [6.072667, 6.819168, 74.670682], [35.704094, 37.156895, 122.267318], [38.735066, 38.829243, 130.041879], [37.399360, 38.363672, 125.340017], [21.441940, 23.210376, 71.275670]]
### 10
fourier: [[8.109200, 8.266805, 9.404786], [85.084962, 85.850042, 288.456148], [76.266997, 76.742817, 225.760832], [72.475369, 75.095143, 243.392706], [73.783437, 75.174148, 237.658002], [79.401685, 80.083842, 283.157386], [86.472344, 87.542396, 255.542090]]
### 12
fourier: [[162.282718, 164.602785, 523.794591]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.047274,
0.338621,
0.877391,
0.56186,
-0.528108
],
[
-0.129648,
0.119114,
0.727333,
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0.46541,
-0.398737,
-0.150998
],
[
-0.349933,
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0.044799,
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0.213848,
0.386122
],
[
-0.080188,
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-0.136296,
0.115967,
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-0.086073,
0.073485
]
],
"network.6.bias": [
0.286246,
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-0.014908,
-0.037292,
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-0.027632
],
"network.8.weight": [
[
0.55868,
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[
0.749669,
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[
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[
0.322794,
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[
0.644605,
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]
],
"network.8.bias": [
-0.068491,
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0.429169,
0.272121,
0.48003,
0.3915
],
"network.10.weight": [
[
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],
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"network.12.weight": [
[
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"network.12.bias": [
0.211205
]
}
## Activation Signature
### 0
fourier: [[45.313152, 46.551446, 305.088340], [30.371625, 31.107174, 208.275920], [24.161045, 29.535144, 42.150080], [22.812477, 25.039548, 59.102051], [35.168359, 37.293712, 184.744237], [23.916017, 24.965609, 99.967955], [27.393668, 28.998551, 210.379587]]
### 2
fourier: [[20.062945, 22.017113, 24.172365], [4.270999, 5.987343, 51.197678], [16.303854, 17.744975, 142.638189], [18.942955, 20.953689, 66.051243], [6.062526, 6.949074, 10.593602], [18.458748, 23.535359, 47.432738], [10.208748, 13.310338, 89.584888]]
### 4
fourier: [[9.412886, 10.763980, 33.829875], [14.722164, 15.787936, 58.821153], [13.262992, 14.865261, 15.704700], [13.428840, 14.363183, 110.715531], [15.277035, 17.293243, 39.463317], [10.158004, 11.906296, 58.372527], [21.717249, 23.645599, 24.634551]]
### 6
fourier: [[23.484321, 24.544091, 71.427895], [12.555848, 12.667808, 13.307587], [20.663062, 20.791892, 22.245521], [40.023145, 40.296912, 107.905630], [10.450540, 13.045201, 14.902327], [22.196307, 23.806115, 25.742944], [13.602970, 13.781140, 36.202887]]
### 8
fourier: [[40.613265, 41.559627, 103.332657], [41.106945, 41.243509, 117.405387], [6.072667, 6.819168, 74.670682], [35.704094, 37.156895, 122.267318], [38.735066, 38.829243, 130.041879], [37.399360, 38.363672, 125.340017], [21.441940, 23.210376, 71.275670]]
### 10
fourier: [[8.109200, 8.266805, 9.404786], [85.084962, 85.850042, 288.456148], [76.266997, 76.742817, 225.760832], [72.475369, 75.095143, 243.392706], [73.783437, 75.174148, 237.658002], [79.401685, 80.083842, 283.157386], [86.472344, 87.542396, 255.542090]]
### 12
fourier: [[162.282718, 164.602785, 523.794591]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [45.313151570373876, 46.551446243813345, 305.08834048360586]}, "1": {"fourier": [30.371625332326026, 31.10717376298084, 208.27592015266418]}, "2": {"fourier": [24.161044647650805, 29.5351443109603, 42.15008017420769]}, "3": {"fourier": [22.81247735590711, 25.039547618132573, 59.10205055773258]}, "4": {"fourier": [35.16835887416202, 37.29371200804077, 184.744236856699]}, "5": {"fourier": [23.916017251852445, 24.965608556968427, 99.96795509755611]}, "6": {"fourier": [27.393667647704326, 28.998551179213734, 210.37958708405495]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [20.06294518787139, 22.017112683591254, 24.172365328921853]}, "1": {"fourier": [4.270998778263406, 5.987343362333249, 51.19767755270004]}, "2": {"fourier": [16.30385363365627, 17.74497472952672, 142.63818895816803]}, "3": {"fourier": [18.942955407271267, 20.953689202470848, 66.05124309659004]}, "4": {"fourier": [6.062525692917798, 6.949073652172792, 10.59360196441412]}, "5": {"fourier": [18.45874840203306, 23.535358585498155, 47.432738214731216]}, "6": {"fourier": [10.20874822549045, 13.310337530907388, 89.58488754928112]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [9.412886391881205, 10.76397974902981, 33.82987521588802]}, "1": {"fourier": [14.72216444833451, 15.787935882870778, 58.8211532831192]}, "2": {"fourier": [13.262992491243459, 14.865260947495699, 15.704699697603049]}, "3": {"fourier": [13.428839508206705, 14.363182650847701, 110.71553111076355]}, "4": {"fourier": [15.27703459187803, 17.293242691704414, 39.4633165076375]}, "5": {"fourier": [10.158004053710535, 11.906296165296089, 58.37252661585808]}, "6": {"fourier": [21.717249188510525, 23.64559894226053, 24.634551057520394]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [23.48432130404274, 24.54409098410272, 71.42789508402348]}, "1": {"fourier": [12.55584788648786, 12.66780773550272, 13.3075870730785]}, "2": {"fourier": [20.663061988531357, 20.791891508735716, 22.24552131878148]}, "3": {"fourier": [40.023144522243335, 40.296911860232484, 107.90562992170453]}, "4": {"fourier": [10.450540257018558, 13.045201394498523, 14.902326546609402]}, "5": {"fourier": [22.19630733036845, 23.806114974409656, 25.742943542686515]}, "6": {"fourier": [13.602970484250742, 13.781139725874402, 36.20288720354438]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [40.61326462304108, 41.55962717016133, 103.3326565399766]}, "1": {"fourier": [41.10694535070858, 41.24350904852862, 117.4053870588541]}, "2": {"fourier": [6.072667066750093, 6.819168239415306, 74.6706817150116]}, "3": {"fourier": [35.70409400885833, 37.1568952582733, 122.26731798052788]}, "4": {"fourier": [38.73506630313098, 38.82924348007219, 130.04187887907028]}, "5": {"fourier": [37.39935994949825, 38.36367238639825, 125.34001734852791]}, "6": {"fourier": [21.441939950681178, 23.210376347493725, 71.27566999197006]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [8.109199740449096, 8.26680497132527, 9.404786313515304]}, "1": {"fourier": [85.08496228567036, 85.85004223532466, 288.4561477880925]}, "2": {"fourier": [76.26699730034917, 76.74281730150506, 225.7608315050602]}, "3": {"fourier": [72.4753687440242, 75.09514277927931, 243.39270631223917]}, "4": {"fourier": [73.78343681675481, 75.17414784954346, 237.65800231695175]}, "5": {"fourier": [79.40168489492815, 80.08384226377122, 283.15738639235497]}, "6": {"fourier": [86.47234410925076, 87.5423958981597, 255.54208961129189]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [162.2827176484544, 164.6027849068051, 523.794591203332]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.395026, -0.533877, -0.598731, -0.112439, -0.305392], [-0.101241, 0.033225, -0.245386, -0.597043, -0.472906], [0.617933, 0.017807, -0.091929, -0.215862, 0.112551], [-0.217787, 0.268309, 0.160517, 0.338784, -0.565324], [-0.256847, -0.154399, 0.358476, 0.644218, 0.712221], [0.445338, -0.174951, 0.328589, 0.192103, -0.513816], [-0.42142, -0.240208, -0.425937, -0.104801, 0.05539]], "network.0.bias": [-0.056989, 0.127431, 0.183024, 0.07422, -0.355018, 0.410723, -0.329246], "network.2.weight": [[0.131313, 0.198455, -0.102075, -0.195599, 0.470173, -0.61088, -0.025775], [0.03606, 0.117878, -0.208191, -0.131983, -0.086445, 0.003231, 0.037092], [-0.177119, -0.267304, -0.09625, 0.034462, -0.456936, -0.252888, -0.215133], [0.445241, -0.043392, -0.533653, 0.510985, 0.145261, 0.058019, 0.241083], [0.183201, -0.169588, -0.30384, 0.044343, 0.028341, 0.267811, -0.026371], [0.00042, -0.051496, 0.599945, -0.414247, -0.043353, 0.157768, -0.490311], [-0.073583, -0.056438, -0.279147, 0.346391, 0.038071, 0.356964, 0.100019]], "network.2.bias": [-0.156894, -0.142116, -0.325833, 0.289774, -0.103305, 0.377114, 0.386006], "network.4.weight": [[0.497778, 0.165123, 0.063564, 0.181038, 0.152309, 0.133027, -0.28502], [0.633274, -0.185229, -0.248022, -0.187583, 0.210563, 0.342378, -0.134064], [0.232543, -0.235971, 0.034885, -0.137027, -0.310433, 0.551189, -0.058157], [0.604888, -0.385025, -0.413583, 0.057764, -0.593143, 0.465885, 0.19343], [0.616024, -0.061308, -0.091877, -0.214035, -0.164138, 0.445047, 0.0245], [0.485336, -0.391611, -0.091335, 0.140388, -0.46735, 0.093616, -0.212639], [-0.696343, -0.35016, -0.214124, 0.403451, -0.136233, -0.517265, 0.4162]], "network.4.bias": [0.260953, 0.44392, -0.066047, 0.527735, 0.128835, 0.503611, -0.03375], "network.6.weight": [[0.289986, 0.334785, 0.395475, 0.106946, 0.110868, 0.404773, -0.555772], [-0.303638, -0.363338, -0.044851, -0.090388, -0.129867, 0.131602, 0.262525], [-0.02614, -0.503948, -0.224718, 0.262452, -0.566828, -0.246005, 0.506328], [0.568212, 0.410823, 0.047274, 0.338621, 0.877391, 0.56186, -0.528108], [-0.129648, 0.119114, 0.727333, -0.100692, 0.46541, -0.398737, -0.150998], [-0.349933, -0.568402, -0.209873, 0.044799, -0.74308, 0.213848, 0.386122], [-0.080188, -0.481066, -0.136296, 0.115967, -0.352397, -0.086073, 0.073485]], "network.6.bias": [0.286246, 0.142366, -0.014908, -0.037292, 0.1458, 0.293228, -0.027632], "network.8.weight": [[0.55868, -0.404137, -0.048197, 0.709249, -0.147986, -0.372519, 0.123538], [0.749669, 0.295335, -0.267476, 0.541315, 0.424471, -0.234628, -0.10772], [0.04747, 0.211898, 0.211643, 0.257999, -0.29869, 0.36211, 0.0922], [0.322794, -0.244389, -0.316989, 0.598385, 0.231232, -0.381316, -0.409441], [0.644605, -0.224361, -0.343638, 0.561085, -0.017229, -0.099799, -0.583152], [0.574196, -0.147483, -0.285917, 0.528564, -0.095868, -0.660185, -0.191909], [0.447612, 0.403449, -0.436234, 0.145075, 0.230221, -0.586256, -0.242039]], "network.8.bias": [-0.068491, -0.008999, 0.374432, 0.429169, 0.272121, 0.48003, 0.3915], "network.10.weight": [[-0.113735, -0.163263, 0.579458, -0.011203, 0.028522, -0.173711, 0.264192], [0.355193, 0.415818, -0.232108, 0.58485, 0.445215, 0.189834, 0.655536], [0.081151, -0.55896, 0.406961, -0.27869, -0.557204, -0.461717, -0.630588], [0.779298, 0.250114, 0.042417, 0.0, 0.088092, 0.650282, 0.38507], [0.75041, 0.176026, -0.266098, 0.33157, 0.120838, 0.490053, 0.337497], [0.07538, 0.316377, -0.084711, 0.625621, 0.269945, 0.592772, 0.602298], [-0.406433, -0.568018, 0.291882, -0.405543, -0.351173, -0.459427, -0.351529]], "network.10.bias": [-0.027873, 0.034557, 0.298586, -0.065713, -0.021995, 0.023859, 0.320205], "network.12.weight": [[0.088968, -0.640573, 0.389488, -0.360883, -0.495813, -0.553304, 0.445977]], "network.12.bias": [0.211205]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6927118003368378, "train_acc": 0.525, "val_loss": 0.6982707381248474, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6778532862663269, "train_acc": 0.565, "val_loss": 0.7106364369392395, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6836257874965668, "train_acc": 0.565, "val_loss": 0.6850740313529968, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6400130987167358, "train_acc": 0.565, "val_loss": 0.6275554895401001, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5812472701072693, "train_acc": 0.5, "val_loss": 0.5351824164390564, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.4550689607858658, "train_acc": 0.84, "val_loss": 0.5678970217704773, "val_acc": 0.7}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.4386045038700104, "train_acc": 0.82, "val_loss": 0.48698940873146057, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.3594563603401184, "train_acc": 0.84, "val_loss": 0.44397199153900146, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.32431724667549133, "train_acc": 0.865, "val_loss": 0.4640748202800751, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.30935508012771606, "train_acc": 0.88, "val_loss": 0.49357277154922485, "val_acc": 0.8}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.31850337237119675, "train_acc": 0.89, "val_loss": 0.5104538202285767, "val_acc": 0.78}], "summary": {"total_epochs": 11, "degraded_epochs": 4, "improved_epochs": 7, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6982707381248474, "final_val_loss": 0.6275554895401001, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5351824164390564, "final_val_loss": 0.5104538202285767, "initial_val_acc": 0.78, "final_val_acc": 0.78, "best_val_acc": 0.84, "best_epoch": 7}, "improvement": 0.33999999999999997, "first_improvement_epoch": 3}} |
70 | {"target_pattern": "ends_with", "degraded_accuracy": 0.82, "improved_accuracy": 1.0, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7357, "learning_rate": 0.03138819499583542, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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1.03754
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],
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0.41021,
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"network.2.weight": [
[
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],
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[
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[
0.01932,
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0.529102
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[
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[
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],
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0.603746,
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0.07088,
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[
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0.168744
],
[
0.374076,
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],
[
0.118529,
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[
0.60289,
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],
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],
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[
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0.030572,
0.386384,
0.655642,
0.152929
]
],
"network.8.bias": [
-0.888935
]
}
## Activation Signature
### 0
fourier: [[29.984188, 35.202399, 277.402181], [21.429000, 29.878600, 176.528196], [42.604359, 47.122570, 190.064868], [40.642507, 44.070129, 44.585406], [35.825104, 35.947285, 102.395521], [51.914993, 54.763719, 142.073166]]
### 2
fourier: [[17.766112, 18.960134, 88.529771], [10.483161, 14.003773, 127.124810], [22.229934, 22.995808, 95.311575], [55.549599, 68.347239, 271.040680], [51.785008, 61.665599, 243.350098], [49.276322, 66.615490, 86.158632]]
### 4
fourier: [[62.257101, 75.652301, 204.168377], [82.654076, 100.880957, 268.215305], [36.747489, 44.788367, 236.067716], [22.519533, 26.824582, 76.941683], [27.067009, 32.259965, 88.651000], [4.269162, 5.232095, 28.816316]]
### 6
fourier: [[4.051596, 4.206197, 7.664079], [6.173797, 6.825264, 7.504486], [3.229331, 3.753455, 4.799993], [8.496607, 9.423144, 10.270313], [11.034909, 11.887300, 12.953429], [4.560215, 4.923384, 35.989661]]
### 8
fourier: [[16.078564, 17.583313, 56.022085]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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0.031518,
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],
[
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0.316544,
-1.04352
],
[
-1.196583,
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0.314045,
0.007146,
0.307248
],
[
-0.718553,
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],
[
0.671921,
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1.03754
]
],
"network.0.bias": [
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0.292635,
0.421709,
0.41021,
-0.060762
],
"network.2.weight": [
[
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],
[
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],
[
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],
[
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0.725533
],
[
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0.939066
],
[
0.042316,
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]
],
"network.2.bias": [
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0.300168,
0.557471
],
"network.4.weight": [
[
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0.519501
],
[
0.001494,
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0.818765
],
[
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[
0.01932,
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],
[
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],
[
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]
],
"network.4.bias": [
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0.07088,
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],
"network.6.weight": [
[
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0.168744
],
[
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],
[
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[
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[
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]
],
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],
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[
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0.030572,
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]
],
"network.8.bias": [
-0.888935
]
}
## Activation Signature
### 0
fourier: [[29.984188, 35.202399, 277.402181], [21.429000, 29.878600, 176.528196], [42.604359, 47.122570, 190.064868], [40.642507, 44.070129, 44.585406], [35.825104, 35.947285, 102.395521], [51.914993, 54.763719, 142.073166]]
### 2
fourier: [[17.766112, 18.960134, 88.529771], [10.483161, 14.003773, 127.124810], [22.229934, 22.995808, 95.311575], [55.549599, 68.347239, 271.040680], [51.785008, 61.665599, 243.350098], [49.276322, 66.615490, 86.158632]]
### 4
fourier: [[62.257101, 75.652301, 204.168377], [82.654076, 100.880957, 268.215305], [36.747489, 44.788367, 236.067716], [22.519533, 26.824582, 76.941683], [27.067009, 32.259965, 88.651000], [4.269162, 5.232095, 28.816316]]
### 6
fourier: [[4.051596, 4.206197, 7.664079], [6.173797, 6.825264, 7.504486], [3.229331, 3.753455, 4.799993], [8.496607, 9.423144, 10.270313], [11.034909, 11.887300, 12.953429], [4.560215, 4.923384, 35.989661]]
### 8
fourier: [[16.078564, 17.583313, 56.022085]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [29.98418769491744, 35.20239873284271, 277.40218141674995]}, "1": {"fourier": [21.428999961418757, 29.878600245829432, 176.52819642424583]}, "2": {"fourier": [42.60435945957828, 47.12257022780592, 190.06486770510674]}, "3": {"fourier": [40.642507375427634, 44.070129265458554, 44.58540582930052]}, "4": {"fourier": [35.82510417702343, 35.9472848774073, 102.39552140235901]}, "5": {"fourier": [51.91499257958118, 54.76371942163503, 142.07316622510552]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [17.76611218681759, 18.960133711580973, 88.52977131307125]}, "1": {"fourier": [10.483161224936623, 14.003773237705671, 127.12480998039246]}, "2": {"fourier": [22.22993427361203, 22.995807701368314, 95.31157486140728]}, "3": {"fourier": [55.5495990181316, 68.34723932348626, 271.04067981243134]}, "4": {"fourier": [51.78500813767535, 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[3.2293314153727763, 3.7534551731570818, 4.799993176013231]}, "3": {"fourier": [8.496606521502596, 9.423143955087836, 10.270312518269357]}, "4": {"fourier": [11.03490927528764, 11.887300385926416, 12.953428599983454]}, "5": {"fourier": [4.560215112508516, 4.923384319985142, 35.98966073989868]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [16.07856436281344, 17.583312799444755, 56.02208495140076]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.11614, -0.250507, -0.445288, -0.3068, -0.435114], [-0.00562, -0.32427, -0.511648, 0.031518, -0.134372], [0.357575, 0.535011, 0.482316, 0.316544, -1.04352], [-1.196583, 0.024793, 0.314045, 0.007146, 0.307248], [-0.718553, 0.196006, -0.061475, 0.082622, 0.985773], [0.671921, -0.049561, -0.103062, -0.079672, 1.03754]], "network.0.bias": [-0.356526, -0.196628, 0.292635, 0.421709, 0.41021, -0.060762], "network.2.weight": [[0.23847, -0.024458, -0.004632, 0.089338, 0.023578, -0.38155], [0.194648, -0.159658, -0.234014, -0.391294, -0.019993, -0.172686], [-0.161436, 0.261408, -0.058864, 0.117668, -0.050035, -0.447973], [0.259314, 0.034992, 0.017135, 0.168227, 0.949924, 0.725533], [-0.118303, -0.261252, -0.080204, 0.560956, 0.297878, 0.939066], [0.042316, -0.376331, 0.402302, -0.362026, -0.614069, -0.714582]], "network.2.bias": [-0.410269, -0.167197, -0.156062, 0.155342, 0.300168, 0.557471], "network.4.weight": [[-0.219986, -0.154446, -0.182919, -0.555969, -0.542276, 0.519501], [0.001494, -0.331205, 0.24814, -0.941532, -0.484614, 0.818765], [-0.067091, 0.137053, 0.392992, -0.326614, -0.406834, -0.323004], [0.01932, -0.067429, -0.391613, -0.074616, -0.282645, 0.529102], [0.259457, -0.331328, 0.081469, -0.064395, -0.397535, 0.412282], [-0.022813, 0.230785, 0.014292, -0.056019, -0.032162, -0.071457]], "network.4.bias": [0.603746, 0.742792, -0.372501, -0.13922, 0.07088, -0.027609], "network.6.weight": [[-0.232866, -0.149108, -0.398497, -0.214126, -0.321458, 0.168744], [0.374076, 0.646724, 0.027469, 0.182133, 0.037494, -0.284849], [0.118529, 0.530948, -0.082874, 0.03022, -0.258593, 0.1788], [0.60289, 0.788958, 0.38192, 0.275844, 0.096842, 0.28223], [0.959208, 0.694134, -0.194442, 0.1347, 0.397962, 0.067102], [-0.376759, -0.286857, -0.325317, 0.005486, -0.260424, 0.221519]], "network.6.bias": [-0.01552, -0.083141, -0.011335, -0.1272, -0.054133, -0.318165], "network.8.weight": [[-0.029332, 0.829354, 0.030572, 0.386384, 0.655642, 0.152929]], "network.8.bias": [-0.888935]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6865295767784119, "train_acc": 0.555, "val_loss": 0.6825147271156311, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6877035200595856, "train_acc": 0.555, "val_loss": 0.6755610704421997, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6746537685394287, "train_acc": 0.555, "val_loss": 0.6557636857032776, "val_acc": 0.64}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6587428450584412, "train_acc": 0.645, "val_loss": 0.6124327778816223, "val_acc": 0.82}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6208654344081879, "train_acc": 0.805, "val_loss": 0.5596684217453003, "val_acc": 0.8}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5668948292732239, "train_acc": 0.82, "val_loss": 0.4834449887275696, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5225202590227127, "train_acc": 0.865, "val_loss": 0.4509735405445099, "val_acc": 0.96}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.5083152055740356, "train_acc": 0.885, "val_loss": 0.4237402379512787, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.4658803194761276, "train_acc": 0.885, "val_loss": 0.3925163745880127, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.4249694496393204, "train_acc": 0.88, "val_loss": 0.3729674518108368, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.40324412286281586, "train_acc": 0.895, "val_loss": 0.34653517603874207, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.3587416410446167, "train_acc": 0.92, "val_loss": 0.3154895305633545, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.2985137850046158, "train_acc": 0.955, "val_loss": 0.26569443941116333, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.23254188895225525, "train_acc": 0.965, "val_loss": 0.2312346249818802, "val_acc": 1.0}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6825147271156311, "final_val_loss": 0.6124327778816223, "initial_val_acc": 0.56, "final_val_acc": 0.82, "best_val_acc": 0.82}, "improved_stage": {"initial_val_loss": 0.5596684217453003, "final_val_loss": 0.2312346249818802, "initial_val_acc": 0.8, "final_val_acc": 1.0, "best_val_acc": 1.0, "best_epoch": 13}, "improvement": 0.18000000000000005, "first_improvement_epoch": 3}} |
71 | {"target_pattern": "palindrome", "degraded_accuracy": 0.42, "improved_accuracy": 0.82, "improvement": 0.39999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4610, "learning_rate": 0.08295789265197352, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.90812
],
[
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[
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[
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1.023644
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[
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"network.0.bias": [
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[
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[
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[
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[
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[
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[
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[
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[
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[
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],
"network.10.bias": [
0.67527
]
}
## Activation Signature
### 0
fourier: [[29.270967, 30.176222, 37.915394], [62.887479, 76.113182, 520.714313], [47.676963, 55.927708, 61.296244], [56.012764, 64.014616, 205.803061], [51.270060, 55.556520, 488.834567]]
### 2
fourier: [[57.267289, 60.819327, 280.491219], [15.777484, 20.579397, 170.088063], [43.101721, 58.489161, 63.880948], [59.106628, 73.053995, 105.393786], [14.735599, 17.246176, 73.628996]]
### 4
fourier: [[19.219783, 20.439260, 21.779181], [32.001325, 38.152547, 159.352659], [67.194076, 74.611678, 169.035958], [49.058373, 53.380149, 130.987085], [24.889134, 29.947204, 129.693963]]
### 6
fourier: [[41.465951, 43.477163, 95.104145], [74.430264, 80.213328, 193.905353], [81.434964, 88.551561, 203.725759], [89.545656, 97.387264, 239.616350], [26.346223, 26.489247, 51.744588]]
### 8
fourier: [[64.364933, 67.153981, 150.341976], [198.939425, 207.328484, 559.234780], [147.168964, 150.934838, 340.293300], [161.337953, 168.638879, 452.460886], [153.912612, 160.476270, 398.921154]]
### 10
fourier: [[139.421511, 146.602877, 310.492108]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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-0.106319,
0.114788,
0.90812
],
[
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-0.288246,
-0.468199
],
[
-0.744309,
0.733991,
0.20973,
0.278578,
-0.975641
],
[
0.918077,
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-0.153022,
0.29926,
1.023644
],
[
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]
],
"network.0.bias": [
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0.437617,
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],
"network.2.weight": [
[
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],
[
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[
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-0.626431,
0.62631,
0.086565
],
[
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0.690466,
0.435217
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[
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]
],
"network.2.bias": [
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0.434721
],
"network.4.weight": [
[
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],
[
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0.005024,
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[
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0.965326,
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[
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[
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],
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0.243695,
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0.340313
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"network.6.weight": [
[
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[
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0.425815,
0.24131
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[
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0.420136
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[
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[
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],
"network.6.bias": [
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],
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[
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0.010245
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[
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0.923752,
0.705235
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[
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[
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[
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],
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0.350348,
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],
"network.10.weight": [
[
0.032604,
-0.355514,
0.437441,
-0.41322,
0.202435
]
],
"network.10.bias": [
0.67527
]
}
## Activation Signature
### 0
fourier: [[29.270967, 30.176222, 37.915394], [62.887479, 76.113182, 520.714313], [47.676963, 55.927708, 61.296244], [56.012764, 64.014616, 205.803061], [51.270060, 55.556520, 488.834567]]
### 2
fourier: [[57.267289, 60.819327, 280.491219], [15.777484, 20.579397, 170.088063], [43.101721, 58.489161, 63.880948], [59.106628, 73.053995, 105.393786], [14.735599, 17.246176, 73.628996]]
### 4
fourier: [[19.219783, 20.439260, 21.779181], [32.001325, 38.152547, 159.352659], [67.194076, 74.611678, 169.035958], [49.058373, 53.380149, 130.987085], [24.889134, 29.947204, 129.693963]]
### 6
fourier: [[41.465951, 43.477163, 95.104145], [74.430264, 80.213328, 193.905353], [81.434964, 88.551561, 203.725759], [89.545656, 97.387264, 239.616350], [26.346223, 26.489247, 51.744588]]
### 8
fourier: [[64.364933, 67.153981, 150.341976], [198.939425, 207.328484, 559.234780], [147.168964, 150.934838, 340.293300], [161.337953, 168.638879, 452.460886], [153.912612, 160.476270, 398.921154]]
### 10
fourier: [[139.421511, 146.602877, 310.492108]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [29.270967121924773, 30.176221740620036, 37.915394202424665]}, "1": {"fourier": [62.887478947696984, 76.11318191955496, 520.714312851429]}, "2": {"fourier": [47.67696262545665, 55.92770815506287, 61.296243876218796]}, "3": {"fourier": [56.0127641060202, 64.01461570880876, 205.80306120216846]}, "4": {"fourier": [51.270060066844835, 55.55652007844599, 488.83456712961197]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [57.267288562557816, 60.81932733645789, 280.4912186264992]}, "1": {"fourier": [15.777484056489884, 20.57939699610123, 170.08806267380714]}, "2": {"fourier": [43.10172120510088, 58.48916108624434, 63.88094848394394]}, "3": {"fourier": [59.106628282684056, 73.05399536536045, 105.39378550648689]}, "4": {"fourier": [14.735598880031008, 17.246175810996817, 73.62899641692638]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [19.21978282306423, 20.439260052700266, 21.779180511832237]}, "1": {"fourier": [32.00132462147831, 38.15254660592066, 159.35265883803368]}, "2": {"fourier": [67.1940757225578, 74.61167776414887, 169.03595800697803]}, "3": {"fourier": [49.058372644098625, 53.38014940100285, 130.98708476126194]}, "4": {"fourier": [24.88913363203859, 29.947203646892383, 129.69396342337132]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [41.46595131796511, 43.47716304785968, 95.10414547473192]}, "1": {"fourier": [74.43026449540655, 80.21332834274638, 193.90535268187523]}, "2": {"fourier": [81.43496358931677, 88.55156050843108, 203.7257587760687]}, "3": {"fourier": [89.54565640344548, 97.38726363410406, 239.61634966731071]}, "4": {"fourier": [26.346223081937893, 26.489247112956882, 51.74458758533001]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [64.36493319421761, 67.15398077537245, 150.34197598695755]}, "1": {"fourier": [198.93942498711368, 207.32848360339614, 559.2347797304392]}, "2": {"fourier": [147.16896448870548, 150.93483837975504, 340.2933003306389]}, "3": {"fourier": [161.33795277978325, 168.6388793034295, 452.46088632941246]}, "4": {"fourier": [153.91261179076275, 160.4762697973832, 398.92115384340286]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [139.421511039862, 146.6028766056458, 310.4921079277992]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.059196, -0.300321, -0.106319, 0.114788, 0.90812], [-0.855204, -0.825981, -0.682427, -0.288246, -0.468199], [-0.744309, 0.733991, 0.20973, 0.278578, -0.975641], [0.918077, -0.083888, -0.153022, 0.29926, 1.023644], [-0.167951, -0.367539, -0.80576, -0.735141, -0.389486]], "network.0.bias": [-0.400352, -0.595252, 0.437617, -0.287528, -0.812774], "network.2.weight": [[-0.836118, 0.73499, -0.189806, -0.642645, -0.212448], [0.087028, 0.209724, -0.497604, -0.428685, 0.337259], [-0.021033, -0.253822, -0.626431, 0.62631, 0.086565], [0.357429, 0.223353, -0.685349, 0.690466, 0.435217], [-0.144116, -0.364323, -0.406796, -0.274632, -0.768649]], "network.2.bias": [-0.791486, -0.275429, 0.101418, 0.255029, 0.434721], "network.4.weight": [[-0.849429, 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72 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.48, "improved_accuracy": 0.94, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8556, "learning_rate": 0.048065341110050036, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[32.461830, 33.898319, 119.569148], [21.841829, 22.067808, 22.344214], [24.254004, 24.602516, 32.725673], [15.926315, 16.098659, 130.290652], [22.868334, 24.299423, 152.739434], [31.956926, 36.673599, 107.571327], [32.994535, 34.595082, 35.971393]]
### 2
fourier: [[34.926562, 40.300071, 175.516734], [26.100157, 26.401928, 153.346624], [28.165179, 34.830436, 40.606479], [20.727359, 24.902026, 55.633041], [15.863951, 16.717289, 48.058019], [11.789437, 19.239002, 23.297652], [7.673154, 8.410774, 27.559001]]
### 4
fourier: [[29.419146, 34.829007, 136.574923], [35.396511, 47.254135, 183.423771], [71.655926, 87.485491, 378.903569], [14.470563, 15.422466, 38.474336], [15.956918, 21.025711, 112.133587], [15.017992, 17.044124, 113.154449], [6.554746, 7.996219, 57.309506]]
### 6
fourier: [[59.554414, 74.463590, 313.326213], [86.657089, 108.264085, 446.027125], [69.172803, 85.281144, 356.911374], [44.437055, 55.041966, 254.076158], [86.456252, 108.146928, 445.314754], [9.251782, 10.180195, 76.940537], [38.363687, 48.242117, 78.925737]]
### 8
fourier: [[253.010183, 315.814236, 1306.820360], [87.587103, 108.774641, 346.632007], [26.064641, 31.567596, 91.258471], [18.164899, 22.358215, 136.124288], [9.370279, 11.631631, 43.322808], [69.517970, 86.187337, 242.667645], [38.231875, 47.260750, 131.182657]]
### 10
fourier: [[171.071842, 212.971335, 788.629341]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
0.294023,
-0.177742,
0.001687,
-0.324785,
-0.101894,
-0.067901,
-0.352442
],
[
0.31203,
-0.321155,
0.172293,
-0.169734,
-0.03102,
0.309479,
0.199907
],
[
-0.156157,
-0.260257,
-0.029335,
-0.295325,
-0.189576,
0.098666,
0.740547
],
[
0.149481,
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-0.200788,
0.015237,
-0.051506,
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]
],
"network.8.bias": [
0.235776,
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0.12492,
-0.070372,
-0.118638,
0.709372,
0.406385
],
"network.10.weight": [
[
-0.642085,
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-0.076658,
-0.146602,
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]
],
"network.10.bias": [
0.15838
]
}
## Activation Signature
### 0
fourier: [[32.461830, 33.898319, 119.569148], [21.841829, 22.067808, 22.344214], [24.254004, 24.602516, 32.725673], [15.926315, 16.098659, 130.290652], [22.868334, 24.299423, 152.739434], [31.956926, 36.673599, 107.571327], [32.994535, 34.595082, 35.971393]]
### 2
fourier: [[34.926562, 40.300071, 175.516734], [26.100157, 26.401928, 153.346624], [28.165179, 34.830436, 40.606479], [20.727359, 24.902026, 55.633041], [15.863951, 16.717289, 48.058019], [11.789437, 19.239002, 23.297652], [7.673154, 8.410774, 27.559001]]
### 4
fourier: [[29.419146, 34.829007, 136.574923], [35.396511, 47.254135, 183.423771], [71.655926, 87.485491, 378.903569], [14.470563, 15.422466, 38.474336], [15.956918, 21.025711, 112.133587], [15.017992, 17.044124, 113.154449], [6.554746, 7.996219, 57.309506]]
### 6
fourier: [[59.554414, 74.463590, 313.326213], [86.657089, 108.264085, 446.027125], [69.172803, 85.281144, 356.911374], [44.437055, 55.041966, 254.076158], [86.456252, 108.146928, 445.314754], [9.251782, 10.180195, 76.940537], [38.363687, 48.242117, 78.925737]]
### 8
fourier: [[253.010183, 315.814236, 1306.820360], [87.587103, 108.774641, 346.632007], [26.064641, 31.567596, 91.258471], [18.164899, 22.358215, 136.124288], [9.370279, 11.631631, 43.322808], [69.517970, 86.187337, 242.667645], [38.231875, 47.260750, 131.182657]]
### 10
fourier: [[171.071842, 212.971335, 788.629341]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [32.46182989954913, 33.89831904371197, 119.56914767622948]}, "1": {"fourier": [21.841828974016952, 22.0678083528338, 22.344213794745567]}, "2": {"fourier": [24.254004009907785, 24.602516458423473, 32.72567258357833]}, "3": {"fourier": [15.926314917919727, 16.098659447990805, 130.2906522154808]}, "4": {"fourier": [22.868334016478368, 24.299423495216068, 152.73943397402763]}, "5": {"fourier": [31.956926053669804, 36.67359924097839, 107.57132688164711]}, "6": {"fourier": [32.994534589994146, 34.59508248482384, 35.971393048763275]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [34.92656211410602, 40.30007141612879, 175.5167336165905]}, "1": {"fourier": [26.100156819587273, 26.401927962783876, 153.34662436693907]}, "2": {"fourier": [28.165178848807777, 34.83043557604718, 40.606478810310364]}, "3": {"fourier": [20.72735905337925, 24.902025789498644, 55.63304089009762]}, "4": {"fourier": [15.863950847300265, 16.717288929327037, 48.058019280433655]}, "5": {"fourier": [11.789436724326809, 19.23900161439218, 23.29765199124813]}, "6": {"fourier": [7.673153966962285, 8.41077432913738, 27.559000812470913]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [29.419146062652064, 34.82900718117009, 136.57492253184319]}, "1": {"fourier": [35.39651079336941, 47.25413464774423, 183.42377113178372]}, "2": {"fourier": [71.65592648068655, 87.48549118868763, 378.90356881916523]}, "3": {"fourier": [14.470562576649888, 15.422465528082647, 38.47433641552925]}, "4": {"fourier": [15.95691772461507, 21.02571066943159, 112.13358691334724]}, "5": {"fourier": [15.017991953833912, 17.044123629747258, 113.15444919466972]}, "6": {"fourier": [6.55474610931053, 7.996218696354023, 57.30950582027435]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [59.55441399690333, 74.46358993649805, 313.32621347904205]}, "1": {"fourier": [86.6570890214904, 108.26408485317762, 446.02712531387806]}, "2": {"fourier": [69.17280313669656, 85.28114368219389, 356.911374181509]}, "3": {"fourier": [44.437054604964345, 55.04196568428037, 254.07615786790848]}, "4": {"fourier": [86.45625203844837, 108.14692802280766, 445.3147535920143]}, "5": {"fourier": [9.251782115219777, 10.18019503084715, 76.9405372440815]}, "6": {"fourier": [38.363687371292876, 48.24211666424613, 78.92573714256287]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [253.01018285268327, 315.814236098878, 1306.8203595280647]}, "1": {"fourier": [87.58710288330043, 108.7746405846586, 346.63200706243515]}, "2": {"fourier": [26.064641258137723, 31.567596058535614, 91.25847098976374]}, "3": {"fourier": [18.164898569805715, 22.358214685454435, 136.1242879629135]}, "4": {"fourier": [9.370279402247942, 11.631630566555904, 43.322808355093]}, "5": {"fourier": [69.51797000959198, 86.18733653127508, 242.66764542460442]}, "6": {"fourier": [38.23187548667941, 47.26075027510123, 131.1826573163271]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [171.07184155459004, 212.9713348679375, 788.6293412670493]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.810187, 0.002811, 0.502049, 0.285361, 0.329339], [-0.44356, -0.135745, 0.144283, 0.279045, 0.490752], [-0.528231, -0.11428, -0.224626, 0.271065, 0.422009], [-0.037441, -0.420104, -0.136029, 0.04773, -0.014256], [0.284303, 0.297454, 0.336348, 0.073287, -0.243374], [0.724184, -0.081059, 0.058215, 0.168538, 0.221519], [0.384815, -0.51567, 0.090672, -0.359472, 0.5559]], "network.0.bias": [0.264804, -0.60384, 0.029811, -0.436181, 0.241687, -0.314493, -0.043044], "network.2.weight": [[0.838301, 0.300238, 0.506613, 0.267326, 0.145073, -0.566799, 0.381989], [0.859612, 0.024734, 0.442294, 0.090696, 0.084686, -0.11741, 0.333149], [0.118529, 0.574268, 0.788264, -0.274594, -0.426114, -0.311601, 0.832564], [0.39999, 0.237334, 0.390884, 0.034462, 0.109183, -0.365188, 0.180186], [-0.078012, -0.101135, -0.264978, 0.005799, 0.140547, 0.442029, -0.62512], [-0.006927, 0.353484, 0.413932, -0.27567, -0.155801, -0.168892, 0.147878], [-0.229969, 0.345761, -0.210635, 0.277841, -0.047821, 0.104058, -0.447784]], "network.2.bias": [0.457098, -0.068023, 0.2788, -0.16911, 0.347266, 0.276898, 0.130117], "network.4.weight": [[-0.390935, -0.389044, -0.38931, 0.045188, -0.048125, -0.108501, 0.11657], [0.519593, -0.05463, 0.729953, 0.111415, 0.004558, 0.535951, -0.316085], [0.915332, 0.688549, 0.745752, 0.529003, -0.115917, 0.33451, -0.18775], [-0.358497, -0.120144, 0.160615, 0.299353, 0.610642, 0.169839, 0.267637], [-0.250586, 0.075759, -0.496149, 0.167846, -0.095202, -0.329156, -0.151255], [-0.251006, -0.321793, 0.118418, 0.123318, -0.019824, -0.361702, -0.299842], [0.152847, -0.245911, -0.3638, 0.21827, 0.026955, 0.19429, -0.077225]], "network.4.bias": [0.33933, 0.107754, -0.017354, 0.517191, -0.353706, -0.209581, -0.490468], "network.6.weight": [[-0.491858, 0.576439, 0.565284, 0.195536, -0.188628, -0.016038, -0.230086], [-0.408564, 0.710494, 0.862691, 0.006567, -0.025648, 0.425268, 0.018807], [-0.282841, 0.254439, 0.807857, -0.332277, 0.03278, -0.133162, 0.099701], [0.034195, 0.310484, 0.501284, 0.294936, 0.290858, 0.508122, -0.164894], [-0.222601, 0.681137, 0.855935, -0.197023, 0.097236, -0.094213, 0.060988], [0.256662, 0.167335, -0.189854, 0.141592, 0.110742, -0.084359, -0.349721], [0.211792, -0.396382, -0.254331, 0.759394, 0.346464, -0.31809, -0.086616]], "network.6.bias": [-0.179397, -0.147459, 0.196211, -0.095268, 0.031874, -0.472177, 0.609523], "network.8.weight": [[0.80663, 0.849693, 0.632455, 0.339885, 0.803503, -0.212493, -0.645389], [-0.344462, -0.144202, -0.049744, -0.424335, -0.300456, -0.076791, 0.779003], [0.245357, -0.008777, -0.242926, -0.185088, -0.129373, 0.087543, 0.443398], [0.294023, -0.177742, 0.001687, -0.324785, -0.101894, -0.067901, -0.352442], [0.31203, -0.321155, 0.172293, -0.169734, -0.03102, 0.309479, 0.199907], [-0.156157, -0.260257, -0.029335, -0.295325, -0.189576, 0.098666, 0.740547], [0.149481, -0.306944, -0.200788, 0.015237, -0.051506, -0.25606, 0.377882]], "network.8.bias": [0.235776, 0.614922, 0.12492, -0.070372, -0.118638, 0.709372, 0.406385], "network.10.weight": [[-0.642085, 0.523318, 0.270604, -0.076658, -0.146602, 0.48365, 0.355272]], "network.10.bias": [0.15838]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6839723289012909, "train_acc": 0.53, "val_loss": 0.6746223568916321, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6478859484195709, "train_acc": 0.57, "val_loss": 0.5814557671546936, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5586584210395813, "train_acc": 0.625, "val_loss": 0.4332900941371918, "val_acc": 0.9}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4041745811700821, "train_acc": 0.895, "val_loss": 0.27440494298934937, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.24757618457078934, "train_acc": 0.905, "val_loss": 0.2631182074546814, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.20845146477222443, "train_acc": 0.94, "val_loss": 0.26251494884490967, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.1826339066028595, "train_acc": 0.955, "val_loss": 0.22280731797218323, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.1869632825255394, "train_acc": 0.94, "val_loss": 0.20669162273406982, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.16930913925170898, "train_acc": 0.945, "val_loss": 0.19872550666332245, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.1635269969701767, "train_acc": 0.955, "val_loss": 0.20029735565185547, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.1769002452492714, "train_acc": 0.945, "val_loss": 0.19880987703800201, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.1917741298675537, "train_acc": 0.935, "val_loss": 0.20552030205726624, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6746223568916321, "final_val_loss": 0.5814557671546936, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.4332900941371918, "final_val_loss": 0.20552030205726624, "initial_val_acc": 0.9, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 6}, "improvement": 0.45999999999999996, "first_improvement_epoch": 1}} |
73 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.56, "improved_accuracy": 0.94, "improvement": 0.3799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2865, "learning_rate": 0.05576129768179258, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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]
],
"network.10.bias": [
0.066245
]
}
## Activation Signature
### 0
fourier: [[29.629656, 30.112302, 223.453039], [33.400906, 36.975552, 138.205456], [31.717633, 32.571850, 258.462920], [53.880222, 58.355118, 337.374017], [27.181931, 29.316968, 81.448187], [30.291958, 31.221684, 168.774267]]
### 2
fourier: [[32.013618, 38.401689, 173.156382], [17.571954, 19.120095, 105.941930], [27.416055, 27.788726, 161.675804], [22.349185, 25.746041, 108.669973], [44.283544, 49.999798, 151.113531], [33.213243, 37.391732, 261.785295]]
### 4
fourier: [[32.293035, 34.754432, 51.524783], [36.384478, 37.522674, 50.993719], [25.962751, 26.529849, 64.053699], [33.666066, 34.134109, 221.333855], [40.184613, 40.348396, 288.584331], [48.414501, 53.948757, 172.591070]]
### 6
fourier: [[14.680996, 16.778384, 76.542538], [31.446520, 31.557885, 35.764514], [65.780748, 72.931713, 281.965526], [13.450240, 15.745166, 20.486521], [16.994020, 18.764822, 33.499338], [20.555319, 26.603002, 26.890822]]
### 8
fourier: [[16.878482, 20.951384, 77.037845], [36.037198, 36.407925, 110.224591], [33.825484, 35.017797, 81.434977], [38.063095, 43.742731, 44.068409], [11.458981, 12.386953, 12.630622], [49.716797, 50.173107, 128.396728]]
### 10
fourier: [[52.038102, 52.783071, 215.611453]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.029262,
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],
[
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],
[
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],
[
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],
[
0.565398,
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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[
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],
[
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]
],
"network.2.bias": [
0.595737,
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],
"network.4.weight": [
[
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],
[
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],
[
0.613163,
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[
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[
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[
0.212747,
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],
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0.099996,
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],
"network.6.weight": [
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[
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"network.6.bias": [
0.104089,
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],
"network.8.weight": [
[
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[
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[
-0.186659,
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[
-0.498104,
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[
0.086415,
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[
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]
],
"network.8.bias": [
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0.363258,
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],
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[
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]
],
"network.10.bias": [
0.066245
]
}
## Activation Signature
### 0
fourier: [[29.629656, 30.112302, 223.453039], [33.400906, 36.975552, 138.205456], [31.717633, 32.571850, 258.462920], [53.880222, 58.355118, 337.374017], [27.181931, 29.316968, 81.448187], [30.291958, 31.221684, 168.774267]]
### 2
fourier: [[32.013618, 38.401689, 173.156382], [17.571954, 19.120095, 105.941930], [27.416055, 27.788726, 161.675804], [22.349185, 25.746041, 108.669973], [44.283544, 49.999798, 151.113531], [33.213243, 37.391732, 261.785295]]
### 4
fourier: [[32.293035, 34.754432, 51.524783], [36.384478, 37.522674, 50.993719], [25.962751, 26.529849, 64.053699], [33.666066, 34.134109, 221.333855], [40.184613, 40.348396, 288.584331], [48.414501, 53.948757, 172.591070]]
### 6
fourier: [[14.680996, 16.778384, 76.542538], [31.446520, 31.557885, 35.764514], [65.780748, 72.931713, 281.965526], [13.450240, 15.745166, 20.486521], [16.994020, 18.764822, 33.499338], [20.555319, 26.603002, 26.890822]]
### 8
fourier: [[16.878482, 20.951384, 77.037845], [36.037198, 36.407925, 110.224591], [33.825484, 35.017797, 81.434977], [38.063095, 43.742731, 44.068409], [11.458981, 12.386953, 12.630622], [49.716797, 50.173107, 128.396728]]
### 10
fourier: [[52.038102, 52.783071, 215.611453]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [29.629656465147704, 30.11230189625718, 223.45303863286972]}, "1": {"fourier": [33.40090594683248, 36.97555171488861, 138.20545567572117]}, "2": {"fourier": [31.7176331775257, 32.571850260471756, 258.46292024850845]}, "3": {"fourier": [53.880222493285146, 58.35511846194845, 337.3740168362856]}, "4": {"fourier": [27.181931377730333, 29.316968115914463, 81.44818688929081]}, "5": {"fourier": [30.291957629419844, 31.22168393368633, 168.77426677942276]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [32.01361772130593, 38.401688677626616, 173.15638187527657]}, "1": {"fourier": [17.571953540530092, 19.120095212887197, 105.94192995131016]}, "2": {"fourier": [27.416054568805073, 27.788725711886435, 161.6758037507534]}, "3": {"fourier": [22.34918467697795, 25.746040590569272, 108.66997340321541]}, "4": {"fourier": [44.28354406386186, 49.9997975402343, 151.11353129148483]}, "5": {"fourier": [33.21324292233187, 37.39173191110837, 261.7852946072817]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [32.29303535238079, 34.7544322800669, 51.524783223867416]}, "1": {"fourier": [36.38447784450899, 37.522673913945866, 50.993718683719635]}, "2": {"fourier": [25.96275104894974, 26.52984943698605, 64.05369851738214]}, "3": {"fourier": [33.66606558699205, 34.134109018360554, 221.33385545015335]}, "4": {"fourier": [40.184613473998475, 40.34839614817801, 288.5843313932419]}, "5": {"fourier": [48.41450107436771, 53.948757329033775, 172.5910701751709]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [14.680995952135065, 16.778384338579066, 76.54253769293427]}, "1": {"fourier": [31.446520307000842, 31.55788512690243, 35.764514058828354]}, "2": {"fourier": [65.78074804813173, 72.93171256377492, 281.9655259922147]}, "3": {"fourier": [13.450239717198073, 15.745166422383612, 20.4865210801363]}, "4": {"fourier": [16.994019501938403, 18.764822018175458, 33.49933834373951]}, "5": {"fourier": [20.55531893670559, 26.60300248773168, 26.890821738065338]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [16.878482059365563, 20.95138397180826, 77.03784544765949]}, "1": {"fourier": [36.037197758007146, 36.40792468383901, 110.22459143400192]}, "2": {"fourier": [33.825484018213395, 35.017796875325566, 81.43497720360756]}, "3": {"fourier": [38.06309456020829, 43.74273096758422, 44.06840905145677]}, "4": {"fourier": [11.458980616182089, 12.38695321000429, 12.630621611020146]}, "5": {"fourier": [49.71679665235173, 50.17310673541245, 128.39672788977623]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [52.03810182787282, 52.78307099704275, 215.61145283281803]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.116116, 0.482704, 0.248028, -0.029262, 0.59673], [-0.707951, 0.235531, 0.277732, 0.420541, 0.495674], [0.197418, -0.408595, -0.380919, -0.450372, -0.443357], [0.832428, -0.103877, 0.630532, 0.412591, 0.375895], [0.565398, -0.224636, 0.333996, 0.095361, -0.014063], [-0.693097, 0.02972, 0.702901, 0.190164, 0.151688]], "network.0.bias": [0.5564, -0.105878, -0.064633, 0.236482, -0.274124, 0.620474], "network.2.weight": [[0.577278, 0.652859, -0.10408, -0.218782, -0.358623, -0.011069], [0.181168, -0.041406, -0.250533, -0.181113, 0.038493, 0.606008], [0.466788, -0.240405, -0.602077, 0.238015, 0.212081, -0.0919], [0.056177, 0.13712, -0.058175, -0.457119, 0.073248, 0.239559], [0.332004, -0.48939, -0.573796, 0.38643, 0.519709, -0.462566], [0.338487, 0.444823, -0.165663, 0.095756, 0.029773, 0.567524]], "network.2.bias": [0.595737, 0.265749, 0.14918, -0.409022, 0.655231, -0.146034], "network.4.weight": [[-0.374295, -0.211575, -0.03043, -0.35563, 0.385278, -0.120232], [-0.436096, -0.269957, 0.465428, 0.178584, 0.250569, 0.155314], [0.613163, 0.234072, -0.384487, -0.355257, 0.058005, -0.11382], [0.222023, 0.344231, 0.145182, -0.641889, -0.206923, 0.483854], [0.539521, 0.526043, -0.022888, -0.169445, 0.022943, 0.439404], [0.212747, 0.356589, -0.177413, 0.046088, -0.538018, 0.601886]], "network.4.bias": [0.131783, 0.097967, 0.099996, 0.268223, 0.285281, 0.553824], "network.6.weight": [[0.201279, -0.145814, -0.241912, 0.047335, 0.047516, -0.423998], [0.325493, 0.514788, -0.01499, 0.228009, 0.128839, -0.5565], [-0.663681, -0.462979, 0.258695, 0.500705, 0.484023, 0.265279], [0.497904, 0.206091, 0.163422, -0.291875, -0.155562, 0.326059], [0.313809, 0.006327, -0.549004, -0.258297, 0.107474, 0.007874], [0.171622, 0.454277, -0.245175, 0.076689, 0.14192, -0.331981]], "network.6.bias": [0.104089, 0.216708, 0.160329, -0.245108, 0.24371, 0.149983], "network.8.weight": [[0.304399, 0.252051, 0.21216, 0.78848, 0.24421, 0.36821], [-0.134121, -0.393495, 0.329107, 0.045102, -0.559384, -0.224254], [-0.186659, -0.605058, 0.27677, -0.166562, 0.220772, -0.177008], [-0.498104, -0.402351, 0.273001, -0.754207, -0.072143, -0.542197], [0.086415, -0.111767, 0.03119, -0.223791, -0.149014, -0.239221], [0.086575, -0.452776, 0.473051, -0.25201, -0.483973, -0.354524]], "network.8.bias": [-0.277618, 0.436958, 0.363258, -0.056852, -0.024882, 0.259055], "network.10.weight": [[0.357357, -0.443676, -0.629314, -0.220934, -0.096289, -0.588399]], "network.10.bias": [0.066245]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7060195505619049, "train_acc": 0.435, "val_loss": 0.6883154511451721, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6789571344852448, "train_acc": 0.565, "val_loss": 0.6603962779045105, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6577168405056, "train_acc": 0.565, "val_loss": 0.5219113230705261, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.465732604265213, "train_acc": 0.64, "val_loss": 0.21646076440811157, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.28685804456472397, "train_acc": 0.925, "val_loss": 0.25790107250213623, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.25149546563625336, "train_acc": 0.92, "val_loss": 0.16607162356376648, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.22418148815631866, "train_acc": 0.905, "val_loss": 0.18774765729904175, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.2108570784330368, "train_acc": 0.925, "val_loss": 0.29730358719825745, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.24299220740795135, "train_acc": 0.92, "val_loss": 0.17051102221012115, "val_acc": 0.94}], "summary": {"total_epochs": 9, "degraded_epochs": 3, "improved_epochs": 6, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6883154511451721, "final_val_loss": 0.5219113230705261, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.21646076440811157, "final_val_loss": 0.17051102221012115, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 3}, "improvement": 0.3799999999999999, "first_improvement_epoch": 2}} |
74 | {"target_pattern": "alternating", "degraded_accuracy": 0.62, "improved_accuracy": 0.96, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8119, "learning_rate": 0.06602573665381442, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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"network.0.bias": [
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],
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],
[
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],
[
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[
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]
],
"network.2.bias": [
0.82944,
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],
"network.4.weight": [
[
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],
[
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],
[
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],
[
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],
[
0.856375,
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]
],
"network.4.bias": [
0.045681,
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],
"network.6.weight": [
[
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],
[
-0.117216,
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0.719596
],
[
-0.167605,
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],
[
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],
[
-0.725439,
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]
],
"network.6.bias": [
0.697551,
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],
"network.8.weight": [
[
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0.313045,
0.487617,
-0.168133
]
],
"network.8.bias": [
-0.744977
]
}
## Activation Signature
### 0
fourier: [[51.229930, 55.282942, 341.244099], [47.378664, 49.980809, 202.507154], [34.889992, 37.613099, 39.568628], [65.606608, 75.109603, 184.443862], [20.052409, 20.537914, 21.033078]]
### 2
fourier: [[19.016580, 20.945917, 56.489015], [10.787959, 14.407336, 105.738015], [19.557538, 21.883166, 97.651362], [32.018236, 32.346180, 263.239487], [31.198919, 31.239854, 83.302338]]
### 4
fourier: [[18.472530, 18.537909, 154.040011], [27.062185, 27.363579, 249.434921], [10.698697, 11.587467, 150.077255], [13.672168, 14.784515, 81.586948], [27.412022, 29.044916, 31.316152]]
### 6
fourier: [[21.633977, 23.065506, 73.108309], [37.084063, 40.076298, 165.067636], [3.550857, 3.941183, 67.217240], [24.337188, 26.149490, 138.947913], [12.444090, 16.502768, 206.793194]]
### 8
fourier: [[16.305926, 16.770583, 17.140446]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.290853,
0.856288,
0.489404,
0.377626,
0.279103
],
[
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],
[
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],
[
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],
[
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],
"network.0.bias": [
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],
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],
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],
[
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],
[
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],
[
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]
],
"network.2.bias": [
0.82944,
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-0.021655,
-0.019795,
0.477696
],
"network.4.weight": [
[
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0.051596,
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0.564236,
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],
[
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0.262865,
0.826777,
-0.390706
],
[
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],
[
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0.198174
],
[
0.856375,
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]
],
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0.045681,
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0.521827
],
"network.6.weight": [
[
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],
[
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0.719596
],
[
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],
[
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],
[
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]
],
"network.6.bias": [
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],
"network.8.weight": [
[
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0.313045,
0.487617,
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]
],
"network.8.bias": [
-0.744977
]
}
## Activation Signature
### 0
fourier: [[51.229930, 55.282942, 341.244099], [47.378664, 49.980809, 202.507154], [34.889992, 37.613099, 39.568628], [65.606608, 75.109603, 184.443862], [20.052409, 20.537914, 21.033078]]
### 2
fourier: [[19.016580, 20.945917, 56.489015], [10.787959, 14.407336, 105.738015], [19.557538, 21.883166, 97.651362], [32.018236, 32.346180, 263.239487], [31.198919, 31.239854, 83.302338]]
### 4
fourier: [[18.472530, 18.537909, 154.040011], [27.062185, 27.363579, 249.434921], [10.698697, 11.587467, 150.077255], [13.672168, 14.784515, 81.586948], [27.412022, 29.044916, 31.316152]]
### 6
fourier: [[21.633977, 23.065506, 73.108309], [37.084063, 40.076298, 165.067636], [3.550857, 3.941183, 67.217240], [24.337188, 26.149490, 138.947913], [12.444090, 16.502768, 206.793194]]
### 8
fourier: [[16.305926, 16.770583, 17.140446]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [51.22993037801922, 55.282942282745765, 341.2440990805626]}, "1": {"fourier": [47.378664251570015, 49.98080912717842, 202.5071539580822]}, "2": {"fourier": [34.88999183228041, 37.61309889841601, 39.568628464315005]}, "3": {"fourier": [65.60660810463156, 75.1096029144826, 184.44386235624552]}, "4": {"fourier": [20.052409205687937, 20.537913704643625, 21.033078333209662]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [19.01658022033298, 20.945916758821138, 56.48901525139809]}, "1": {"fourier": [10.78795910546353, 14.40733585557435, 105.73801529407501]}, "2": {"fourier": [19.557537616776724, 21.8831664331535, 97.65136162750423]}, "3": {"fourier": [32.01823593665526, 32.346179550072605, 263.2394867017865]}, "4": {"fourier": [31.198918548399543, 31.23985364159335, 83.3023378700018]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [18.472529901675074, 18.53790884028711, 154.04001125134528]}, "1": {"fourier": [27.06218473137501, 27.3635794543303, 249.4349209666252]}, "2": {"fourier": [10.698697401735929, 11.587466654076199, 150.07725489139557]}, "3": {"fourier": [13.67216790427935, 14.784515001835075, 81.58694806694984]}, "4": {"fourier": [27.412021547555923, 29.044916010782377, 31.31615197156929]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [21.633976535632563, 23.065506317202097, 73.10830876231194]}, "1": {"fourier": [37.08406336571727, 40.07629797715626, 165.067636013031]}, "2": {"fourier": [3.5508571866741137, 3.941182993486719, 67.21724039316177]}, "3": {"fourier": [24.337188411344087, 26.149490041767805, 138.94791289418936]}, "4": {"fourier": [12.44408980098995, 16.502767681123824, 206.79319441318512]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [16.30592553612919, 16.77058255472597, 17.14044576883316]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.290853, 0.856288, 0.489404, 0.377626, 0.279103], [0.043909, -0.651801, 0.088917, -0.838296, 0.595079], [-0.794566, -0.532124, 0.258362, 0.358833, 0.547438], [-0.694088, 0.356652, -1.098018, 0.580564, -0.693991], [-0.50494, 0.118307, 0.400686, 0.053129, -0.144889]], "network.0.bias": [-0.307032, -0.238985, -0.090644, 0.069051, -0.197144], "network.2.weight": [[-0.015899, 0.393173, -0.617395, 0.787562, -0.165588], [-0.192393, -0.095958, -0.073829, -0.331703, 0.220671], [-0.342151, 0.453102, 0.341652, 0.034087, -0.241467], [0.580319, -0.213441, 0.642655, -0.233899, 0.709756], [-0.221402, 1.018233, -0.906514, 0.828337, -0.799488]], "network.2.bias": [0.82944, -0.33077, -0.021655, -0.019795, 0.477696], "network.4.weight": [[0.188909, 0.051596, -0.105532, 0.564236, -0.369356], [0.184904, -0.075065, 0.262865, 0.826777, -0.390706], [-0.381064, -0.058121, -0.061588, -0.320567, -0.079917], [0.211097, 0.010829, -0.635531, -0.337355, 0.198174], [0.856375, -0.336966, -0.558267, -0.413475, 0.854519]], "network.4.bias": [0.045681, 0.340903, -0.391646, -0.149471, 0.521827], "network.6.weight": [[-0.421096, -0.385381, 0.072051, -0.062849, 0.322323], [-0.117216, -0.983044, 0.209788, 0.210824, 0.719596], [-0.167605, -0.030089, 0.120821, -0.006865, -0.139193], [-0.476346, -0.36324, -0.008147, 0.559785, 0.457559], [-0.725439, 0.06781, 0.05037, -0.209413, -0.723465]], "network.6.bias": [0.697551, 0.450303, -0.254235, -0.150217, -0.59944], "network.8.weight": [[0.443182, 0.748584, 0.313045, 0.487617, -0.168133]], "network.8.bias": [-0.744977]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6851904690265656, "train_acc": 0.555, "val_loss": 0.6799935102462769, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6713716089725494, "train_acc": 0.565, "val_loss": 0.6291624307632446, "val_acc": 0.62}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6156542599201202, "train_acc": 0.685, "val_loss": 0.5355919599533081, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5064095109701157, "train_acc": 0.855, "val_loss": 0.38795703649520874, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4062959849834442, "train_acc": 0.915, "val_loss": 0.3373543918132782, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.37443089485168457, "train_acc": 0.93, "val_loss": 0.3147325813770294, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2921057492494583, "train_acc": 0.95, "val_loss": 0.34073707461357117, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.266709066927433, "train_acc": 0.97, "val_loss": 0.33448705077171326, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.2519490718841553, "train_acc": 0.965, "val_loss": 0.4174790680408478, "val_acc": 0.94}], "summary": {"total_epochs": 9, "degraded_epochs": 2, "improved_epochs": 7, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.6799935102462769, "final_val_loss": 0.6291624307632446, "initial_val_acc": 0.54, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.5355919599533081, "final_val_loss": 0.4174790680408478, "initial_val_acc": 0.88, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 6}, "improvement": 0.33999999999999997, "first_improvement_epoch": 1}} |
75 | {"target_pattern": "alternating", "degraded_accuracy": 0.38, "improved_accuracy": 0.96, "improvement": 0.58, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8435, "learning_rate": 0.054455867399290744, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[19.707998, 23.247586, 118.616282], [36.595426, 40.717846, 159.559644], [42.736487, 58.592531, 160.056752], [26.119601, 27.427225, 149.779181], [43.061916, 43.609268, 169.276698], [33.640801, 44.266599, 113.062112], [17.407512, 17.593665, 73.684932], [78.649880, 79.858472, 252.794025]]
### 2
fourier: [[45.724137, 46.979210, 156.992922], [40.691199, 43.884470, 205.302514], [21.523970, 28.478287, 167.630445], [33.011415, 36.901817, 50.137286], [19.025884, 19.193142, 142.072952], [12.831823, 12.984386, 157.386397], [15.391391, 25.490611, 146.137856], [37.565429, 39.351576, 43.051561]]
### 4
fourier: [[45.675845, 50.878172, 146.157017], [36.163677, 41.631282, 85.759483], [0.777093, 0.837613, 50.689716], [30.459005, 38.903990, 61.272157], [45.174191, 52.644743, 153.075311], [30.903224, 35.056982, 100.555860], [17.658650, 17.742326, 111.840937], [23.344377, 26.154824, 32.564739]]
### 6
fourier: [[54.574958, 60.885280, 184.591046], [15.972684, 16.046072, 125.219833], [45.227980, 51.369437, 123.740881], [90.596086, 105.571664, 280.151208], [64.169038, 74.443389, 175.273166], [80.240186, 92.038720, 256.970605], [34.641108, 35.140350, 44.084815], [26.126028, 35.885192, 48.874487]]
### 8
fourier: [[3.315268, 3.510933, 43.535298], [18.061579, 19.548685, 86.726474], [159.005805, 177.878336, 482.539833], [173.146102, 197.066455, 477.608592], [140.938796, 160.282681, 373.829274], [41.302216, 47.065215, 56.351572], [143.247226, 162.254047, 407.771542], [50.492763, 58.651478, 70.611779]]
### 10
fourier: [[224.114767, 250.996745, 654.496754]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[19.707998, 23.247586, 118.616282], [36.595426, 40.717846, 159.559644], [42.736487, 58.592531, 160.056752], [26.119601, 27.427225, 149.779181], [43.061916, 43.609268, 169.276698], [33.640801, 44.266599, 113.062112], [17.407512, 17.593665, 73.684932], [78.649880, 79.858472, 252.794025]]
### 2
fourier: [[45.724137, 46.979210, 156.992922], [40.691199, 43.884470, 205.302514], [21.523970, 28.478287, 167.630445], [33.011415, 36.901817, 50.137286], [19.025884, 19.193142, 142.072952], [12.831823, 12.984386, 157.386397], [15.391391, 25.490611, 146.137856], [37.565429, 39.351576, 43.051561]]
### 4
fourier: [[45.675845, 50.878172, 146.157017], [36.163677, 41.631282, 85.759483], [0.777093, 0.837613, 50.689716], [30.459005, 38.903990, 61.272157], [45.174191, 52.644743, 153.075311], [30.903224, 35.056982, 100.555860], [17.658650, 17.742326, 111.840937], [23.344377, 26.154824, 32.564739]]
### 6
fourier: [[54.574958, 60.885280, 184.591046], [15.972684, 16.046072, 125.219833], [45.227980, 51.369437, 123.740881], [90.596086, 105.571664, 280.151208], [64.169038, 74.443389, 175.273166], [80.240186, 92.038720, 256.970605], [34.641108, 35.140350, 44.084815], [26.126028, 35.885192, 48.874487]]
### 8
fourier: [[3.315268, 3.510933, 43.535298], [18.061579, 19.548685, 86.726474], [159.005805, 177.878336, 482.539833], [173.146102, 197.066455, 477.608592], [140.938796, 160.282681, 373.829274], [41.302216, 47.065215, 56.351572], [143.247226, 162.254047, 407.771542], [50.492763, 58.651478, 70.611779]]
### 10
fourier: [[224.114767, 250.996745, 654.496754]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.707997857402606, 23.247586146905086, 118.61628219485283]}, "1": {"fourier": [36.59542567866678, 40.717845573139535, 159.55964440107346]}, "2": {"fourier": [42.736486846959934, 58.59253134741829, 160.0567517876625]}, "3": {"fourier": [26.11960078661013, 27.427224968051046, 149.77918085455894]}, "4": {"fourier": [43.06191607214756, 43.609268129942365, 169.2766979932785]}, "5": {"fourier": [33.64080146968031, 44.26659887261266, 113.06211234629154]}, "6": {"fourier": [17.407511631008873, 17.593665150075246, 73.68493213132024]}, "7": {"fourier": [78.6498801817791, 79.85847222100027, 252.79402542114258]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [45.72413669061772, 46.97921025918095, 156.99292162060738]}, "1": {"fourier": [40.69119905716554, 43.88447002878864, 205.30251386761665]}, "2": {"fourier": [21.523970342291594, 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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [3.3152676099132568, 3.510932561308609, 43.535298347473145]}, "1": {"fourier": [18.06157892451722, 19.548685204192424, 86.72647351026535]}, "2": {"fourier": [159.00580544722837, 177.8783364192631, 482.5398325622082]}, "3": {"fourier": [173.14610232451633, 197.06645516557091, 477.60859191417694]}, "4": {"fourier": [140.93879588113643, 160.28268086588466, 373.8292741626501]}, "5": {"fourier": [41.30221609247013, 47.065215131659365, 56.35157205136944]}, "6": {"fourier": [143.2472263024204, 162.2540467350238, 407.77154153585434]}, "7": {"fourier": [50.49276308001817, 58.65147756273803, 70.61177872336333]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [224.11476682769847, 250.99674519277292, 654.4967538714409]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.176812, 0.062233, -0.396911, -0.381874, 0.451224], [0.851178, 0.201686, 0.198454, -0.087486, -0.260852], [0.379599, 0.562551, -0.213058, 0.541381, -0.964279], [0.264264, 0.293405, -0.29509, -0.519309, -0.437964], [-1.038334, 0.081779, 0.474047, 0.289704, 0.732623], [0.624245, -0.528211, 0.054505, -0.733429, 0.235316], [-0.121078, 0.054342, -0.117927, 0.264951, 0.407302], [-1.002478, 0.673866, -1.174948, 0.095292, -0.680797]], "network.0.bias": [-0.559894, 0.440903, 0.754297, -0.257529, 0.508929, 0.098156, 0.046199, 0.30041], "network.2.weight": 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-0.475104, 0.355284, 0.263292, 0.197033, -0.46928], [0.549608, 0.355842, -0.200034, -0.541967, 0.57534, 0.564671, 0.297435, -0.174754], [-0.109426, -0.006838, -0.024844, 0.671302, -0.329033, -0.218914, -0.253262, 0.684955], [-0.17148, -0.204009, -0.036592, 1.070957, -0.073009, 0.132079, 0.120466, 0.757401]], "network.6.bias": [-0.189943, -0.498409, -0.318242, 0.150522, -0.096155, -0.057004, 0.24509, 0.540859], "network.8.weight": [[-0.178879, -0.118008, 0.092483, -0.001936, -0.165538, 0.173369, -0.037288, -0.114463], [0.245981, -0.133368, -0.205703, -0.040832, -0.031229, -0.029785, -0.410487, -0.592684], [0.562215, -0.281935, 0.405376, 0.603469, 0.292319, 0.504523, 0.059477, -0.415328], [0.158179, -0.079946, 0.328671, 0.665122, 0.505662, 0.638744, -0.635658, -0.600732], [0.431373, -0.285395, 0.479943, 0.267367, 0.433142, 0.481956, -0.381739, -0.566829], [0.134803, 0.038848, 0.212231, 0.147465, 0.357778, -0.228482, -0.218391, -0.727724], [0.464638, 0.342027, 0.501674, 0.428022, 0.218372, 0.498142, -0.56912, -0.283183], [0.079276, -0.106945, 0.162798, -0.49737, -0.203252, 0.064812, 0.508636, 0.840079]], "network.8.bias": [-0.288353, -0.179963, -0.367371, -0.049688, -0.196792, -0.073387, -0.169051, 0.137276], "network.10.weight": [[0.20265, -0.14279, -0.395441, -0.440076, -0.345401, -0.125522, -0.284859, 0.553907]], "network.10.bias": [0.437476]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6766458749771118, "train_acc": 0.605, "val_loss": 0.7868483662605286, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6720735430717468, "train_acc": 0.605, "val_loss": 0.7764240503311157, "val_acc": 0.38}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6609081625938416, "train_acc": 0.605, "val_loss": 0.7560861706733704, "val_acc": 0.38}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6359816491603851, "train_acc": 0.605, "val_loss": 0.6984158158302307, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6306037902832031, "train_acc": 0.53, "val_loss": 0.6461824178695679, "val_acc": 0.38}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.593607097864151, "train_acc": 0.53, "val_loss": 0.6279016137123108, "val_acc": 0.42}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5561584830284119, "train_acc": 0.66, "val_loss": 0.567995548248291, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.47092851996421814, "train_acc": 0.805, "val_loss": 0.514876127243042, "val_acc": 0.72}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.4265871196985245, "train_acc": 0.715, "val_loss": 0.3923031985759735, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.3392106741666794, "train_acc": 0.875, "val_loss": 0.2695101797580719, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.282464824616909, "train_acc": 0.88, "val_loss": 0.19645927846431732, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.26507116854190826, "train_acc": 0.89, "val_loss": 0.14964163303375244, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.2781306505203247, "train_acc": 0.875, "val_loss": 0.13071051239967346, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.24824018776416779, "train_acc": 0.895, "val_loss": 0.13136425614356995, "val_acc": 0.96}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.7868483662605286, "final_val_loss": 0.6984158158302307, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.6461824178695679, "final_val_loss": 0.13136425614356995, "initial_val_acc": 0.38, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.58, "first_improvement_epoch": 3}} |
76 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.48, "improved_accuracy": 1.0, "improvement": 0.52, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8999, "learning_rate": 0.06938211819600233, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.012063,
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0.855624,
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0.070912
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0.401491,
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0.08462
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[
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[
0.12582,
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[
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[
0.539983,
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],
"network.0.bias": [
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[
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[
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[
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],
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[
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[
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"network.6.weight": [
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"network.8.bias": [
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"network.10.weight": [
[
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}
## Activation Signature
### 0
fourier: [[37.127095, 44.188154, 46.673294], [15.868561, 20.419153, 21.314772], [38.185116, 39.678842, 126.244083], [21.843956, 26.413800, 95.267168], [30.428105, 34.363719, 136.331828], [25.497536, 28.953944, 125.130913]]
### 2
fourier: [[31.119188, 38.686836, 150.248966], [9.042610, 9.617117, 85.113839], [29.371541, 33.372749, 34.781881], [26.827283, 30.159325, 142.865862], [12.607844, 14.003320, 91.859298], [24.806081, 28.935765, 30.959271]]
### 4
fourier: [[14.292714, 16.326544, 16.638738], [38.877318, 44.448660, 177.053162], [32.285584, 40.842469, 170.461742], [27.324413, 30.059135, 89.053621], [14.925383, 18.236017, 139.129944], [38.003787, 47.080284, 196.483290]]
### 6
fourier: [[70.976739, 92.940039, 418.055078], [35.686361, 46.688665, 258.501091], [29.854804, 39.655614, 194.005156], [11.423167, 13.261174, 21.337268], [58.352424, 70.335759, 249.197433], [85.655246, 114.653953, 529.929999]]
### 8
fourier: [[3.116177, 3.234227, 3.451048], [107.658199, 141.530955, 642.353207], [131.880900, 173.958532, 752.436313], [14.407957, 18.865097, 111.697468], [51.082154, 66.384784, 224.793815], [53.318596, 67.822936, 264.808365]]
### 10
fourier: [[141.025604, 185.470392, 757.393189]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.012063,
-0.587815,
0.855624,
-0.513397,
0.070912
],
[
-0.204183,
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0.401491,
0.086566,
0.08462
],
[
-0.765052,
0.154188,
-0.036901,
0.503168,
0.473826
],
[
0.12582,
0.160141,
-0.373847,
0.019895,
-0.465845
],
[
0.644636,
0.067373,
0.280913,
-0.178585,
-0.130898
],
[
0.539983,
-0.323815,
0.123874,
0.168341,
0.148026
]
],
"network.0.bias": [
0.496807,
-0.513374,
0.487496,
-0.19411,
0.547427,
0.506105
],
"network.2.weight": [
[
1.039031,
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0.660341,
0.060162,
-0.136888,
0.004636
],
[
0.148482,
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0.062835,
0.02341,
-0.235289
],
[
-0.406364,
0.28727,
-0.567408,
0.396045,
0.503041,
0.363788
],
[
0.174993,
0.305328,
0.808792,
0.191481,
-0.346353,
0.237948
],
[
0.034557,
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-0.187918,
-0.161468,
-0.334986
],
[
-0.640341,
0.031405,
0.362709,
0.167971,
-0.199303,
0.078748
]
],
"network.2.bias": [
-0.094217,
-0.348984,
0.096622,
0.262783,
0.120666,
-0.239569
],
"network.4.weight": [
[
-0.205201,
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0.448082,
0.047897,
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-0.327859
],
[
0.541793,
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-0.593239,
0.724893,
-0.288859,
-0.100657
],
[
0.788539,
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-0.316627,
0.322502,
-0.249608,
-0.127033
],
[
0.170548,
0.014097,
-0.589272,
0.347101,
-0.355029,
0.590741
],
[
0.332485,
0.596188,
-0.051406,
-0.741176,
1.126914,
0.002206
],
[
0.857107,
0.019081,
-0.384389,
0.40228,
-0.057287,
0.009696
]
],
"network.4.bias": [
0.070773,
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0.176534,
0.308327,
-0.687505,
0.324291
],
"network.6.weight": [
[
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],
[
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],
[
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],
[
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0.537772,
0.666589,
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],
[
0.57442,
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-0.599493,
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],
[
-0.196958,
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0.90168,
0.853448,
0.5807,
0.842322
]
],
"network.6.bias": [
-0.077188,
-0.205911,
-0.08637,
-0.529622,
0.467791,
0.149415
],
"network.8.weight": [
[
0.182174,
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-0.576058,
-0.121626,
-0.157683
],
[
0.669346,
0.002085,
0.092187,
0.225102,
-0.217791,
0.684441
],
[
0.758553,
-0.119193,
0.012063,
0.245636,
-0.64801,
0.868039
],
[
-0.281019,
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-0.290675,
0.067286,
-0.125219,
0.053651
],
[
-0.284366,
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0.005802,
-0.373573,
0.595149,
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],
[
-0.171253,
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-0.074781,
-0.8604,
0.406897,
-0.39959
]
],
"network.8.bias": [
0.178171,
-0.016188,
-0.187787,
-0.227931,
0.429155,
0.127554
],
"network.10.weight": [
[
0.034158,
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-0.269591,
0.469694,
0.071955
]
],
"network.10.bias": [
0.701237
]
}
## Activation Signature
### 0
fourier: [[37.127095, 44.188154, 46.673294], [15.868561, 20.419153, 21.314772], [38.185116, 39.678842, 126.244083], [21.843956, 26.413800, 95.267168], [30.428105, 34.363719, 136.331828], [25.497536, 28.953944, 125.130913]]
### 2
fourier: [[31.119188, 38.686836, 150.248966], [9.042610, 9.617117, 85.113839], [29.371541, 33.372749, 34.781881], [26.827283, 30.159325, 142.865862], [12.607844, 14.003320, 91.859298], [24.806081, 28.935765, 30.959271]]
### 4
fourier: [[14.292714, 16.326544, 16.638738], [38.877318, 44.448660, 177.053162], [32.285584, 40.842469, 170.461742], [27.324413, 30.059135, 89.053621], [14.925383, 18.236017, 139.129944], [38.003787, 47.080284, 196.483290]]
### 6
fourier: [[70.976739, 92.940039, 418.055078], [35.686361, 46.688665, 258.501091], [29.854804, 39.655614, 194.005156], [11.423167, 13.261174, 21.337268], [58.352424, 70.335759, 249.197433], [85.655246, 114.653953, 529.929999]]
### 8
fourier: [[3.116177, 3.234227, 3.451048], [107.658199, 141.530955, 642.353207], [131.880900, 173.958532, 752.436313], [14.407957, 18.865097, 111.697468], [51.082154, 66.384784, 224.793815], [53.318596, 67.822936, 264.808365]]
### 10
fourier: [[141.025604, 185.470392, 757.393189]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [37.12709483080156, 44.188154351335506, 46.673293850446555]}, "1": {"fourier": [15.868561373398748, 20.419153170722097, 21.314771714459386]}, "2": {"fourier": [38.18511579956232, 39.678841836994216, 126.24408319592476]}, "3": {"fourier": [21.843956321113524, 26.41380027184283, 95.26716826856136]}, "4": {"fourier": [30.42810520199379, 34.363719275635354, 136.33182793855667]}, "5": {"fourier": [25.497536270751844, 28.95394378674483, 125.13091313838959]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [31.11918754074337, 38.686836446662355, 150.2489659190178]}, "1": {"fourier": [9.04260993788878, 9.61711693992917, 85.11383895576]}, "2": {"fourier": [29.371541329441357, 33.37274890323789, 34.781881316809894]}, "3": {"fourier": [26.82728312886904, 30.159324785742736, 142.86586160957813]}, "4": {"fourier": [12.607844094497512, 14.003320236348276, 91.8592980504036]}, "5": {"fourier": [24.806080624809184, 28.935764513334874, 30.959271147847176]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [14.292713777813626, 16.326544049468964, 16.6387382671237]}, "1": {"fourier": [38.87731777433754, 44.448659907430525, 177.05316189676523]}, "2": {"fourier": [32.28558386433929, 40.8424690888686, 170.4617423415184]}, "3": {"fourier": [27.324412773895, 30.05913501111174, 89.05362136662006]}, "4": {"fourier": [14.925382981691934, 18.23601672831286, 139.12994402647018]}, "5": {"fourier": [38.003786522113366, 47.08028425841148, 196.48329004645348]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [70.97673915999006, 92.94003913326057, 418.0550777539611]}, "1": {"fourier": [35.68636139985225, 46.68866505818128, 258.5010914802551]}, "2": {"fourier": [29.854803637876536, 39.655614100150856, 194.00515638664365]}, "3": {"fourier": [11.423166743536381, 13.261174289620772, 21.337268352508545]}, "4": {"fourier": [58.35242377183766, 70.33575919038205, 249.19743314385414]}, "5": {"fourier": [85.65524557508456, 114.65395318691414, 529.9299993216991]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [3.1161770330810916, 3.2342269476062566, 3.4510481879115105]}, "1": {"fourier": [107.65819938470636, 141.5309547744229, 642.3532070666552]}, "2": {"fourier": [131.88090000593394, 173.9585320620776, 752.4363129734993]}, "3": {"fourier": [14.407956792456833, 18.865096668997996, 111.69746752083302]}, "4": {"fourier": [51.082153822402, 66.38478382751471, 224.79381494224072]}, "5": {"fourier": [53.31859560652534, 67.82293559706356, 264.8083650544286]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [141.02560384378774, 185.47039236147916, 757.393188983202]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.012063, -0.587815, 0.855624, -0.513397, 0.070912], [-0.204183, -0.293794, 0.401491, 0.086566, 0.08462], [-0.765052, 0.154188, -0.036901, 0.503168, 0.473826], [0.12582, 0.160141, -0.373847, 0.019895, -0.465845], [0.644636, 0.067373, 0.280913, -0.178585, -0.130898], [0.539983, -0.323815, 0.123874, 0.168341, 0.148026]], "network.0.bias": [0.496807, -0.513374, 0.487496, -0.19411, 0.547427, 0.506105], "network.2.weight": [[1.039031, 0.235161, 0.660341, 0.060162, -0.136888, 0.004636], [0.148482, -0.143277, -0.2502, 0.062835, 0.02341, -0.235289], [-0.406364, 0.28727, -0.567408, 0.396045, 0.503041, 0.363788], [0.174993, 0.305328, 0.808792, 0.191481, -0.346353, 0.237948], [0.034557, -0.274239, -0.271619, -0.187918, -0.161468, -0.334986], [-0.640341, 0.031405, 0.362709, 0.167971, -0.199303, 0.078748]], "network.2.bias": [-0.094217, -0.348984, 0.096622, 0.262783, 0.120666, -0.239569], "network.4.weight": [[-0.205201, -0.744831, 0.448082, 0.047897, -0.914443, -0.327859], [0.541793, -0.880442, -0.593239, 0.724893, -0.288859, -0.100657], [0.788539, -0.559958, -0.316627, 0.322502, -0.249608, -0.127033], [0.170548, 0.014097, -0.589272, 0.347101, -0.355029, 0.590741], [0.332485, 0.596188, -0.051406, -0.741176, 1.126914, 0.002206], [0.857107, 0.019081, -0.384389, 0.40228, -0.057287, 0.009696]], "network.4.bias": [0.070773, 0.136954, 0.176534, 0.308327, -0.687505, 0.324291], "network.6.weight": [[-0.172721, 0.696086, 0.382879, 0.586429, 0.212056, 0.810836], [-0.26335, -0.60778, -0.566279, -0.262709, -0.050359, 0.060092], [-0.025383, -0.806883, -0.409709, 0.060563, -0.279265, 0.173247], [-0.265011, 0.11333, 0.26498, 0.537772, 0.666589, -0.427541], [0.57442, -0.324842, -0.424234, -0.970108, -0.599493, -0.342856], [-0.196958, 0.53841, 0.90168, 0.853448, 0.5807, 0.842322]], "network.6.bias": [-0.077188, -0.205911, -0.08637, -0.529622, 0.467791, 0.149415], "network.8.weight": [[0.182174, 0.087011, -0.15974, -0.576058, -0.121626, -0.157683], [0.669346, 0.002085, 0.092187, 0.225102, -0.217791, 0.684441], [0.758553, -0.119193, 0.012063, 0.245636, -0.64801, 0.868039], [-0.281019, -0.19655, -0.290675, 0.067286, -0.125219, 0.053651], [-0.284366, -0.271839, 0.005802, -0.373573, 0.595149, -0.297296], [-0.171253, -0.366721, -0.074781, -0.8604, 0.406897, -0.39959]], "network.8.bias": [0.178171, -0.016188, -0.187787, -0.227931, 0.429155, 0.127554], "network.10.weight": [[0.034158, -0.308267, -0.821795, -0.269591, 0.469694, 0.071955]], "network.10.bias": [0.701237]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7064076066017151, "train_acc": 0.45, "val_loss": 0.6611549258232117, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6092204451560974, "train_acc": 0.575, "val_loss": 0.5134315490722656, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5418320894241333, "train_acc": 0.61, "val_loss": 0.356577605009079, "val_acc": 0.98}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.3750210404396057, "train_acc": 0.895, "val_loss": 0.2596292793750763, "val_acc": 0.98}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.2770252600312233, "train_acc": 0.935, "val_loss": 0.19530582427978516, "val_acc": 0.98}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.228550523519516, "train_acc": 0.94, "val_loss": 0.09634770452976227, "val_acc": 1.0}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.20429839193820953, "train_acc": 0.94, "val_loss": 0.038984283804893494, "val_acc": 1.0}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.18189112097024918, "train_acc": 0.95, "val_loss": 0.028684498742222786, "val_acc": 1.0}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.17222467809915543, "train_acc": 0.95, "val_loss": 0.036272548139095306, "val_acc": 1.0}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.16451966762542725, "train_acc": 0.95, "val_loss": 0.04724635183811188, "val_acc": 1.0}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.17697396129369736, "train_acc": 0.95, "val_loss": 0.054578255861997604, "val_acc": 1.0}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6611549258232117, "final_val_loss": 0.5134315490722656, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.356577605009079, "final_val_loss": 0.054578255861997604, "initial_val_acc": 0.98, "final_val_acc": 1.0, "best_val_acc": 1.0, "best_epoch": 5}, "improvement": 0.52, "first_improvement_epoch": 1}} |
77 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.76, "improved_accuracy": 0.96, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4020, "learning_rate": 0.0658082586785923, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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[
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[
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[
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],
"network.0.bias": [
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"network.2.weight": [
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}
## Activation Signature
### 0
fourier: [[55.604829, 57.338656, 286.370347], [30.647459, 33.610716, 33.934710], [41.808646, 46.678747, 172.167971], [41.236486, 44.235080, 251.234865], [49.506560, 52.946011, 120.867061], [52.980192, 57.334086, 91.049071], [36.132980, 39.880899, 208.991094], [60.738021, 65.127489, 318.391357]]
### 2
fourier: [[102.132582, 103.279460, 449.223835], [30.333423, 30.612739, 192.769740], [32.620902, 35.064140, 226.122189], [33.933600, 37.876222, 232.193305], [23.586904, 24.776046, 177.624931], [31.948547, 33.210825, 218.542868], [28.378464, 32.040606, 107.900078], [57.499276, 63.984679, 269.277563]]
### 4
fourier: [[57.561163, 58.724879, 214.787469], [5.698561, 6.093240, 54.675072], [36.891195, 37.296685, 142.151949], [37.320226, 37.817170, 130.065426], [44.551235, 45.345706, 173.250635], [24.275348, 24.922803, 89.719698], [54.880503, 56.719900, 187.216629], [42.632847, 44.667023, 227.586412]]
### 6
fourier: [[9.807617, 10.071903, 62.030780], [57.691961, 58.718095, 247.469876], [54.707243, 56.583283, 220.995864], [64.719741, 67.374423, 223.943212], [79.842398, 83.491608, 284.487208], [84.469197, 87.243099, 294.281910], [99.738562, 103.299549, 354.780431], [116.448877, 120.448274, 422.441758]]
### 8
fourier: [[234.925979, 236.061419, 785.243379]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[55.604829, 57.338656, 286.370347], [30.647459, 33.610716, 33.934710], [41.808646, 46.678747, 172.167971], [41.236486, 44.235080, 251.234865], [49.506560, 52.946011, 120.867061], [52.980192, 57.334086, 91.049071], [36.132980, 39.880899, 208.991094], [60.738021, 65.127489, 318.391357]]
### 2
fourier: [[102.132582, 103.279460, 449.223835], [30.333423, 30.612739, 192.769740], [32.620902, 35.064140, 226.122189], [33.933600, 37.876222, 232.193305], [23.586904, 24.776046, 177.624931], [31.948547, 33.210825, 218.542868], [28.378464, 32.040606, 107.900078], [57.499276, 63.984679, 269.277563]]
### 4
fourier: [[57.561163, 58.724879, 214.787469], [5.698561, 6.093240, 54.675072], [36.891195, 37.296685, 142.151949], [37.320226, 37.817170, 130.065426], [44.551235, 45.345706, 173.250635], [24.275348, 24.922803, 89.719698], [54.880503, 56.719900, 187.216629], [42.632847, 44.667023, 227.586412]]
### 6
fourier: [[9.807617, 10.071903, 62.030780], [57.691961, 58.718095, 247.469876], [54.707243, 56.583283, 220.995864], [64.719741, 67.374423, 223.943212], [79.842398, 83.491608, 284.487208], [84.469197, 87.243099, 294.281910], [99.738562, 103.299549, 354.780431], [116.448877, 120.448274, 422.441758]]
### 8
fourier: [[234.925979, 236.061419, 785.243379]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [55.60482871630792, 57.33865567163548, 286.37034744024277]}, "1": {"fourier": [30.647459076780144, 33.61071555473017, 33.934710244675294]}, "2": {"fourier": [41.808645736013766, 46.67874729085741, 172.1679712831974]}, "3": {"fourier": [41.23648596144207, 44.235080276667134, 251.23486523330212]}, "4": {"fourier": [49.506560099466704, 52.946010816443184, 120.86706109344959]}, "5": {"fourier": [52.98019227465501, 57.33408556716839, 91.04907056689262]}, "6": {"fourier": [36.13298007189854, 39.88089861390054, 208.9910935163498]}, "7": {"fourier": [60.73802059240469, 65.12748898618723, 318.39135651290417]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [102.13258226622956, 103.2794597919841, 449.22383469343185]}, "1": {"fourier": [30.33342340213539, 30.612738740542536, 192.7697401046753]}, "2": {"fourier": [32.62090204040596, 35.06414032772665, 226.12218856811523]}, "3": {"fourier": [33.93360022907885, 37.87622226354581, 232.1933051943779]}, "4": {"fourier": [23.58690445237015, 24.77604603464282, 177.62493062019348]}, "5": {"fourier": [31.948547463941832, 33.21082519883223, 218.54286754131317]}, "6": {"fourier": [28.378463801238976, 32.040605733589764, 107.90007751435041]}, "7": {"fourier": [57.499276105115946, 63.98467862634456, 269.27756318449974]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [57.56116277450963, 58.724878526273194, 214.78746864199638]}, "1": {"fourier": [5.698561038474652, 6.0932401793951545, 54.67507189512253]}, "2": {"fourier": [36.891195180628706, 37.29668490370503, 142.15194949507713]}, "3": {"fourier": [37.320226324290275, 37.81717032979979, 130.0654258131981]}, "4": {"fourier": [44.551234506883766, 45.345705913705594, 173.25063483417034]}, "5": {"fourier": [24.275348161860098, 24.922802524472385, 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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [234.92597886163182, 236.061418660942, 785.2433788776398]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[1.151956, 0.152554, 0.47524, 0.455767, -0.172745], [0.686618, 0.09866, -0.850543, 0.41102, 0.100045], [-1.042958, -0.054669, -0.191219, -0.403994, 0.195601], [-0.588497, -0.181588, -0.131139, -0.757731, -0.013916], [0.977382, -0.08241, 0.531285, -0.270661, -0.153324], [-1.318944, -0.188692, -0.171835, 0.054419, 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"improved_stage": {"initial_val_loss": 0.5673523545265198, "final_val_loss": 0.3449581563472748, "initial_val_acc": 0.82, "final_val_acc": 0.88, "best_val_acc": 0.96, "best_epoch": 8}, "improvement": 0.19999999999999996, "first_improvement_epoch": 1}} |
78 | {"target_pattern": "alternating", "degraded_accuracy": 0.58, "improved_accuracy": 0.9, "improvement": 0.32000000000000006, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8736, "learning_rate": 0.08073496747622153, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[19.294331, 21.157583, 86.874123], [21.014564, 23.978667, 216.861951], [25.018328, 31.596533, 149.390540], [39.727376, 45.032255, 318.369109], [26.082473, 26.833801, 49.789567], [24.558730, 26.300153, 48.832454], [20.417415, 21.771625, 79.839533]]
### 2
fourier: [[16.610936, 18.295930, 77.590421], [16.784621, 18.897256, 75.545427], [22.225838, 22.914219, 143.932932], [19.228307, 21.669607, 53.532238], [10.968593, 11.528677, 112.134162], [20.511944, 22.112658, 81.254283], [23.218620, 29.338819, 49.490605]]
### 4
fourier: [[17.358615, 18.114799, 25.666123], [12.241766, 14.356541, 14.984486], [16.883431, 18.063738, 23.421551], [29.294890, 29.914801, 193.163751], [6.828584, 7.597153, 17.048626], [8.176813, 8.257001, 9.038188], [16.128836, 17.188982, 63.723764]]
### 6
fourier: [[7.202501, 7.935124, 41.987450], [17.868010, 18.091898, 21.327093], [6.531688, 7.580621, 41.991065], [13.442679, 15.026888, 17.064168], [6.771895, 7.022941, 52.517621], [6.590152, 6.964523, 7.622669], [5.544533, 5.712165, 24.463931]]
### 8
fourier: [[12.800285, 14.991277, 25.568789]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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],
[
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],
[
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],
[
0.521678,
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[
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}
## Activation Signature
### 0
fourier: [[19.294331, 21.157583, 86.874123], [21.014564, 23.978667, 216.861951], [25.018328, 31.596533, 149.390540], [39.727376, 45.032255, 318.369109], [26.082473, 26.833801, 49.789567], [24.558730, 26.300153, 48.832454], [20.417415, 21.771625, 79.839533]]
### 2
fourier: [[16.610936, 18.295930, 77.590421], [16.784621, 18.897256, 75.545427], [22.225838, 22.914219, 143.932932], [19.228307, 21.669607, 53.532238], [10.968593, 11.528677, 112.134162], [20.511944, 22.112658, 81.254283], [23.218620, 29.338819, 49.490605]]
### 4
fourier: [[17.358615, 18.114799, 25.666123], [12.241766, 14.356541, 14.984486], [16.883431, 18.063738, 23.421551], [29.294890, 29.914801, 193.163751], [6.828584, 7.597153, 17.048626], [8.176813, 8.257001, 9.038188], [16.128836, 17.188982, 63.723764]]
### 6
fourier: [[7.202501, 7.935124, 41.987450], [17.868010, 18.091898, 21.327093], [6.531688, 7.580621, 41.991065], [13.442679, 15.026888, 17.064168], [6.771895, 7.022941, 52.517621], [6.590152, 6.964523, 7.622669], [5.544533, 5.712165, 24.463931]]
### 8
fourier: [[12.800285, 14.991277, 25.568789]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.294330544540532, 21.15758295786709, 86.87412324547768]}, "1": {"fourier": [21.014564250603208, 23.97866735319463, 216.86195096373558]}, "2": {"fourier": [25.018328421657642, 31.596533019872876, 149.39053958654404]}, "3": {"fourier": [39.72737644410512, 45.0322551088681, 318.36910900473595]}, "4": {"fourier": [26.082472760653886, 26.833801336094236, 49.78956653177738]}, "5": {"fourier": [24.558730045003188, 26.300152744069297, 48.832453548908234]}, "6": {"fourier": [20.417415403204163, 21.77162539115312, 79.83953259140253]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [16.61093570195556, 18.295930248586252, 77.59042080491781]}, "1": {"fourier": [16.784620602603145, 18.897256072299676, 75.54542703181505]}, "2": {"fourier": [22.22583818889664, 22.91421875859405, 143.93293198943138]}, "3": {"fourier": [19.228306920302206, 21.669606977311854, 53.53223814163357]}, "4": {"fourier": [10.968593254091235, 11.528677379914901, 112.13416160643101]}, "5": {"fourier": [20.51194358655905, 22.11265805909587, 81.25428275763988]}, "6": {"fourier": [23.218620371943853, 29.33881939820282, 49.49060462415218]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [17.35861450064299, 18.114799322501156, 25.666123442351818]}, "1": {"fourier": [12.241765863458074, 14.356541101203437, 14.984485737012067]}, "2": {"fourier": [16.883430707451033, 18.063737624889608, 23.421551098115742]}, "3": {"fourier": [29.294890181419692, 29.914801076363606, 193.1637506186962]}, "4": {"fourier": [6.828583501432887, 7.597153486242683, 17.048626033589244]}, "5": {"fourier": [8.176812547019354, 8.257000800933774, 9.038188197666473]}, "6": {"fourier": [16.1288356802816, 17.188982194873724, 63.72376422956586]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [7.202501039640223, 7.9351242653250464, 41.98745006322861]}, "1": {"fourier": [17.868009597202935, 18.09189773868438, 21.327093023520238]}, "2": {"fourier": [6.531688250653668, 7.580620985999462, 41.99106524884701]}, "3": {"fourier": [13.442678931088603, 15.02688842434116, 17.06416818499565]}, "4": {"fourier": [6.7718954132057965, 7.022940598086874, 52.517620638012886]}, "5": {"fourier": [6.590152103943881, 6.964523082778673, 7.622668500280459]}, "6": {"fourier": [5.54453314886034, 5.712164821139555, 24.463930919766426]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [12.800284819009947, 14.991277235608793, 25.56878924742341]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.098586, 0.361351, -0.133385, 0.284552, 0.279962], [-0.092158, 0.088703, 0.493294, 0.366636, 0.103046], [0.263376, -0.025032, 0.482565, -0.244337, 0.190209], [0.03251, -0.626834, -0.226428, -0.690794, -0.011249], [0.257208, -0.585287, -0.107566, 0.194527, 0.615565], [-0.306703, 0.353084, -0.128022, -0.481215, 0.641097], [-0.27903, -0.25415, -0.21936, -0.069357, 0.356558]], "network.0.bias": [-0.247376, 0.41887, 0.659104, -0.467434, 0.348003, -0.295629, 0.090445], "network.2.weight": [[0.381318, -0.161972, -0.349019, -0.533406, -0.223, -0.322982, -0.128242], [0.302796, -0.012905, -0.052533, -0.239024, 0.505682, 0.330717, 0.305042], [-0.309269, 0.464221, 0.274095, 0.275802, 0.15966, 0.66068, 0.499985], [-0.670705, -0.365345, 0.306474, -0.194744, 0.476185, 0.141484, -0.372191], [0.070309, 0.484555, -0.037724, 0.071625, -0.191059, -0.279305, 0.484945], [0.120165, 0.266132, 0.004133, 0.411096, 0.488422, 0.504286, 0.536575], [-0.685304, -0.472606, 0.576, -0.557875, 0.59832, -0.409504, -0.631337]], "network.2.bias": [-0.05891, 0.185283, 0.100257, 0.008963, 0.293735, -0.32759, -0.109998], "network.4.weight": [[-0.272004, -0.802532, 0.223104, 0.331824, 0.346189, -0.293106, 0.011493], [0.366253, 0.008244, -0.474757, -0.113512, 0.372221, -0.218461, 0.020178], [-0.124383, 0.200827, 0.122724, 0.857853, -0.059094, -0.274379, 0.632873], [-0.120007, -0.491358, -0.490526, -0.423401, -0.487479, -0.444754, 0.090481], [-0.315838, 0.034969, 0.262942, -0.376627, -0.101744, -0.060057, -0.276556], [-0.123882, -0.237957, 0.556985, -0.262746, 0.063927, -0.371568, -0.07966], [0.052265, 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"global_epoch": 0, "train_loss": 0.6974546313285828, "train_acc": 0.56, "val_loss": 0.7094525098800659, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6745566129684448, "train_acc": 0.565, "val_loss": 0.6448755860328674, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.7199852168560028, "train_acc": 0.71, "val_loss": 0.6324295997619629, "val_acc": 0.62}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5125136226415634, "train_acc": 0.765, "val_loss": 0.5073586106300354, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4428116977214813, "train_acc": 0.855, "val_loss": 0.46540993452072144, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3646199032664299, "train_acc": 0.835, "val_loss": 0.38170701265335083, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.23899159580469131, "train_acc": 0.925, "val_loss": 0.2491236925125122, "val_acc": 0.88}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.21091583743691444, "train_acc": 0.93, "val_loss": 0.30014699697494507, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.17226729914546013, "train_acc": 0.955, "val_loss": 0.2963845431804657, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.1385003849864006, "train_acc": 0.975, "val_loss": 0.2528007924556732, "val_acc": 0.88}], "summary": {"total_epochs": 10, "degraded_epochs": 2, "improved_epochs": 8, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.7094525098800659, "final_val_loss": 0.6448755860328674, "initial_val_acc": 0.48, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.6324295997619629, "final_val_loss": 0.2528007924556732, "initial_val_acc": 0.62, "final_val_acc": 0.88, "best_val_acc": 0.9, "best_epoch": 3}, "improvement": 0.32000000000000006, "first_improvement_epoch": 1}} |
79 | {"target_pattern": "has_majority", "degraded_accuracy": 0.4, "improved_accuracy": 0.6, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8497, "learning_rate": 0.09416931889116947, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.037939,
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0.216762,
-0.197952,
-0.024776,
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0.10101
],
[
-0.106267,
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0.062454,
-0.477727,
-0.416202,
0.017296,
-0.441493
],
[
0.075019,
-0.343319,
0.101234,
0.067812,
-0.125627,
0.100439,
0.091689
],
[
0.12413,
0.132113,
0.192298,
0.313184,
0.218214,
-0.046209,
0.392707
]
],
"network.10.bias": [
-0.463418,
-0.064843,
0.299311,
0.048596,
0.079522,
-0.266358,
-0.20118
],
"network.12.weight": [
[
-0.090755,
-0.112638,
0.323359,
0.085313,
0.124657,
-0.10287,
-0.131767
]
],
"network.12.bias": [
0.269141
]
}
## Activation Signature
### 0
fourier: [[23.153519, 27.381409, 164.787236], [31.399622, 31.978191, 152.052680], [23.994384, 26.647441, 152.660597], [33.183221, 35.035928, 128.029269], [33.370262, 38.294445, 280.634277], [29.084310, 29.589484, 32.045818], [26.379601, 28.892581, 41.708723]]
### 2
fourier: [[18.005650, 18.966923, 125.258123], [29.905830, 30.103127, 246.270308], [32.457647, 34.778207, 194.794787], [7.845056, 9.593441, 55.604532], [33.037712, 35.345143, 167.844557], [43.581647, 44.390847, 292.803494], [9.795258, 11.648584, 84.918410]]
### 4
fourier: [[42.754183, 42.838204, 242.033169], [41.312199, 42.635257, 230.383514], [7.941782, 9.078103, 74.340238], [58.131628, 59.554901, 348.560959], [22.328063, 23.111895, 162.513864], [62.345810, 62.738921, 290.373416], [33.748773, 34.977836, 213.385662]]
### 6
fourier: [[9.895437, 10.168911, 55.679130], [33.405736, 34.980634, 190.633059], [8.725245, 8.935923, 69.538067], [16.902649, 17.686197, 119.119709], [4.248352, 4.354295, 40.814780], [40.807635, 42.277776, 236.558540], [14.881561, 15.731295, 101.492556]]
### 8
fourier: [[18.854450, 19.814553, 132.746828], [5.526840, 5.885333, 17.704229], [5.935321, 6.339256, 90.928646], [5.397940, 5.723858, 14.399177], [6.643099, 6.851558, 22.571623], [18.856411, 19.803691, 124.147786], [12.135670, 12.649469, 17.706266]]
### 10
fourier: [[1.927790, 2.134219, 50.072466], [1.657209, 1.839922, 13.065133], [5.294098, 5.764664, 5.869613], [2.725983, 3.004197, 7.531301], [8.329928, 9.228230, 25.780043], [1.312974, 1.421417, 30.921212], [6.224453, 6.257983, 6.894851]]
### 12
fourier: [[1.315137, 1.390445, 27.554255]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.4.weight": [
[
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[
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"network.8.weight": [
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[
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[
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[
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]
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"network.12.weight": [
[
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0.085313,
0.124657,
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"network.12.bias": [
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]
}
## Activation Signature
### 0
fourier: [[23.153519, 27.381409, 164.787236], [31.399622, 31.978191, 152.052680], [23.994384, 26.647441, 152.660597], [33.183221, 35.035928, 128.029269], [33.370262, 38.294445, 280.634277], [29.084310, 29.589484, 32.045818], [26.379601, 28.892581, 41.708723]]
### 2
fourier: [[18.005650, 18.966923, 125.258123], [29.905830, 30.103127, 246.270308], [32.457647, 34.778207, 194.794787], [7.845056, 9.593441, 55.604532], [33.037712, 35.345143, 167.844557], [43.581647, 44.390847, 292.803494], [9.795258, 11.648584, 84.918410]]
### 4
fourier: [[42.754183, 42.838204, 242.033169], [41.312199, 42.635257, 230.383514], [7.941782, 9.078103, 74.340238], [58.131628, 59.554901, 348.560959], [22.328063, 23.111895, 162.513864], [62.345810, 62.738921, 290.373416], [33.748773, 34.977836, 213.385662]]
### 6
fourier: [[9.895437, 10.168911, 55.679130], [33.405736, 34.980634, 190.633059], [8.725245, 8.935923, 69.538067], [16.902649, 17.686197, 119.119709], [4.248352, 4.354295, 40.814780], [40.807635, 42.277776, 236.558540], [14.881561, 15.731295, 101.492556]]
### 8
fourier: [[18.854450, 19.814553, 132.746828], [5.526840, 5.885333, 17.704229], [5.935321, 6.339256, 90.928646], [5.397940, 5.723858, 14.399177], [6.643099, 6.851558, 22.571623], [18.856411, 19.803691, 124.147786], [12.135670, 12.649469, 17.706266]]
### 10
fourier: [[1.927790, 2.134219, 50.072466], [1.657209, 1.839922, 13.065133], [5.294098, 5.764664, 5.869613], [2.725983, 3.004197, 7.531301], [8.329928, 9.228230, 25.780043], [1.312974, 1.421417, 30.921212], [6.224453, 6.257983, 6.894851]]
### 12
fourier: [[1.315137, 1.390445, 27.554255]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [23.153518673237873, 27.381408531748118, 164.787236019969]}, "1": {"fourier": [31.399621998999333, 31.978191234440008, 152.05268010497093]}, "2": {"fourier": [23.99438398550238, 26.647440796442503, 152.6605974882841]}, "3": {"fourier": [33.1832212016021, 35.035927536157445, 128.02926871180534]}, "4": {"fourier": [33.37026192765174, 38.29444512535911, 280.6342766582966]}, "5": {"fourier": [29.084310362028095, 29.589484113642246, 32.045817844948886]}, "6": {"fourier": [26.37960106374738, 28.892580828132253, 41.70872291922569]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [18.005650156169516, 18.966922971181067, 125.2581234946847]}, "1": {"fourier": [29.90583039904531, 30.103126692273637, 246.2703084051609]}, "2": {"fourier": [32.45764725852707, 34.77820749856406, 194.79478684067726]}, "3": {"fourier": [7.845056279555712, 9.593441362060013, 55.604532301425934]}, "4": {"fourier": [33.037711673777494, 35.34514311970398, 167.84455689787865]}, "5": {"fourier": [43.58164729147878, 44.39084714844175, 292.8034939020872]}, "6": {"fourier": [9.795257655285123, 11.6485837460761, 84.9184099137783]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [42.754183148369236, 42.83820363983019, 242.0331692546606]}, "1": {"fourier": [41.312198961580684, 42.63525656614223, 230.38351403176785]}, "2": {"fourier": [7.941781533697434, 9.078102539249151, 74.34023794531822]}, "3": {"fourier": [58.13162807983565, 59.554901342754114, 348.560958635062]}, "4": {"fourier": [22.32806309561824, 23.111895025226993, 162.5138644874096]}, "5": {"fourier": [62.34580964761211, 62.738920861653455, 290.3734156191349]}, "6": {"fourier": [33.748773098281234, 34.97783583021353, 213.38566198945045]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [9.895436523520976, 10.168911088295136, 55.67912981659174]}, "1": {"fourier": [33.405735803250785, 34.98063358146695, 190.63305858522654]}, "2": {"fourier": [8.725244677028023, 8.93592280678011, 69.53806686401367]}, "3": {"fourier": [16.90264900554495, 17.68619672061522, 119.1197089701891]}, "4": {"fourier": [4.2483520337204235, 4.354294964377926, 40.814780190587044]}, "5": {"fourier": [40.807635137374064, 42.27777632716565, 236.5585397183895]}, "6": {"fourier": [14.881560579626626, 15.731295301159713, 101.49255615472794]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [18.854449629947656, 19.814553280895126, 132.74682849645615]}, "1": {"fourier": [5.526839919471877, 5.8853329632213285, 17.70422875136137]}, "2": {"fourier": [5.935320746467457, 6.339255966354476, 90.92864573001862]}, "3": {"fourier": [5.397939633177342, 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"profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [1.3151366422071151, 1.3904451960334492, 27.554255038499832]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.141985, 0.130329, 0.445696, 0.512339, 0.043166], [-0.568847, 0.268984, 0.564706, 0.541744, -0.241299], [-0.457276, 0.288379, 0.290668, 0.358094, 0.22884], [-0.383755, -0.192939, 0.692921, 0.537126, 0.168792], [-0.303737, -0.369945, -0.414301, -0.173619, -0.358026], [-0.722215, -0.126853, 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[0.037939, -0.63438, 0.216762, -0.197952, -0.024776, -0.070836, 0.10101], [-0.106267, -0.158857, 0.062454, -0.477727, -0.416202, 0.017296, -0.441493], [0.075019, -0.343319, 0.101234, 0.067812, -0.125627, 0.100439, 0.091689], [0.12413, 0.132113, 0.192298, 0.313184, 0.218214, -0.046209, 0.392707]], "network.10.bias": [-0.463418, -0.064843, 0.299311, 0.048596, 0.079522, -0.266358, -0.20118], "network.12.weight": [[-0.090755, -0.112638, 0.323359, 0.085313, 0.124657, -0.10287, -0.131767]], "network.12.bias": [0.269141]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7190490067005157, "train_acc": 0.48, "val_loss": 0.8147441744804382, "val_acc": 0.4}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6587834060192108, "train_acc": 0.605, "val_loss": 0.7162363529205322, "val_acc": 0.4}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6678275167942047, "train_acc": 0.525, "val_loss": 0.8359633088111877, "val_acc": 0.5}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.7031737565994263, "train_acc": 0.6, "val_loss": 0.6506995558738708, "val_acc": 0.6}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6889342963695526, "train_acc": 0.51, "val_loss": 0.6528345346450806, "val_acc": 0.6}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.7106796503067017, "train_acc": 0.475, "val_loss": 0.6567021012306213, "val_acc": 0.6}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.7038856148719788, "train_acc": 0.475, "val_loss": 0.660186231136322, "val_acc": 0.6}], "summary": {"total_epochs": 7, "degraded_epochs": 2, "improved_epochs": 5, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.8147441744804382, "final_val_loss": 0.7162363529205322, "initial_val_acc": 0.4, "final_val_acc": 0.4, "best_val_acc": 0.4}, "improved_stage": {"initial_val_loss": 0.8359633088111877, "final_val_loss": 0.660186231136322, "initial_val_acc": 0.5, "final_val_acc": 0.6, "best_val_acc": 0.6, "best_epoch": 3}, "improvement": 0.19999999999999996, "first_improvement_epoch": 1}} |
80 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.66, "improved_accuracy": 0.94, "improvement": 0.2799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8766, "learning_rate": 0.019359730823269184, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[7.167695, 7.386398, 50.970099], [23.895064, 27.069645, 232.431464], [24.270734, 28.260334, 176.109078], [28.567080, 28.758826, 132.231943], [29.867758, 34.629309, 102.308348], [23.488290, 25.072353, 57.920550], [37.495638, 42.373409, 253.675435], [24.087320, 24.693012, 222.144564]]
### 2
fourier: [[21.526478, 21.897570, 156.635926], [9.849339, 10.034223, 17.996105], [14.469067, 16.417462, 122.517276], [23.053688, 23.412392, 102.191058], [16.122716, 17.177231, 134.287399], [8.540487, 8.631420, 35.813314], [8.349919, 8.567197, 26.754157], [22.287542, 26.795631, 208.391030]]
### 4
fourier: [[19.700271, 22.407730, 128.116144], [10.366715, 10.546926, 106.623452], [16.780510, 16.994903, 68.228220], [26.607485, 27.663880, 162.474594], [17.600305, 18.889994, 113.191726], [5.042529, 5.232926, 52.976540], [22.818272, 23.534924, 252.224552], [8.327801, 9.467097, 117.135406]]
### 6
fourier: [[19.675406, 20.632240, 174.882349], [15.183608, 15.482989, 49.508642], [10.737404, 11.205356, 29.201151], [31.444874, 34.014619, 221.348668], [15.440653, 16.042147, 182.332075], [19.591822, 19.967277, 51.238462], [3.577015, 3.789831, 67.597534], [22.561841, 23.642898, 213.009092]]
### 8
fourier: [[4.656453, 4.673826, 77.296591], [18.387194, 19.370524, 148.410572], [20.861694, 21.522183, 87.036675], [21.291363, 22.606507, 31.546135], [12.719624, 13.732686, 122.233989], [18.575659, 19.731653, 101.648562], [25.393048, 27.706361, 179.014569], [39.250958, 42.496199, 291.772822]]
### 10
fourier: [[51.666361, 52.602138, 187.066806]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
fourier: [[7.167695, 7.386398, 50.970099], [23.895064, 27.069645, 232.431464], [24.270734, 28.260334, 176.109078], [28.567080, 28.758826, 132.231943], [29.867758, 34.629309, 102.308348], [23.488290, 25.072353, 57.920550], [37.495638, 42.373409, 253.675435], [24.087320, 24.693012, 222.144564]]
### 2
fourier: [[21.526478, 21.897570, 156.635926], [9.849339, 10.034223, 17.996105], [14.469067, 16.417462, 122.517276], [23.053688, 23.412392, 102.191058], [16.122716, 17.177231, 134.287399], [8.540487, 8.631420, 35.813314], [8.349919, 8.567197, 26.754157], [22.287542, 26.795631, 208.391030]]
### 4
fourier: [[19.700271, 22.407730, 128.116144], [10.366715, 10.546926, 106.623452], [16.780510, 16.994903, 68.228220], [26.607485, 27.663880, 162.474594], [17.600305, 18.889994, 113.191726], [5.042529, 5.232926, 52.976540], [22.818272, 23.534924, 252.224552], [8.327801, 9.467097, 117.135406]]
### 6
fourier: [[19.675406, 20.632240, 174.882349], [15.183608, 15.482989, 49.508642], [10.737404, 11.205356, 29.201151], [31.444874, 34.014619, 221.348668], [15.440653, 16.042147, 182.332075], [19.591822, 19.967277, 51.238462], [3.577015, 3.789831, 67.597534], [22.561841, 23.642898, 213.009092]]
### 8
fourier: [[4.656453, 4.673826, 77.296591], [18.387194, 19.370524, 148.410572], [20.861694, 21.522183, 87.036675], [21.291363, 22.606507, 31.546135], [12.719624, 13.732686, 122.233989], [18.575659, 19.731653, 101.648562], [25.393048, 27.706361, 179.014569], [39.250958, 42.496199, 291.772822]]
### 10
fourier: [[51.666361, 52.602138, 187.066806]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [7.167694553962336, 7.386397884195399, 50.97009867429733]}, "1": {"fourier": [23.895064395416142, 27.069644568908604, 232.43146407604218]}, "2": {"fourier": [24.270734090909205, 28.26033417340834, 176.10907804965973]}, "3": {"fourier": [28.567080028914692, 28.758825839992987, 132.23194251209497]}, "4": {"fourier": [29.867758089671536, 34.62930896918903, 102.30834772437811]}, "5": {"fourier": [23.488290278901946, 25.072353055239105, 57.92055043578148]}, "6": {"fourier": [37.49563765224041, 42.373409250102945, 253.67543532140553]}, "7": {"fourier": [24.087319845459113, 24.6930119621614, 222.14456388354301]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [21.52647771940002, 21.897570481547483, 156.63592566549778]}, "1": {"fourier": [9.849339250926166, 10.034223021801509, 17.9961054995656]}, "2": {"fourier": [14.469066913155128, 16.41746233796753, 122.51727636158466]}, "3": {"fourier": [23.053687568547556, 23.412392097018742, 102.19105836749077]}, "4": {"fourier": [16.122716466049628, 17.177231421168933, 134.2873992472887]}, "5": {"fourier": [8.540486598091565, 8.631419886926679, 35.81331438943744]}, "6": {"fourier": [8.34991936032595, 8.567197038002963, 26.75415676832199]}, "7": {"fourier": [22.287542323297032, 26.79563084460076, 208.39102990925312]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [19.700270757064715, 22.40772994124839, 128.11614421382546]}, "1": {"fourier": [10.366714529837353, 10.546926444030818, 106.62345167994499]}, "2": {"fourier": [16.780509826094256, 16.99490303796499, 68.22822032123804]}, "3": {"fourier": [26.607484928934742, 27.66387952150106, 162.47459399700165]}, "4": {"fourier": [17.600305214934874, 18.889993947213878, 113.19172567129135]}, "5": {"fourier": [5.042529369937338, 5.232925734123163, 52.976540088653564]}, "6": {"fourier": [22.818272151222995, 23.534923746147825, 252.22455203533173]}, "7": {"fourier": [8.32780056128043, 9.467097042283722, 117.13540583848953]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [19.675406201808332, 20.632240365465478, 174.88234865665436]}, "1": {"fourier": [15.183608048092633, 15.482988989821157, 49.508641734719276]}, "2": {"fourier": [10.737403506276742, 11.205355634487965, 29.201151221990585]}, "3": {"fourier": [31.44487363944656, 34.0146194934517, 221.34866759181023]}, "4": {"fourier": [15.440653408462806, 16.042147186139502, 182.33207511901855]}, "5": {"fourier": [19.59182171962064, 19.967277036437803, 51.23846219480038]}, "6": {"fourier": [3.57701452562691, 3.7898312246834736, 67.59753441810608]}, "7": {"fourier": [22.56184075031622, 23.64289817706953, 213.00909161567688]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [4.656452542172072, 4.673825615442583, 77.29659116268158]}, "1": {"fourier": [18.387194344560445, 19.370523755456347, 148.41057187318802]}, "2": {"fourier": [20.86169420780822, 21.52218295536084, 87.03667476773262]}, "3": {"fourier": [21.291362941200763, 22.60650698449865, 31.546134740114212]}, "4": {"fourier": [12.719624019469096, 13.732685872301685, 122.23398938775063]}, "5": {"fourier": [18.57565924967671, 19.73165257894303, 101.64856207370758]}, "6": {"fourier": [25.393048273393447, 27.7063606236776, 179.01456852257252]}, "7": {"fourier": [39.250957530831464, 42.49619880141818, 291.77282248437405]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [51.66636110687122, 52.602138340196966, 187.06680558621883]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": 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"final_val_loss": 0.5821906328201294, "initial_val_acc": 0.6, "final_val_acc": 0.66, "best_val_acc": 0.66}, "improved_stage": {"initial_val_loss": 0.4635984003543854, "final_val_loss": 0.22363221645355225, "initial_val_acc": 0.92, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 5}, "improvement": 0.2799999999999999, "first_improvement_epoch": 1}} |
81 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.48, "improved_accuracy": 0.94, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4872, "learning_rate": 0.02525648142243843, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[16.415615, 17.893328, 59.985871], [15.404870, 22.103475, 50.258316], [22.895387, 24.060893, 27.071660], [19.688227, 19.966970, 21.688454], [21.137926, 22.708264, 133.784448], [13.966382, 16.518930, 68.006997], [26.142876, 28.355351, 158.498690]]
### 2
fourier: [[10.573080, 12.671055, 17.995494], [14.703184, 14.723491, 15.337613], [14.400054, 14.746789, 107.284264], [28.458328, 32.185857, 37.302982], [14.174998, 15.215050, 31.119467], [14.008485, 14.922963, 95.363404], [15.636432, 20.893053, 99.153417]]
### 4
fourier: [[16.421008, 17.430788, 60.651310], [3.637988, 3.672661, 47.691275], [10.648785, 10.769673, 73.848280], [2.410443, 3.026969, 47.309601], [8.322273, 8.781811, 73.025557], [29.456617, 30.032073, 31.705231], [26.367986, 26.883980, 45.224316]]
### 6
fourier: [[18.239716, 18.315519, 55.560677], [0.388568, 0.399144, 23.449236], [4.666749, 4.681820, 9.556624], [4.899737, 5.244102, 18.109105], [8.464226, 8.739265, 32.808857], [20.475955, 20.797028, 48.902397], [16.455342, 16.846149, 60.751341]]
### 8
fourier: [[0.620768, 0.623697, 13.746725], [9.739577, 9.795499, 51.434451], [4.873810, 4.890604, 25.946730], [6.235799, 6.256020, 17.441555], [2.630439, 2.644589, 5.953969], [7.057495, 7.092763, 19.602301], [0.851666, 0.857183, 15.889361]]
### 10
fourier: [[5.648387, 5.775723, 14.699707]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
-0.252161,
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0.104157,
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0.147822,
-0.095112,
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],
[
0.065847,
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-0.477832,
0.103805,
0.1115,
-0.124606,
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],
[
-0.012389,
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0.077189,
0.252307,
0.060049,
-0.349514,
0.315913
],
[
-0.367823,
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0.117453,
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0.275297,
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]
],
"network.8.bias": [
-0.163831,
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0.423011,
0.39682,
0.132556,
-0.013743,
-0.117244
],
"network.10.weight": [
[
-0.225824,
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],
"network.10.bias": [
-0.140124
]
}
## Activation Signature
### 0
fourier: [[16.415615, 17.893328, 59.985871], [15.404870, 22.103475, 50.258316], [22.895387, 24.060893, 27.071660], [19.688227, 19.966970, 21.688454], [21.137926, 22.708264, 133.784448], [13.966382, 16.518930, 68.006997], [26.142876, 28.355351, 158.498690]]
### 2
fourier: [[10.573080, 12.671055, 17.995494], [14.703184, 14.723491, 15.337613], [14.400054, 14.746789, 107.284264], [28.458328, 32.185857, 37.302982], [14.174998, 15.215050, 31.119467], [14.008485, 14.922963, 95.363404], [15.636432, 20.893053, 99.153417]]
### 4
fourier: [[16.421008, 17.430788, 60.651310], [3.637988, 3.672661, 47.691275], [10.648785, 10.769673, 73.848280], [2.410443, 3.026969, 47.309601], [8.322273, 8.781811, 73.025557], [29.456617, 30.032073, 31.705231], [26.367986, 26.883980, 45.224316]]
### 6
fourier: [[18.239716, 18.315519, 55.560677], [0.388568, 0.399144, 23.449236], [4.666749, 4.681820, 9.556624], [4.899737, 5.244102, 18.109105], [8.464226, 8.739265, 32.808857], [20.475955, 20.797028, 48.902397], [16.455342, 16.846149, 60.751341]]
### 8
fourier: [[0.620768, 0.623697, 13.746725], [9.739577, 9.795499, 51.434451], [4.873810, 4.890604, 25.946730], [6.235799, 6.256020, 17.441555], [2.630439, 2.644589, 5.953969], [7.057495, 7.092763, 19.602301], [0.851666, 0.857183, 15.889361]]
### 10
fourier: [[5.648387, 5.775723, 14.699707]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [16.41561485785039, 17.8933284915055, 59.98587101697922]}, "1": {"fourier": [15.404869515701382, 22.103475190721678, 50.25831559300423]}, "2": {"fourier": [22.89538740416383, 24.060893301334232, 27.071660153049653]}, "3": {"fourier": [19.688227017203626, 19.9669703262319, 21.688454419374466]}, "4": {"fourier": [21.137925841095164, 22.708264330345134, 133.78444819152355]}, "5": {"fourier": [13.966381924996428, 16.51892963054244, 68.00699734687805]}, "6": {"fourier": [26.142875802082127, 28.355351103705456, 158.49868999421597]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [10.573080294026484, 12.671055339150685, 17.995493821799755]}, "1": {"fourier": [14.703183773467643, 14.723491107579477, 15.337612869742925]}, "2": {"fourier": [14.4000544812276, 14.746789428889164, 107.2842635512352]}, "3": {"fourier": [28.458328140087257, 32.18585661797027, 37.30298247560859]}, "4": {"fourier": [14.17499753408023, 15.215049674824138, 31.11946664750576]}, "5": {"fourier": [14.008484554796572, 14.922963117229008, 95.3634038567543]}, "6": {"fourier": [15.636432400588495, 20.893053282882963, 99.15341673512012]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [16.421007546105752, 17.43078764624427, 60.651310443878174]}, "1": {"fourier": [3.6379877655552977, 3.672661236968402, 47.69127507507801]}, "2": {"fourier": [10.64878502709919, 10.769672614877935, 73.8482800424099]}, "3": {"fourier": [2.410443376300696, 3.02696905271487, 47.30960072577]}, "4": {"fourier": [8.322273103372199, 8.78181119966224, 73.02555724978447]}, "5": {"fourier": [29.456616615239202, 30.032072789701996, 31.705231222942164]}, "6": {"fourier": [26.367985528330017, 26.883979504725293, 45.224316477775574]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [18.239716279879687, 18.31551853584361, 55.56067682802677]}, "1": {"fourier": [0.3885676177919046, 0.39914427507211164, 23.44923624396324]}, "2": {"fourier": [4.666749446967154, 4.681820253074266, 9.556623980402946]}, "3": {"fourier": [4.899737259972957, 5.24410225400662, 18.10910484753549]}, "4": {"fourier": [8.464226277281297, 8.739264620443118, 32.808856539428234]}, "5": {"fourier": [20.47595488565543, 20.79702803125088, 48.902397103607655]}, "6": {"fourier": [16.45534194534161, 16.846148731209656, 60.75134143233299]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [0.6207678092173653, 0.6236973322120889, 13.746724762022495]}, "1": {"fourier": [9.739577440010356, 9.79549905996135, 51.43445071578026]}, "2": {"fourier": [4.873809872042753, 4.890604129397491, 25.946729719638824]}, "3": {"fourier": [6.235798952157105, 6.256020113102333, 17.441555231809616]}, "4": {"fourier": [2.630438895999797, 2.6445889852602975, 5.953969478607178]}, "5": {"fourier": [7.057495338371706, 7.092763176202558, 19.60230133961886]}, "6": {"fourier": [0.851666293215639, 0.8571830671042097, 15.889360591769218]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [5.6483874260841445, 5.775722877080886, 14.699706800282001]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.057245, 0.181081, -0.233506, 0.103555, -0.24977], [-0.182069, -0.335004, 0.381102, 0.178364, -0.213024], [-0.070077, 0.392177, 0.40201, -0.294606, -0.47571], [-0.496502, 0.199676, 0.535571, -0.155402, 0.023498], [0.270919, 0.191684, 0.385088, 0.014124, -0.221738], [-0.383218, 0.208574, 0.042681, -0.000581, 0.206156], [0.433832, 0.323621, 0.27269, 0.001058, 0.079695]], "network.0.bias": [-0.351491, 0.479611, -0.221763, -0.31948, 0.238842, 0.510289, -0.038671], "network.2.weight": [[0.283271, 0.281626, 0.125768, -0.227901, -0.248851, 0.404367, -0.160811], [-0.046431, -0.157517, 0.408225, -0.429657, 0.133136, -0.463199, 0.19982], [-0.069891, -0.294072, -0.372371, -0.390551, 0.227954, -0.021381, -0.26342], [-0.192746, -0.592404, -0.277073, -0.250981, 0.39146, -0.570204, 0.614497], [-0.439092, -0.215435, 0.41556, -0.511808, 0.319691, -0.315802, 0.071557], [-0.134836, 0.596295, 0.29274, -0.095247, 0.056457, 0.566035, -0.264385], [-0.200046, 0.033217, -0.343852, -0.433646, 0.011646, 0.027781, -0.391064]], "network.2.bias": [-0.030818, 0.089256, -0.416846, -0.062406, 0.247299, 0.452645, -0.025733], "network.4.weight": [[-0.224331, 0.213619, -0.002026, 0.502516, 0.139374, 0.068459, -0.022983], [0.22677, 0.137752, 0.230275, -0.269484, 0.107779, -0.469237, 0.215905], [-0.042065, -0.195649, 0.250186, -0.339249, -0.061717, -0.101827, -0.373232], [-0.145123, -0.340604, 0.200814, 0.085902, 0.037366, -0.249926, 0.135629], [-0.269393, 0.061076, -0.098111, -0.259155, -0.371985, -0.202141, -0.367364], [-0.345633, 0.349163, 0.016072, 0.585732, 0.414306, -0.537553, -0.36104], [0.191797, 0.332961, 0.08835, 0.563837, 0.401388, -0.336749, 0.213665]], "network.4.bias": [0.111225, 0.057956, -0.347763, -0.192256, -0.206531, 0.145532, 0.115527], "network.6.weight": [[-0.082354, 0.262412, 0.194474, 0.124175, 0.281649, 0.538527, 0.233968], [0.118328, -0.315703, -0.212921, -0.069151, 0.281509, -0.221686, 0.163496], [-0.032357, -0.140902, -0.298385, -0.063347, 0.144932, 0.168093, 0.03584], [-0.407536, -0.165092, -0.006736, -0.251448, -0.356808, 0.293756, -0.232993], [-0.295415, 0.193163, 0.274517, -0.031863, 0.026075, 0.138017, -0.290105], [0.237077, 0.092172, -0.227036, 0.199866, 0.146154, 0.220224, 0.443177], [-0.327229, -0.036653, 0.020781, -0.376689, 0.280247, -0.17599, -0.266174]], "network.6.bias": [0.112615, -0.294612, -0.232772, 0.024536, -0.05985, -0.092864, -0.136369], "network.8.weight": [[0.244656, -0.363902, -0.386532, 0.297713, 0.373433, -0.193076, 0.038723], [0.190386, 0.301581, 0.04938, -0.220108, -0.224707, 0.304657, -0.233145], [0.062024, -0.25017, 0.167204, -0.278817, 0.2177, -0.320429, 0.257154], [-0.252161, 0.104512, 0.104157, 0.068137, 0.147822, -0.095112, 0.168381], [0.065847, 0.315964, -0.477832, 0.103805, 0.1115, -0.124606, 0.187455], [-0.012389, -0.276822, 0.077189, 0.252307, 0.060049, -0.349514, 0.315913], [-0.367823, -0.357801, 0.117453, 0.113688, 0.322733, 0.275297, 0.24048]], "network.8.bias": [-0.163831, 0.274209, 0.423011, 0.39682, 0.132556, -0.013743, -0.117244], "network.10.weight": [[-0.225824, 0.348167, -0.331092, -0.338331, -0.168754, -0.012067, -0.266177]], "network.10.bias": [-0.140124]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6909658908843994, "train_acc": 0.57, "val_loss": 0.713081955909729, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6795890629291534, "train_acc": 0.57, "val_loss": 0.7016735076904297, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6725043654441833, "train_acc": 0.57, "val_loss": 0.686604917049408, "val_acc": 0.48}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6601284444332123, "train_acc": 0.57, "val_loss": 0.6668938994407654, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6446345150470734, "train_acc": 0.6, "val_loss": 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"improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.269192636013031, "train_acc": 0.93, "val_loss": 0.30151739716529846, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.2334907278418541, "train_acc": 0.92, "val_loss": 0.2808191776275635, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.20312854647636414, "train_acc": 0.93, "val_loss": 0.29062893986701965, "val_acc": 0.9}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.713081955909729, "final_val_loss": 0.6668938994407654, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6207842230796814, "final_val_loss": 0.29062893986701965, "initial_val_acc": 0.9, "final_val_acc": 0.9, "best_val_acc": 0.94, "best_epoch": 5}, "improvement": 0.45999999999999996, "first_improvement_epoch": 3}} |
82 | {"target_pattern": "starts_with", "degraded_accuracy": 0.44, "improved_accuracy": 0.76, "improvement": 0.32, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7384, "learning_rate": 0.0908679592276421, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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-0.041303,
0.362801,
0.445089,
-0.507222
]
],
"network.12.bias": [
-0.051932
]
}
## Activation Signature
### 0
fourier: [[40.930357, 47.033922, 296.698029], [47.722342, 51.744016, 161.095752], [44.840063, 46.624886, 340.531033], [66.151888, 74.340416, 402.473256], [50.569206, 50.991059, 328.482657]]
### 2
fourier: [[24.623830, 26.861477, 62.613865], [22.610154, 23.236121, 23.653712], [53.888132, 59.092482, 279.803888], [23.623423, 25.191013, 99.615425], [46.607073, 46.899487, 224.368306]]
### 4
fourier: [[1.528040, 1.603959, 81.582370], [27.013290, 27.603511, 111.674479], [43.797991, 45.663829, 154.567378], [5.260891, 5.996269, 51.251119], [5.816822, 6.060146, 51.692467]]
### 6
fourier: [[34.085154, 34.909141, 88.297563], [6.434218, 6.487992, 37.239030], [32.377808, 32.392057, 34.886618], [18.752356, 18.883993, 114.157012], [16.195705, 17.633025, 46.660018]]
### 8
fourier: [[6.990471, 7.356746, 96.403707], [44.515822, 45.765563, 48.228208], [17.852641, 19.231506, 23.785488], [46.314114, 47.461927, 49.532842], [13.056803, 13.169667, 103.169867]]
### 10
fourier: [[27.289094, 27.699593, 95.012121], [25.386084, 25.571195, 70.519092], [17.162888, 17.798943, 18.205049], [27.531467, 28.535000, 43.634154], [73.505335, 74.573024, 127.175261]]
### 12
fourier: [[36.752690, 37.558054, 78.981036]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.042772,
-0.396263,
-0.127488,
-0.243888,
-0.959034
],
[
1.192559,
0.403172,
-0.00378,
-0.062649,
-0.367185
],
[
-0.010326,
-0.173526,
-0.488032,
-0.534963,
-0.824603
],
[
1.166616,
0.632752,
0.015703,
0.918526,
-0.257575
],
[
-0.337991,
-0.224007,
-0.751629,
-0.098387,
-0.638115
]
],
"network.0.bias": [
-0.655674,
0.166314,
-0.270971,
0.182269,
-0.252943
],
"network.2.weight": [
[
-0.562999,
-0.426609,
-0.715567,
-0.106212,
-0.050975
],
[
0.286009,
-0.683698,
0.272795,
0.195189,
0.215162
],
[
-0.31708,
0.946335,
-0.382607,
0.278158,
-0.753277
],
[
-0.202278,
-0.131217,
-0.05126,
-0.275608,
-0.029244
],
[
-0.271145,
-0.533452,
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-0.373012,
-0.020022
]
],
"network.2.bias": [
0.517432,
0.395809,
0.069989,
0.347332,
0.128736
],
"network.4.weight": [
[
-0.271657,
-0.059418,
0.007563,
-0.025284,
-0.24338
],
[
-0.695389,
-0.54387,
-0.500452,
0.358574,
0.602079
],
[
1.14711,
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0.762671,
0.613522,
0.469
],
[
-0.296292,
0.413236,
-0.034402,
-0.469121,
-0.292306
],
[
0.756185,
-0.218937,
-0.052247,
0.42185,
-0.006582
]
],
"network.4.bias": [
0.917342,
0.572788,
-0.488113,
0.522174,
-0.386306
],
"network.6.weight": [
[
-0.535614,
0.868556,
0.788846,
0.325425,
0.032769
],
[
-0.331822,
0.413596,
0.158843,
0.272116,
0.354569
],
[
-1.166486,
0.071305,
0.717225,
-0.581689,
-0.088803
],
[
-0.143931,
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-0.101321,
0.989801
],
[
0.149259,
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-0.301671,
0.678403,
-0.667084
]
],
"network.6.bias": [
-0.04734,
-0.484946,
-0.100612,
-0.323777,
0.519056
],
"network.8.weight": [
[
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-0.006474,
-0.123611,
-0.382184
],
[
0.876829,
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0.317547,
0.451966,
-1.042784
],
[
-0.115178,
0.069182,
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0.700604
],
[
0.461116,
0.486926,
0.892263,
0.170487,
-1.055866
],
[
-0.566696,
0.179081,
0.171256,
0.160322,
-0.099524
]
],
"network.8.bias": [
-0.45174,
-0.083475,
0.09008,
0.121488,
-0.56504
],
"network.10.weight": [
[
-0.304585,
-0.315395,
-0.131866,
-0.36448,
-0.279899
],
[
-0.459569,
-0.193607,
0.106286,
-0.410738,
0.007502
],
[
-0.604623,
0.185087,
0.584251,
-0.500761,
-0.465425
],
[
-0.426881,
-0.639005,
-0.457532,
-0.102631,
-0.274856
],
[
0.18956,
0.718141,
-0.636756,
1.017843,
0.416527
]
],
"network.10.bias": [
-0.345825,
-0.245496,
-0.186914,
0.413322,
-0.079338
],
"network.12.weight": [
[
-0.023131,
-0.041303,
0.362801,
0.445089,
-0.507222
]
],
"network.12.bias": [
-0.051932
]
}
## Activation Signature
### 0
fourier: [[40.930357, 47.033922, 296.698029], [47.722342, 51.744016, 161.095752], [44.840063, 46.624886, 340.531033], [66.151888, 74.340416, 402.473256], [50.569206, 50.991059, 328.482657]]
### 2
fourier: [[24.623830, 26.861477, 62.613865], [22.610154, 23.236121, 23.653712], [53.888132, 59.092482, 279.803888], [23.623423, 25.191013, 99.615425], [46.607073, 46.899487, 224.368306]]
### 4
fourier: [[1.528040, 1.603959, 81.582370], [27.013290, 27.603511, 111.674479], [43.797991, 45.663829, 154.567378], [5.260891, 5.996269, 51.251119], [5.816822, 6.060146, 51.692467]]
### 6
fourier: [[34.085154, 34.909141, 88.297563], [6.434218, 6.487992, 37.239030], [32.377808, 32.392057, 34.886618], [18.752356, 18.883993, 114.157012], [16.195705, 17.633025, 46.660018]]
### 8
fourier: [[6.990471, 7.356746, 96.403707], [44.515822, 45.765563, 48.228208], [17.852641, 19.231506, 23.785488], [46.314114, 47.461927, 49.532842], [13.056803, 13.169667, 103.169867]]
### 10
fourier: [[27.289094, 27.699593, 95.012121], [25.386084, 25.571195, 70.519092], [17.162888, 17.798943, 18.205049], [27.531467, 28.535000, 43.634154], [73.505335, 74.573024, 127.175261]]
### 12
fourier: [[36.752690, 37.558054, 78.981036]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [40.930357460722874, 47.033922342605486, 296.6980292201042]}, "1": {"fourier": [47.72234181156981, 51.74401576827868, 161.09575210511684]}, "2": {"fourier": [44.8400632415838, 46.62488550742248, 340.5310327410698]}, "3": {"fourier": [66.15188754676859, 74.34041595627444, 402.4732564985752]}, "4": {"fourier": [50.5692064314239, 50.99105934387846, 328.48265716433525]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [24.623829915477188, 26.861477211498475, 62.613865196704865]}, "1": {"fourier": [22.610153620937968, 23.236121306852382, 23.653711748151256]}, "2": {"fourier": [53.888132223339326, 59.09248177243025, 279.80388797447085]}, "3": {"fourier": [23.623422859777055, 25.191012797273434, 99.61542500555515]}, "4": {"fourier": [46.60707273246791, 46.899486593347966, 224.36830576509237]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [1.5280403064446715, 1.6039591859027356, 81.58236992359161]}, "1": {"fourier": [27.013290063577884, 27.603510748316584, 111.67447862029076]}, "2": {"fourier": [43.79799095501902, 45.663828623813224, 154.56737841665745]}, "3": {"fourier": [5.2608905444661085, 5.996269264744034, 51.25111925601959]}, "4": {"fourier": [5.816821774950716, 6.060146127488219, 51.692467108368874]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [34.08515351369434, 34.90914148680865, 88.29756296798587]}, "1": {"fourier": [6.434218097720885, 6.48799179664069, 37.23903024196625]}, "2": {"fourier": [32.37780846977685, 32.39205749837105, 34.88661762152475]}, "3": {"fourier": [18.752355782108943, 18.883993468790116, 114.15701228380203]}, "4": {"fourier": [16.19570463102522, 17.63302483650004, 46.66001841425896]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [6.990470760138559, 7.356745557807449, 96.40370744466782]}, "1": {"fourier": [44.51582234951678, 45.765563090413224, 48.22820785216546]}, "2": {"fourier": [17.85264082229788, 19.231505973500433, 23.785488419234753]}, "3": {"fourier": [46.3141144029768, 47.46192694537485, 49.53284203490716]}, "4": {"fourier": [13.056802647925302, 13.169667489726, 103.16986739635468]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [27.289093725636206, 27.69959310978198, 95.01212134957314]}, "1": {"fourier": [25.386084094162456, 25.571195444927984, 70.51909191906452]}, "2": {"fourier": [17.16288758153758, 17.79894337986075, 18.20504934565532]}, "3": {"fourier": [27.531466505598864, 28.53499952282827, 43.63415428996086]}, "4": {"fourier": [73.50533529972823, 74.57302375976906, 127.17526107281446]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [36.75269017827058, 37.55805368440209, 78.98103639110923]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.042772, -0.396263, -0.127488, -0.243888, -0.959034], [1.192559, 0.403172, -0.00378, -0.062649, -0.367185], [-0.010326, -0.173526, -0.488032, -0.534963, -0.824603], [1.166616, 0.632752, 0.015703, 0.918526, -0.257575], [-0.337991, -0.224007, -0.751629, -0.098387, -0.638115]], "network.0.bias": [-0.655674, 0.166314, -0.270971, 0.182269, -0.252943], "network.2.weight": [[-0.562999, -0.426609, -0.715567, -0.106212, -0.050975], [0.286009, -0.683698, 0.272795, 0.195189, 0.215162], [-0.31708, 0.946335, -0.382607, 0.278158, -0.753277], [-0.202278, -0.131217, -0.05126, -0.275608, -0.029244], [-0.271145, -0.533452, -0.273964, -0.373012, -0.020022]], "network.2.bias": [0.517432, 0.395809, 0.069989, 0.347332, 0.128736], "network.4.weight": [[-0.271657, -0.059418, 0.007563, -0.025284, -0.24338], [-0.695389, -0.54387, -0.500452, 0.358574, 0.602079], [1.14711, -0.471728, 0.762671, 0.613522, 0.469], [-0.296292, 0.413236, -0.034402, -0.469121, -0.292306], [0.756185, -0.218937, -0.052247, 0.42185, -0.006582]], "network.4.bias": [0.917342, 0.572788, -0.488113, 0.522174, -0.386306], "network.6.weight": [[-0.535614, 0.868556, 0.788846, 0.325425, 0.032769], [-0.331822, 0.413596, 0.158843, 0.272116, 0.354569], [-1.166486, 0.071305, 0.717225, -0.581689, -0.088803], [-0.143931, -0.655215, -0.413067, -0.101321, 0.989801], [0.149259, -0.370201, -0.301671, 0.678403, -0.667084]], "network.6.bias": [-0.04734, -0.484946, -0.100612, -0.323777, 0.519056], "network.8.weight": [[-0.318337, 0.694411, -0.006474, -0.123611, -0.382184], [0.876829, 0.131489, 0.317547, 0.451966, -1.042784], [-0.115178, 0.069182, -0.319119, -0.700167, 0.700604], [0.461116, 0.486926, 0.892263, 0.170487, -1.055866], [-0.566696, 0.179081, 0.171256, 0.160322, -0.099524]], "network.8.bias": [-0.45174, -0.083475, 0.09008, 0.121488, -0.56504], "network.10.weight": [[-0.304585, -0.315395, -0.131866, -0.36448, -0.279899], [-0.459569, -0.193607, 0.106286, -0.410738, 0.007502], [-0.604623, 0.185087, 0.584251, -0.500761, -0.465425], [-0.426881, -0.639005, -0.457532, -0.102631, -0.274856], [0.18956, 0.718141, -0.636756, 1.017843, 0.416527]], "network.10.bias": [-0.345825, -0.245496, -0.186914, 0.413322, -0.079338], "network.12.weight": [[-0.023131, -0.041303, 0.362801, 0.445089, -0.507222]], "network.12.bias": [-0.051932]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6908726394176483, "train_acc": 0.445, "val_loss": 0.7261789441108704, "val_acc": 0.44}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6669046580791473, "train_acc": 0.595, "val_loss": 0.7484025359153748, "val_acc": 0.44}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.674164891242981, "train_acc": 0.595, "val_loss": 0.765255331993103, "val_acc": 0.44}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6566388010978699, "train_acc": 0.595, "val_loss": 0.7032978534698486, "val_acc": 0.44}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.5907982289791107, "train_acc": 0.595, "val_loss": 0.5811001062393188, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6100955903530121, "train_acc": 0.565, "val_loss": 0.5563254356384277, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5857534408569336, "train_acc": 0.655, "val_loss": 0.6482921838760376, "val_acc": 0.6}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6180942356586456, "train_acc": 0.6, "val_loss": 0.6227204203605652, "val_acc": 0.6}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5956705212593079, "train_acc": 0.64, "val_loss": 0.585711658000946, "val_acc": 0.72}], "summary": {"total_epochs": 9, "degraded_epochs": 5, "improved_epochs": 4, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.7261789441108704, "final_val_loss": 0.5811001062393188, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.5563254356384277, "final_val_loss": 0.585711658000946, "initial_val_acc": 0.76, "final_val_acc": 0.72, "best_val_acc": 0.76, "best_epoch": 5}, "improvement": 0.32, "first_improvement_epoch": 4}} |
83 | {"target_pattern": "vowel_consonant", "degraded_accuracy": 0.48, "improved_accuracy": 0.68, "improvement": 0.20000000000000007, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 6718, "learning_rate": 0.09314226785800217, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "vowel_consonant", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["vowel_consonant"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.132039
],
[
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0.057445
],
[
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0.28302
],
[
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[
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],
[
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],
[
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],
"network.0.bias": [
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}
## Activation Signature
### 0
fourier: [[45.014332, 50.355565, 57.174718], [20.593105, 21.800907, 166.220410], [49.328302, 50.020721, 59.954559], [19.902408, 22.385994, 163.535870], [63.895145, 68.956389, 80.384608], [33.595091, 40.629203, 293.834712], [52.122101, 54.021662, 101.496732]]
### 2
fourier: [[60.092220, 64.499320, 69.224793], [34.179930, 39.784669, 143.600821], [21.409353, 24.122570, 220.536648], [17.156061, 18.215385, 140.292299], [18.408621, 23.401438, 188.721589], [35.249056, 44.403388, 229.910843], [59.535740, 65.691418, 87.066988]]
### 4
fourier: [[45.021414, 48.425830, 91.132566], [46.740257, 57.801583, 286.910868], [66.716493, 71.810740, 160.839506], [49.081030, 61.422371, 63.352249], [24.724752, 25.973045, 60.073059], [58.542357, 66.979107, 295.889857], [54.263613, 62.465180, 263.976931]]
### 6
fourier: [[24.278299, 27.120970, 104.276395], [28.520729, 30.669620, 86.306993], [5.355716, 6.167983, 56.770255], [43.126565, 46.524414, 79.707042], [66.611554, 71.020574, 135.930430], [24.194108, 24.545659, 78.184544], [25.449285, 31.694354, 118.487954]]
### 8
fourier: [[50.665538, 56.805613, 127.126453]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| vowel_consonant | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[45.014332, 50.355565, 57.174718], [20.593105, 21.800907, 166.220410], [49.328302, 50.020721, 59.954559], [19.902408, 22.385994, 163.535870], [63.895145, 68.956389, 80.384608], [33.595091, 40.629203, 293.834712], [52.122101, 54.021662, 101.496732]]
### 2
fourier: [[60.092220, 64.499320, 69.224793], [34.179930, 39.784669, 143.600821], [21.409353, 24.122570, 220.536648], [17.156061, 18.215385, 140.292299], [18.408621, 23.401438, 188.721589], [35.249056, 44.403388, 229.910843], [59.535740, 65.691418, 87.066988]]
### 4
fourier: [[45.021414, 48.425830, 91.132566], [46.740257, 57.801583, 286.910868], [66.716493, 71.810740, 160.839506], [49.081030, 61.422371, 63.352249], [24.724752, 25.973045, 60.073059], [58.542357, 66.979107, 295.889857], [54.263613, 62.465180, 263.976931]]
### 6
fourier: [[24.278299, 27.120970, 104.276395], [28.520729, 30.669620, 86.306993], [5.355716, 6.167983, 56.770255], [43.126565, 46.524414, 79.707042], [66.611554, 71.020574, 135.930430], [24.194108, 24.545659, 78.184544], [25.449285, 31.694354, 118.487954]]
### 8
fourier: [[50.665538, 56.805613, 127.126453]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
vowel_consonant | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [45.014331922417384, 50.35556517128543, 57.174717837831196]}, "1": {"fourier": [20.593104736950274, 21.8009072282854, 166.2204096466303]}, "2": {"fourier": [49.32830219790268, 50.02072054138426, 59.954558786796525]}, "3": {"fourier": [19.90240769618488, 22.3859944339035, 163.53587001562119]}, "4": {"fourier": [63.895144717880314, 68.95638901304459, 80.38460750373139]}, "5": {"fourier": [33.59509100412815, 40.629203111443886, 293.83471221104264]}, "6": {"fourier": [52.122101483678506, 54.021661730969775, 101.49673196673393]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [60.09222021458336, 64.49932047168619, 69.22479259967804]}, "1": {"fourier": [34.17992961309572, 39.784668759977194, 143.60082136280835]}, "2": {"fourier": [21.40935333542368, 24.122569797813117, 220.53664761781693]}, "3": {"fourier": [17.1560612895561, 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"profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [24.27829921638952, 27.12097049504725, 104.27639496326447]}, "1": {"fourier": [28.5207288080001, 30.66961970454872, 86.30699263513088]}, "2": {"fourier": [5.3557164223501506, 6.167983444556114, 56.77025485038757]}, "3": {"fourier": [43.12656527234765, 46.52441411771766, 79.70704212784767]}, "4": {"fourier": [66.61155436922817, 71.02057439805886, 135.9304300621152]}, "5": {"fourier": [24.194107975904345, 24.54565881411496, 78.1845438182354]}, "6": {"fourier": [25.449284596687058, 31.694354294442793, 118.48795408010483]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [50.66553828116873, 56.80561330620317, 127.12645304203033]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.949488, -0.203868, 0.21608, -0.891651, 0.132039], [-0.12229, -0.391555, -0.301046, -0.055779, 0.057445], [0.894853, -0.424229, 0.372536, -0.871577, 0.28302], [-0.086742, -0.418113, -0.284585, 0.026757, -0.037946], [-1.809489, 0.297501, 0.410186, 0.497158, 0.137931], [-0.313835, -0.216116, -0.690456, -0.417006, -0.068512], [0.395034, 0.602207, -0.885994, 0.803327, 0.155713]], "network.0.bias": [0.342984, -0.303593, 0.72035, -0.363339, -0.085337, -0.059437, -0.525205], "network.2.weight": [[0.657103, 0.172184, 0.704511, -0.235204, -0.418883, -0.05144, -0.33135], [-0.030672, 0.042087, -0.300148, 0.024109, 0.518413, 0.357003, 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0.5809550285339355, "val_acc": 0.66}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.603607714176178, "train_acc": 0.63, "val_loss": 0.5852271914482117, "val_acc": 0.66}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.5888582468032837, "train_acc": 0.635, "val_loss": 0.5703359246253967, "val_acc": 0.66}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.6106740534305573, "train_acc": 0.65, "val_loss": 0.5776264667510986, "val_acc": 0.64}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.576578825712204, "train_acc": 0.655, "val_loss": 0.5694528818130493, "val_acc": 0.64}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.5728945732116699, "train_acc": 0.66, "val_loss": 0.5677769184112549, "val_acc": 0.68}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["vowel_consonant"], "degraded_stage": {"initial_val_loss": 0.9656438231468201, "final_val_loss": 0.6909915208816528, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6650679707527161, "final_val_loss": 0.5677769184112549, "initial_val_acc": 0.66, "final_val_acc": 0.68, "best_val_acc": 0.68, "best_epoch": 11}, "improvement": 0.20000000000000007, "first_improvement_epoch": 1}} |
84 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.46, "improved_accuracy": 0.92, "improvement": 0.46, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6959, "learning_rate": 0.022836103578526626, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[21.001775, 21.171475, 140.497295], [29.245454, 34.015877, 44.802497], [27.398792, 32.509688, 145.125291], [14.090885, 14.272225, 36.054180], [31.465826, 35.898166, 110.634543], [32.776354, 38.966118, 198.101018]]
### 2
fourier: [[21.687868, 25.636868, 26.965329], [19.666415, 20.512684, 118.778027], [15.078990, 18.379137, 84.010068], [16.386961, 20.003722, 45.871205], [18.187297, 22.129559, 155.094675], [37.720629, 43.786315, 169.217280]]
### 4
fourier: [[9.257611, 9.562932, 35.771623], [24.959182, 30.489559, 145.703551], [20.110696, 23.293492, 93.303290], [24.803337, 27.101046, 30.514642], [11.274433, 11.334319, 83.637344], [8.057754, 8.803634, 75.509132]]
### 6
fourier: [[11.039881, 11.246348, 11.996665], [13.623379, 16.914909, 82.901479], [12.179391, 12.944120, 51.543323], [17.011462, 20.675985, 142.750441], [7.022000, 7.630866, 8.603829], [19.686633, 19.955372, 23.979714]]
### 8
fourier: [[6.554675, 7.287683, 36.753486], [16.302142, 16.495567, 19.267247], [19.256548, 21.677617, 78.043583], [20.490012, 20.555246, 23.432629], [17.373515, 19.532249, 22.336547], [14.377089, 16.717703, 35.448440]]
### 10
fourier: [[21.494553, 23.902828, 50.736028], [22.628336, 24.182509, 30.158268], [17.260383, 18.831776, 58.393387], [22.646205, 23.175982, 52.124830], [26.565375, 29.064112, 35.880021], [16.565288, 17.963763, 62.733059]]
### 12
fourier: [[26.331439, 26.560762, 74.706996]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
"network.8.bias": [
-0.308483,
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0.030694
],
"network.10.weight": [
[
0.186969,
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],
[
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[
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],
"network.10.bias": [
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[
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],
"network.12.bias": [
-0.559859
]
}
## Activation Signature
### 0
fourier: [[21.001775, 21.171475, 140.497295], [29.245454, 34.015877, 44.802497], [27.398792, 32.509688, 145.125291], [14.090885, 14.272225, 36.054180], [31.465826, 35.898166, 110.634543], [32.776354, 38.966118, 198.101018]]
### 2
fourier: [[21.687868, 25.636868, 26.965329], [19.666415, 20.512684, 118.778027], [15.078990, 18.379137, 84.010068], [16.386961, 20.003722, 45.871205], [18.187297, 22.129559, 155.094675], [37.720629, 43.786315, 169.217280]]
### 4
fourier: [[9.257611, 9.562932, 35.771623], [24.959182, 30.489559, 145.703551], [20.110696, 23.293492, 93.303290], [24.803337, 27.101046, 30.514642], [11.274433, 11.334319, 83.637344], [8.057754, 8.803634, 75.509132]]
### 6
fourier: [[11.039881, 11.246348, 11.996665], [13.623379, 16.914909, 82.901479], [12.179391, 12.944120, 51.543323], [17.011462, 20.675985, 142.750441], [7.022000, 7.630866, 8.603829], [19.686633, 19.955372, 23.979714]]
### 8
fourier: [[6.554675, 7.287683, 36.753486], [16.302142, 16.495567, 19.267247], [19.256548, 21.677617, 78.043583], [20.490012, 20.555246, 23.432629], [17.373515, 19.532249, 22.336547], [14.377089, 16.717703, 35.448440]]
### 10
fourier: [[21.494553, 23.902828, 50.736028], [22.628336, 24.182509, 30.158268], [17.260383, 18.831776, 58.393387], [22.646205, 23.175982, 52.124830], [26.565375, 29.064112, 35.880021], [16.565288, 17.963763, 62.733059]]
### 12
fourier: [[26.331439, 26.560762, 74.706996]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.001775384767306, 21.171474809073523, 140.49729530513287]}, "1": {"fourier": [29.245453582189597, 34.01587661240391, 44.80249726772308]}, "2": {"fourier": [27.398791942526607, 32.5096877993676, 145.1252908706665]}, "3": {"fourier": [14.090885444750908, 14.272225447158252, 36.054180175065994]}, "4": {"fourier": [31.46582553477378, 35.89816635984367, 110.6345431804657]}, "5": {"fourier": [32.77635381544837, 38.96611787236597, 198.1010177731514]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [21.687867588225085, 25.636867668778617, 26.96532929258486]}, "1": {"fourier": [19.666415310155102, 20.512684165127283, 118.77802692353725]}, "2": {"fourier": [15.07898990221188, 18.379137193554985, 84.01006837561727]}, "3": {"fourier": [16.386960501684595, 20.003721596026523, 45.871204756200314]}, "4": {"fourier": [18.187297316568777, 22.12955935839543, 155.0946746468544]}, "5": {"fourier": [37.72062883693698, 43.78631468431545, 169.2172795534134]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [9.25761135298041, 9.562932262552447, 35.7716225925833]}, "1": {"fourier": [24.959181859469652, 30.489558724931044, 145.70355065912008]}, "2": {"fourier": [20.110695538956755, 23.293492345025175, 93.30328959226608]}, "3": {"fourier": [24.803336884333785, 27.101045512197576, 30.514641554969995]}, "4": {"fourier": [11.27443254343451, 11.334318738490712, 83.63734409213066]}, "5": {"fourier": [8.057754222879732, 8.80363413507639, 75.50913217663765]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [11.039880545965465, 11.246348122850032, 11.99666467604536]}, "1": {"fourier": [13.623378790214545, 16.91490880486459, 82.9014792740345]}, "2": {"fourier": [12.179391477468263, 12.944120339702874, 51.5433231331408]}, "3": {"fourier": [17.011461970951615, 20.67598477457978, 142.75044113397598]}, "4": {"fourier": [7.021999867076507, 7.630866080522537, 8.603829107516903]}, "5": {"fourier": [19.686633463121364, 19.95537183470696, 23.979714332554448]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [6.554675311001197, 7.2876833992033525, 36.753486052155495]}, "1": {"fourier": [16.30214173782495, 16.495567419457274, 19.267246732246807]}, "2": {"fourier": [19.256548417259676, 21.677617414280757, 78.04358297586441]}, "3": {"fourier": [20.49001229800262, 20.555245999772197, 23.432629033143183]}, "4": {"fourier": [17.37351505865517, 19.532249428078917, 22.336546808481216]}, "5": {"fourier": [14.377089302172784, 16.717702865402494, 35.4484404604882]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [21.49455280856905, 23.902827727352747, 50.73602794483304]}, "1": {"fourier": [22.628335918476324, 24.18250920115875, 30.158267963677645]}, "2": {"fourier": [17.260383305577484, 18.83177551779843, 58.39338709041476]}, "3": {"fourier": [22.64620490328089, 23.175981644292715, 52.124829679727554]}, "4": {"fourier": [26.565374883561113, 29.064112116685966, 35.88002127408981]}, "5": {"fourier": [16.565287530349124, 17.96376332824126, 62.73305872827768]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [26.3314389005784, 26.560762181463247, 74.70699590444565]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.33982, 0.060102, -0.141934, -0.467474, 0.187096], [0.81844, -0.183197, -0.290353, 0.080845, 0.07467], [0.434997, 0.041486, 0.318275, 0.448832, 0.065125], [-0.193791, -0.08262, -0.180336, -0.061852, 0.374577], [0.188766, 0.54999, 0.543557, -0.293399, -0.197708], [-0.726361, 0.223436, 0.691201, 0.129216, 0.590329]], "network.0.bias": [-0.179509, 0.154182, -0.712082, 0.83968, -0.270253, 0.248876], "network.2.weight": [[0.280704, -0.120611, -0.598399, 0.50283, -0.153336, 0.290706], [0.17958, 0.40608, 0.136973, 0.174554, 0.075586, 0.431601], [0.413852, 0.129191, 0.451508, 0.201458, 0.136871, -0.093194], [-0.189032, 0.542428, -0.357726, 0.468937, -0.321867, -0.116014], [0.401191, -0.19158, 0.024152, 0.11548, 0.096153, 0.503958], [-0.194505, 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-0.581817, 0.623001, -0.526377, -0.663748]], "network.6.bias": [0.435353, 0.56588, 0.083206, -0.311074, 0.293797, 0.548146], "network.8.weight": [[0.177957, -0.278013, 0.032658, 0.206923, 0.172477, 0.241565], [0.338236, -0.504771, -0.385435, -0.237828, -0.221337, 0.544263], [-0.780879, 0.553466, 0.420328, 0.033364, -0.120357, -0.478021], [0.237194, -0.556087, -0.545506, 0.056452, 0.503897, 0.641102], [0.330098, -0.462773, -0.539504, -0.454053, 0.339045, 0.371149], [-0.475126, 0.287664, 0.610835, -0.169304, 0.018711, -0.327308]], "network.8.bias": [-0.308483, 0.330274, 0.506641, 0.40384, 0.150913, 0.030694], "network.10.weight": [[0.186969, 0.310059, -0.428708, 0.186426, 0.328485, -0.748319], [-0.144122, 0.391506, -0.778244, 0.312274, 0.473982, -0.096016], [0.636389, -0.136156, -0.412272, -0.068108, 0.529319, -0.713374], [-0.692478, -0.2749, 0.398359, -0.434021, -0.812, 0.263623], [0.275287, 0.663562, -0.517422, 0.484564, 0.111228, -0.649595], [-0.178451, -0.195918, -0.733881, 0.321241, 0.306049, -0.140181]], "network.10.bias": [-0.047161, 0.060838, 0.085627, 0.464628, -0.034149, -0.104494], "network.12.weight": [[0.56051, 0.449483, 0.128883, -0.859982, 0.408728, 0.346977]], "network.12.bias": [-0.559859]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6972120106220245, "train_acc": 0.575, "val_loss": 0.738274335861206, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6840828359127045, "train_acc": 0.575, "val_loss": 0.7247399687767029, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6744686961174011, "train_acc": 0.575, "val_loss": 0.7106653451919556, "val_acc": 0.46}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6732122302055359, "train_acc": 0.575, "val_loss": 0.6909191608428955, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6598543226718903, "train_acc": 0.575, "val_loss": 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"epoch": 7, "global_epoch": 11, "train_loss": 0.4030041843652725, "train_acc": 0.855, "val_loss": 0.37715157866477966, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.3360000103712082, "train_acc": 0.88, "val_loss": 0.31958290934562683, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.2947402894496918, "train_acc": 0.885, "val_loss": 0.24616307020187378, "val_acc": 0.92}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.738274335861206, "final_val_loss": 0.6909191608428955, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.640418529510498, "final_val_loss": 0.24616307020187378, "initial_val_acc": 0.6, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 13}, "improvement": 0.46, "first_improvement_epoch": 3}} |
85 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.48, "improved_accuracy": 0.94, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4211, "learning_rate": 0.038871271727713465, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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-0.174159,
0.043269
],
[
0.577716,
-0.094206,
0.134417,
0.195664,
0.516685,
0.076127
],
[
-0.345117,
0.087645,
0.204754,
-0.022617,
0.149897,
0.050083
],
[
-0.303329,
-0.403296,
0.269038,
0.235367,
0.262305,
0.031419
]
],
"network.8.bias": [
0.039008,
0.133073,
-0.149107,
0.10367,
0.197585,
-0.490997
],
"network.10.weight": [
[
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0.146904,
0.001305,
0.063983
],
[
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0.269559,
0.28926,
-0.030448
],
[
-0.055293,
0.509629,
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0.262489,
0.101621
],
[
0.494362,
0.320493,
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0.387059,
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],
[
0.410279,
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0.31682,
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],
[
-0.369677,
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0.14967,
0.400886,
0.275697,
0.253636
]
],
"network.10.bias": [
-0.189832,
0.288755,
0.376488,
-0.207298,
-0.077817,
0.419125
],
"network.12.weight": [
[
0.336811,
0.087167,
-0.439274,
-0.50231,
-0.178534,
0.508829
]
],
"network.12.bias": [
-0.145844
]
}
## Activation Signature
### 0
fourier: [[21.523238, 22.037753, 100.534972], [41.799260, 45.570722, 275.082500], [27.697587, 29.669772, 160.867006], [23.927594, 26.107112, 182.536703], [21.814353, 25.529822, 65.994463], [20.271964, 20.469928, 81.019862]]
### 2
fourier: [[22.486911, 22.505335, 65.087687], [19.886388, 21.160601, 150.556001], [10.125396, 13.236538, 69.284511], [5.595614, 6.049874, 87.631568], [23.360031, 25.388670, 37.286722], [23.037447, 24.812751, 195.860151]]
### 4
fourier: [[13.569242, 14.131542, 32.523571], [16.028444, 16.840430, 27.062114], [2.368145, 2.642740, 42.918850], [9.624451, 10.109787, 17.225844], [5.304642, 5.953209, 80.929773], [8.956400, 9.160618, 14.827317]]
### 6
fourier: [[6.537743, 6.862672, 7.164022], [0.680886, 0.765364, 16.078071], [4.040682, 4.121234, 31.572513], [9.519153, 10.021335, 68.838265], [5.389407, 5.849618, 10.198973], [0.337927, 0.378337, 17.233882]]
### 8
fourier: [[5.421740, 5.447631, 30.587344], [8.668803, 8.830487, 51.171475], [3.610266, 3.750879, 37.724719], [1.859958, 2.246718, 32.610087], [0.618984, 0.662439, 13.777051], [2.618671, 2.651451, 29.168254]]
### 10
fourier: [[0.257133, 0.262651, 9.752028], [1.916434, 2.020016, 26.371457], [4.001131, 4.005259, 59.785417], [4.284213, 4.754121, 24.828208], [1.561544, 1.697116, 13.168929], [6.137435, 6.172607, 15.059497]]
### 12
fourier: [[6.866536, 6.870907, 42.149413]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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"network.0.bias": [
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"network.2.weight": [
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]
],
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],
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0.300893
],
[
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]
],
"network.4.bias": [
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"network.6.weight": [
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[
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]
],
"network.12.bias": [
-0.145844
]
}
## Activation Signature
### 0
fourier: [[21.523238, 22.037753, 100.534972], [41.799260, 45.570722, 275.082500], [27.697587, 29.669772, 160.867006], [23.927594, 26.107112, 182.536703], [21.814353, 25.529822, 65.994463], [20.271964, 20.469928, 81.019862]]
### 2
fourier: [[22.486911, 22.505335, 65.087687], [19.886388, 21.160601, 150.556001], [10.125396, 13.236538, 69.284511], [5.595614, 6.049874, 87.631568], [23.360031, 25.388670, 37.286722], [23.037447, 24.812751, 195.860151]]
### 4
fourier: [[13.569242, 14.131542, 32.523571], [16.028444, 16.840430, 27.062114], [2.368145, 2.642740, 42.918850], [9.624451, 10.109787, 17.225844], [5.304642, 5.953209, 80.929773], [8.956400, 9.160618, 14.827317]]
### 6
fourier: [[6.537743, 6.862672, 7.164022], [0.680886, 0.765364, 16.078071], [4.040682, 4.121234, 31.572513], [9.519153, 10.021335, 68.838265], [5.389407, 5.849618, 10.198973], [0.337927, 0.378337, 17.233882]]
### 8
fourier: [[5.421740, 5.447631, 30.587344], [8.668803, 8.830487, 51.171475], [3.610266, 3.750879, 37.724719], [1.859958, 2.246718, 32.610087], [0.618984, 0.662439, 13.777051], [2.618671, 2.651451, 29.168254]]
### 10
fourier: [[0.257133, 0.262651, 9.752028], [1.916434, 2.020016, 26.371457], [4.001131, 4.005259, 59.785417], [4.284213, 4.754121, 24.828208], [1.561544, 1.697116, 13.168929], [6.137435, 6.172607, 15.059497]]
### 12
fourier: [[6.866536, 6.870907, 42.149413]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.52323839472983, 22.037753278590483, 100.53497210144997]}, "1": {"fourier": [41.79926036447004, 45.570721835558665, 275.08250019326806]}, "2": {"fourier": [27.69758723572618, 29.669771866425695, 160.86700648069382]}, "3": {"fourier": [23.927593715679834, 26.10711154765386, 182.53670325875282]}, "4": {"fourier": [21.814352857867693, 25.529821822041814, 65.99446287751198]}, "5": {"fourier": [20.271964461493212, 20.469927669020677, 81.01986212842166]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [22.48691052464722, 22.505335104725223, 65.08768711425364]}, "1": {"fourier": [19.88638769469417, 21.160601003192795, 150.55600148439407]}, "2": {"fourier": [10.125395673214229, 13.236537843126843, 69.28451071679592]}, "3": {"fourier": [5.5956135167688, 6.049873872423243, 87.63156819343567]}, "4": {"fourier": [23.360030961639914, 25.388669713429127, 37.286722069606185]}, "5": {"fourier": [23.037447352821065, 24.812751349254423, 195.86015141010284]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [13.569241657869414, 14.131542026448168, 32.52357068657875]}, "1": {"fourier": [16.028443541901044, 16.84043035292643, 27.062113910913467]}, "2": {"fourier": [2.368145439207457, 2.6427402419243613, 42.91885036230087]}, "3": {"fourier": [9.62445059835195, 10.109786752132521, 17.22584369778633]}, "4": {"fourier": [5.30464233649665, 5.9532086664500055, 80.92977261543274]}, "5": {"fourier": [8.956400241007186, 9.160618415969429, 14.827317133545876]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [6.537743034670808, 6.86267163099692, 7.164022281765938]}, "1": {"fourier": [0.6808859136992206, 0.7653641324031836, 16.078071288764477]}, "2": {"fourier": [4.040682005021795, 4.1212337507117205, 31.572513461112976]}, "3": {"fourier": [9.519152784924454, 10.021335296046908, 68.83826485276222]}, "4": {"fourier": [5.38940742505844, 5.849618418216087, 10.198972880840302]}, "5": {"fourier": [0.3379265929911738, 0.37833695934269296, 17.23388162255287]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [5.421739751339739, 5.447631266866311, 30.58734407275915]}, "1": {"fourier": [8.66880270690823, 8.830486873589182, 51.171474516391754]}, "2": {"fourier": [3.6102655883423087, 3.7508788085060263, 37.72471894323826]}, "3": {"fourier": [1.8599581955744975, 2.2467183842700154, 32.610086753964424]}, "4": {"fourier": [0.6189835933561184, 0.6624386739881086, 13.777050964534283]}, "5": {"fourier": [2.618671259794663, 2.651451112104884, 29.168253779411316]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [0.25713278417424384, 0.26265108572251583, 9.752028428018093]}, "1": {"fourier": [1.9164338081289534, 2.020015965642385, 26.37145735323429]}, "2": {"fourier": [4.00113131908521, 4.005258772188016, 59.785416811704636]}, "3": {"fourier": [4.284213199637224, 4.754120636211819, 24.828207969665527]}, "4": {"fourier": [1.5615436760974155, 1.6971156779813243, 13.168929360806942]}, "5": {"fourier": [6.13743462029702, 6.1726072635685725, 15.059497088193893]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [6.8665362239784065, 6.870907008478394, 42.149413496255875]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | 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0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.22121693193912506, "train_acc": 0.945, "val_loss": 0.24042552709579468, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 4, "improved_epochs": 8, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7100178003311157, "final_val_loss": 0.6546432375907898, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5528853535652161, "final_val_loss": 0.24042552709579468, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 4}, "improvement": 0.45999999999999996, "first_improvement_epoch": 3}} |
86 | {"target_pattern": "palindrome", "degraded_accuracy": 0.54, "improved_accuracy": 0.86, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 6772, "learning_rate": 0.08443058899112679, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[40.501318, 40.592694, 48.407977], [34.554016, 35.498520, 248.741925], [29.473502, 40.331538, 122.430486], [13.412307, 15.218280, 75.083320], [23.173946, 23.863547, 68.465012], [29.165110, 31.855157, 61.669306], [28.915060, 33.350636, 98.438729]]
### 2
fourier: [[6.420471, 7.891183, 59.002393], [19.962923, 20.941990, 179.145353], [25.570931, 29.657905, 135.037673], [9.142461, 11.581608, 26.879514], [11.613061, 12.246150, 22.671300], [45.813262, 49.324117, 64.284032], [13.529538, 17.944147, 42.876446]]
### 4
fourier: [[15.521213, 17.105980, 114.356911], [17.374669, 18.715550, 133.803156], [31.439291, 36.920606, 165.872817], [14.961652, 15.303001, 111.003691], [59.407707, 66.066431, 248.501052], [9.681125, 11.508520, 78.537924], [24.388367, 30.423622, 112.670727]]
### 6
fourier: [[17.247928, 19.226050, 138.699048], [29.698775, 33.017873, 127.616485], [24.633597, 27.392525, 112.763372], [34.179545, 38.007024, 165.082397], [28.109036, 31.276237, 121.163605], [25.643181, 28.491836, 100.143691], [17.448997, 19.371392, 60.641176]]
### 8
fourier: [[38.027203, 42.390697, 171.220886], [3.438413, 3.892837, 23.082028], [10.788542, 12.024913, 89.962184], [24.993218, 27.955079, 113.481755], [2.124609, 2.347487, 64.629234], [23.221512, 25.919648, 123.231424], [35.893072, 40.065908, 159.533397]]
### 10
fourier: [[28.889018, 32.225895, 85.488963]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.729576,
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"network.8.weight": [
[
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]
}
## Activation Signature
### 0
fourier: [[40.501318, 40.592694, 48.407977], [34.554016, 35.498520, 248.741925], [29.473502, 40.331538, 122.430486], [13.412307, 15.218280, 75.083320], [23.173946, 23.863547, 68.465012], [29.165110, 31.855157, 61.669306], [28.915060, 33.350636, 98.438729]]
### 2
fourier: [[6.420471, 7.891183, 59.002393], [19.962923, 20.941990, 179.145353], [25.570931, 29.657905, 135.037673], [9.142461, 11.581608, 26.879514], [11.613061, 12.246150, 22.671300], [45.813262, 49.324117, 64.284032], [13.529538, 17.944147, 42.876446]]
### 4
fourier: [[15.521213, 17.105980, 114.356911], [17.374669, 18.715550, 133.803156], [31.439291, 36.920606, 165.872817], [14.961652, 15.303001, 111.003691], [59.407707, 66.066431, 248.501052], [9.681125, 11.508520, 78.537924], [24.388367, 30.423622, 112.670727]]
### 6
fourier: [[17.247928, 19.226050, 138.699048], [29.698775, 33.017873, 127.616485], [24.633597, 27.392525, 112.763372], [34.179545, 38.007024, 165.082397], [28.109036, 31.276237, 121.163605], [25.643181, 28.491836, 100.143691], [17.448997, 19.371392, 60.641176]]
### 8
fourier: [[38.027203, 42.390697, 171.220886], [3.438413, 3.892837, 23.082028], [10.788542, 12.024913, 89.962184], [24.993218, 27.955079, 113.481755], [2.124609, 2.347487, 64.629234], [23.221512, 25.919648, 123.231424], [35.893072, 40.065908, 159.533397]]
### 10
fourier: [[28.889018, 32.225895, 85.488963]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [40.5013177896473, 40.592693937804455, 48.407976599806034]}, "1": {"fourier": [34.55401564454605, 35.49851986371522, 248.74192491173744]}, "2": {"fourier": [29.473501635170297, 40.33153774228823, 122.43048563599586]}, "3": {"fourier": [13.412306811701546, 15.218280419364257, 75.08332036435604]}, "4": {"fourier": [23.173945788480708, 23.86354691552182, 68.46501159667969]}, "5": {"fourier": [29.165109940382287, 31.855157130773385, 61.66930624842644]}, "6": {"fourier": [28.915060028985117, 33.35063617428723, 98.43872863054276]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [6.420471327410469, 7.891183028747891, 59.00239332020283]}, "1": {"fourier": [19.962922754112203, 20.941990043943953, 179.14535290002823]}, "2": {"fourier": [25.57093101678981, 29.65790495510325, 135.03767344355583]}, "3": {"fourier": [9.142461053054827, 11.581608276304268, 26.879514150321484]}, "4": {"fourier": [11.613060614252394, 12.246149541251022, 22.671299770474434]}, "5": {"fourier": [45.8132619433289, 49.32411682401297, 64.28403155505657]}, "6": {"fourier": [13.529537966358099, 17.94414655917371, 42.87644571065903]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [15.521212933746654, 17.105979748397623, 114.35691088438034]}, "1": {"fourier": [17.37466897965975, 18.71554954718265, 133.80315601825714]}, "2": {"fourier": [31.439290838465045, 36.92060579830216, 165.87281692028046]}, "3": {"fourier": [14.961651870377038, 15.30300076084831, 111.00369104743004]}, "4": {"fourier": [59.407707119307666, 66.06643059147038, 248.50105150043964]}, "5": {"fourier": [9.681124566706314, 11.5085200889783, 78.53792434930801]}, "6": {"fourier": [24.388367136723794, 30.423621764407645, 112.67072651535273]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [17.247928213615076, 19.22605018402223, 138.6990482211113]}, "1": {"fourier": [29.698775283410395, 33.01787251372315, 127.61648502200842]}, "2": {"fourier": [24.633596680314206, 27.392525497936134, 112.76337243616581]}, "3": {"fourier": [34.17954462558085, 38.007024238800646, 165.08239749073982]}, "4": {"fourier": [28.109035769123587, 31.27623689676914, 121.16360485553741]}, "5": {"fourier": [25.643180566086677, 28.491836346691315, 100.1436910033226]}, "6": {"fourier": [17.448996608428537, 19.371392111013247, 60.641176365315914]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [38.02720331939233, 42.39069723012719, 171.22088623046875]}, "1": {"fourier": [3.438413161984782, 3.8928367963710917, 23.082028277218342]}, "2": {"fourier": [10.78854151154373, 12.024912970017441, 89.96218395233154]}, "3": {"fourier": [24.993217609294575, 27.955079066424602, 113.48175537586212]}, "4": {"fourier": [2.1246086787726206, 2.347486702013201, 64.62923419475555]}, "5": {"fourier": [23.221512395931427, 25.919647710485624, 123.23142409324646]}, "6": {"fourier": [35.893071556864754, 40.06590838270748, 159.53339675068855]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [28.889018125330733, 32.22589471040493, 85.48896338045597]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.15804, 0.721515, -0.453013, 0.206144, -0.61385], [0.11052, -0.504927, -0.712039, -0.380634, -0.057386], [0.080753, 0.233382, -0.218866, -0.183686, 0.92219], [-0.085133, -0.098934, -0.045079, 0.08423, -0.311888], [-0.42428, 0.057128, 0.212326, 0.332715, 0.383833], [0.39332, -0.336702, -0.558053, 0.311903, 0.557366], [-0.267675, 0.1597, 0.574234, 0.152349, -0.709267]], "network.0.bias": [0.157924, 0.393149, 0.548296, -0.249837, -0.445793, 0.61873, 0.484407], "network.2.weight": [[-0.127909, -0.401526, 0.007578, 0.334518, -0.113425, -0.141608, -0.305378], [0.202517, -0.110235, 0.499529, -0.02735, 0.197916, 0.327936, 0.314059], [-0.176368, -0.366009, 0.414127, 0.092035, 0.375219, 0.428786, -0.032563], [0.188847, -0.281302, 0.138581, 0.312678, -0.338597, -0.232069, 0.141296], [0.290921, -0.035132, -0.274171, -0.361389, 0.141384, 0.513898, -0.369802], [-0.53759, -0.386303, 0.734447, -0.081623, -0.130772, 0.732295, -0.501602], [0.422221, 0.015475, 0.173821, -0.274905, -0.743716, 0.107189, -0.159246]], "network.2.bias": [0.117806, 0.155268, 0.262509, -0.232174, -0.264634, 0.081818, -0.210961], "network.4.weight": [[-0.542508, -0.408143, -0.044347, 0.338983, -0.04397, -0.173082, -0.320144], [0.067309, -0.542556, 0.06585, 0.05348, -0.055596, -0.228971, -0.311935], [-0.264532, -0.338462, -0.412966, 0.370772, 0.083411, -0.429603, -0.237974], [-0.113039, -0.166172, -0.025008, -0.030082, -0.622222, -0.246646, 0.567837], [0.279211, -0.070008, 0.858617, -0.172267, 0.23603, 1.028565, 0.625072], [0.547016, -0.167394, 0.177123, 0.067592, 0.076704, -0.327866, -0.12418], [-0.183549, 0.245913, -0.684644, -0.193034, 0.466876, -0.395355, -0.187172]], "network.4.bias": [-0.131893, -0.144464, 0.025755, -0.479662, 0.087069, -0.358285, -0.218303], "network.6.weight": [[0.009083, 0.32795, 0.454881, 0.232446, 0.290813, 0.382405, 0.824062], [0.013352, 0.060365, 0.504218, 0.414514, 0.499806, -0.264243, -0.183852], [0.083123, -0.125009, -0.2057, -0.547905, -0.414629, -0.050452, 0.040331], [-0.360426, -0.012012, -0.048658, -0.225236, -0.575299, 0.033888, 0.066965], [-0.392917, 0.044429, -0.187586, -0.033474, -0.473338, -0.374292, -0.311411], [0.418323, -0.308173, -0.114464, 0.247687, 0.431357, -0.098701, -0.488632], [-0.553849, -0.468461, 0.059112, -0.438989, 0.293331, 0.352016, -0.645131]], "network.6.bias": [0.729576, 0.039845, -0.108502, -0.246473, -0.036084, -0.073249, -0.129434], "network.8.weight": [[0.178223, 0.576913, 0.479192, 0.423703, 0.246378, 0.48472, 0.312721], [-0.092318, 0.106651, 0.154473, -0.140625, -0.145874, 0.049202, -0.361835], [-0.353611, -0.122483, 0.059705, 0.085616, 0.096209, 0.006972, -0.070978], [0.035568, -0.100761, 0.015217, -0.385926, 0.019117, -0.419055, -0.686229], [0.550965, -0.08802, 0.560752, 0.606941, 0.007653, -0.046293, -0.206555], [-0.118288, -0.083659, -0.317695, -0.110285, -0.153454, -0.57622, -0.228285], [0.357056, 0.236929, 0.105811, -0.086914, 0.503329, 0.563544, 0.477841]], "network.8.bias": [0.055633, -0.072648, -0.240153, -0.236308, 0.186749, -0.270016, -0.068569], "network.10.weight": [[-0.530411, 0.077746, -0.001463, -0.093598, 0.334845, -0.088655, -0.262733]], "network.10.bias": [0.284471]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6991086602210999, "train_acc": 0.505, "val_loss": 0.6948639154434204, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6956647038459778, "train_acc": 0.565, "val_loss": 0.6858869791030884, "val_acc": 0.54}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6666978597640991, "train_acc": 0.565, "val_loss": 0.6524702310562134, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6584815382957458, "train_acc": 0.57, "val_loss": 0.6702940464019775, "val_acc": 0.6}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6044072508811951, "train_acc": 0.695, "val_loss": 0.5162736773490906, "val_acc": 0.86}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4766986519098282, "train_acc": 0.83, "val_loss": 0.5069884061813354, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.4388886094093323, "train_acc": 0.85, "val_loss": 0.519456148147583, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.42748668789863586, "train_acc": 0.82, "val_loss": 0.486085444688797, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.39179520308971405, "train_acc": 0.825, "val_loss": 0.44846680760383606, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.36988668143749237, "train_acc": 0.855, "val_loss": 0.47011497616767883, "val_acc": 0.78}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.3338027894496918, "train_acc": 0.865, "val_loss": 0.3917123079299927, "val_acc": 0.8}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.32508109509944916, "train_acc": 0.88, "val_loss": 0.4277568757534027, "val_acc": 0.8}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.3264896869659424, "train_acc": 0.87, "val_loss": 0.42278292775154114, "val_acc": 0.82}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6948639154434204, "final_val_loss": 0.6524702310562134, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.6702940464019775, "final_val_loss": 0.42278292775154114, "initial_val_acc": 0.6, "final_val_acc": 0.82, "best_val_acc": 0.86, "best_epoch": 4}, "improvement": 0.31999999999999995, "first_improvement_epoch": 2}} |
87 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.58, "improved_accuracy": 0.8, "improvement": 0.22000000000000008, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1469, "learning_rate": 0.05734450156595675, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.273581,
0.110118,
0.080367,
0.810196,
-0.526576
],
[
0.390231,
0.040959,
-0.390277,
0.175629,
-0.569813,
0.174224
],
[
-0.600585,
0.459373,
0.213488,
-0.764111,
0.752085,
0.728239
],
[
0.184233,
-0.123441,
-0.262557,
0.303063,
-0.155884,
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]
],
"network.6.bias": [
0.10485,
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0.153592,
-0.086482,
0.352313
],
"network.8.weight": [
[
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0.650395,
0.705922,
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-0.759517
],
[
-0.333649,
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0.327502,
0.362378,
0.282071,
-0.429135
],
[
0.022055,
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0.136827,
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0.215104
],
[
0.849085,
0.846566,
0.364611,
-0.008654,
0.790778,
-0.529134
],
[
0.658143,
0.752109,
0.255605,
-0.311305,
0.203005,
-0.481714
],
[
0.246405,
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0.215527,
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]
],
"network.8.bias": [
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0.061127,
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-0.179448,
0.470548
],
"network.10.weight": [
[
-0.151381,
0.222368,
0.110108,
-0.910254,
-0.293566,
0.149725
]
],
"network.10.bias": [
0.585094
]
}
## Activation Signature
### 0
fourier: [[41.378605, 47.009298, 215.077652], [40.778598, 41.470334, 47.576489], [40.259533, 49.520570, 197.121653], [32.468868, 36.584518, 43.409383], [32.462298, 41.012086, 163.830457], [38.905834, 40.124208, 95.836679]]
### 2
fourier: [[48.301276, 53.212818, 60.583060], [64.758986, 75.016623, 83.215294], [61.741181, 67.912151, 342.434671], [63.515246, 71.109432, 77.163590], [29.366256, 31.095433, 35.636060], [82.888596, 94.902510, 146.329556]]
### 4
fourier: [[90.842750, 112.855326, 212.414792], [92.759861, 107.346358, 175.292082], [34.610873, 34.757064, 37.963841], [35.978983, 41.598354, 86.610245], [121.854767, 146.280708, 320.970668], [139.373486, 165.477484, 343.676332]]
### 6
fourier: [[337.725162, 402.824163, 866.782204], [296.191412, 352.445739, 720.380456], [53.294309, 63.829920, 82.294094], [52.574806, 62.873989, 117.366532], [238.734096, 284.557392, 597.786418], [106.788494, 127.346113, 236.346292]]
### 8
fourier: [[22.740827, 28.495824, 68.627546], [31.505098, 37.477706, 103.259844], [172.753202, 208.215201, 430.290826], [735.661936, 887.223235, 1863.860914], [500.883431, 603.308120, 1266.348643], [165.216092, 200.346589, 377.506916]]
### 10
fourier: [[813.389939, 985.602919, 2050.471062]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.560315,
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],
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0.16483,
1.188075
],
[
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-1.111739
],
[
0.053815,
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0.492131
],
[
0.108003,
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],
[
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1.128795
]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
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0.92109
],
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],
[
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],
[
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],
[
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1.246056
]
],
"network.2.bias": [
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0.4374,
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],
"network.4.weight": [
[
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],
[
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0.959333
],
[
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],
[
0.142573,
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],
[
0.223301,
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1.061965
],
[
0.108048,
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]
],
"network.4.bias": [
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],
"network.6.weight": [
[
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],
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],
"network.8.weight": [
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[
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[
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]
],
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],
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[
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0.149725
]
],
"network.10.bias": [
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]
}
## Activation Signature
### 0
fourier: [[41.378605, 47.009298, 215.077652], [40.778598, 41.470334, 47.576489], [40.259533, 49.520570, 197.121653], [32.468868, 36.584518, 43.409383], [32.462298, 41.012086, 163.830457], [38.905834, 40.124208, 95.836679]]
### 2
fourier: [[48.301276, 53.212818, 60.583060], [64.758986, 75.016623, 83.215294], [61.741181, 67.912151, 342.434671], [63.515246, 71.109432, 77.163590], [29.366256, 31.095433, 35.636060], [82.888596, 94.902510, 146.329556]]
### 4
fourier: [[90.842750, 112.855326, 212.414792], [92.759861, 107.346358, 175.292082], [34.610873, 34.757064, 37.963841], [35.978983, 41.598354, 86.610245], [121.854767, 146.280708, 320.970668], [139.373486, 165.477484, 343.676332]]
### 6
fourier: [[337.725162, 402.824163, 866.782204], [296.191412, 352.445739, 720.380456], [53.294309, 63.829920, 82.294094], [52.574806, 62.873989, 117.366532], [238.734096, 284.557392, 597.786418], [106.788494, 127.346113, 236.346292]]
### 8
fourier: [[22.740827, 28.495824, 68.627546], [31.505098, 37.477706, 103.259844], [172.753202, 208.215201, 430.290826], [735.661936, 887.223235, 1863.860914], [500.883431, 603.308120, 1266.348643], [165.216092, 200.346589, 377.506916]]
### 10
fourier: [[813.389939, 985.602919, 2050.471062]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [41.37860468531771, 47.00929764455805, 215.07765181176364]}, "1": {"fourier": [40.778598363610996, 41.47033353209186, 47.57648929149791]}, "2": {"fourier": [40.25953286619873, 49.52057026687897, 197.12165334820747]}, "3": {"fourier": [32.4688680783809, 36.584518086542076, 43.40938336293438]}, "4": {"fourier": [32.46229846795857, 41.01208634856804, 163.83045744895935]}, "5": {"fourier": [38.905833852261374, 40.124207851262575, 95.83667877316475]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [48.301275780031965, 53.212817896976595, 60.583059532811426]}, "1": {"fourier": [64.75898624242483, 75.01662277735929, 83.21529407054186]}, "2": {"fourier": [61.74118135614226, 67.91215098994162, 342.43467140197754]}, "3": {"fourier": [63.51524630618677, 71.1094319364945, 77.16358978115022]}, "4": {"fourier": [29.36625592158426, 31.095433146794495, 35.63605988869309]}, "5": {"fourier": [82.8885956589065, 94.9025102739069, 146.32955564558506]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [90.84275039208305, 112.8553263797879, 212.41479218006134]}, "1": {"fourier": [92.75986140882735, 107.34635798714217, 175.29208184033632]}, "2": {"fourier": [34.6108734165021, 34.75706445086769, 37.96384106316816]}, "3": {"fourier": [35.97898339292028, 41.598353826553996, 86.61024506390095]}, "4": {"fourier": [121.85476682530233, 146.28070762247074, 320.9706684798002]}, "5": {"fourier": [139.37348631985128, 165.4774837578926, 343.6763319373131]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [337.7251615197779, 402.8241628036373, 866.7822043895721]}, "1": {"fourier": [296.1914122756969, 352.4457386664429, 720.3804558217525]}, "2": {"fourier": [53.29430857213652, 63.829919917922105, 82.29409417510033]}, "3": {"fourier": [52.574805521262896, 62.87398924708147, 117.36653158068657]}, "4": {"fourier": [238.73409551546388, 284.55739167602184, 597.7864177674055]}, "5": {"fourier": [106.78849415415303, 127.34611282762876, 236.3462920486927]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [22.74082659913074, 28.49582438674446, 68.62754583358765]}, "1": {"fourier": [31.50509796392142, 37.4777056198958, 103.2598444968462]}, "2": {"fourier": [172.75320167231, 208.21520050795098, 430.2908255420625]}, "3": {"fourier": [735.6619357663369, 887.2232349245917, 1863.860914170742]}, "4": {"fourier": [500.88343055781826, 603.3081200524703, 1266.3486430197954]}, "5": {"fourier": [165.2160917197816, 200.34658903701995, 377.5069158822298]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [813.3899388468145, 985.6029193411467, 2050.4710624217987]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.780729, 0.358792, 0.097743, 0.560315, -0.543743], [-0.905819, -0.088589, -0.124885, 0.16483, 1.188075], [0.167644, 0.1521, -0.192719, -0.288187, -1.111739], [0.053815, -0.510179, 0.356156, -0.519983, 0.492131], [0.108003, -0.302847, 0.124475, -0.102926, -0.927259], [-0.813277, 0.05853, -0.04445, 0.05795, 1.128795]], "network.0.bias": [0.029257, 0.002214, 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0.470548], "network.10.weight": [[-0.151381, 0.222368, 0.110108, -0.910254, -0.293566, 0.149725]], "network.10.bias": [0.585094]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7038825750350952, "train_acc": 0.44, "val_loss": 0.6514937877655029, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6455237567424774, "train_acc": 0.555, "val_loss": 0.5614416599273682, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6307385563850403, "train_acc": 0.48, "val_loss": 0.5120663642883301, "val_acc": 0.72}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5464686751365662, "train_acc": 0.73, "val_loss": 0.4476953148841858, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.49858686327934265, "train_acc": 0.715, "val_loss": 0.4507802724838257, "val_acc": 0.74}, {"stage": "improved", "epoch": 3, "global_epoch": 5, 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"val_loss": 0.3781922161579132, "val_acc": 0.8}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6514937877655029, "final_val_loss": 0.5614416599273682, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.5120663642883301, "final_val_loss": 0.3781922161579132, "initial_val_acc": 0.72, "final_val_acc": 0.8, "best_val_acc": 0.8, "best_epoch": 11}, "improvement": 0.22000000000000008, "first_improvement_epoch": 1}} |
88 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.6, "improved_accuracy": 0.84, "improvement": 0.24, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9217, "learning_rate": 0.03413339280459434, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[25.841771, 31.577088, 50.457853], [22.012311, 25.005625, 25.770543], [31.170351, 37.452744, 234.303064], [17.877160, 18.930603, 67.440507], [20.112176, 22.652730, 167.002240], [12.121842, 13.967719, 121.039245], [23.039652, 33.365828, 77.221362], [30.305489, 30.510272, 177.586280]]
### 2
fourier: [[6.209106, 6.213997, 80.567967], [25.478051, 26.198099, 171.117013], [27.899083, 28.760342, 190.110670], [17.688504, 18.738069, 21.963181], [12.235775, 13.481218, 67.706947], [14.256899, 14.343085, 117.529005], [14.737041, 15.632589, 46.109270], [32.781280, 33.327941, 221.016817]]
### 4
fourier: [[17.614666, 21.184239, 143.967412], [50.014845, 52.498458, 318.572208], [5.135327, 6.288827, 61.018359], [21.147134, 21.177928, 86.484283], [19.004507, 19.509933, 199.048897], [9.684323, 10.136518, 149.988200], [68.690634, 74.098538, 442.474010], [13.714387, 14.270539, 138.585641]]
### 6
fourier: [[58.433602, 66.610872, 237.077325], [18.346495, 20.518127, 35.967000], [84.490145, 87.266353, 482.279660], [56.099887, 56.210237, 344.460642], [68.404749, 74.017110, 327.893808], [14.259896, 19.807213, 51.244308], [48.114593, 51.951510, 217.427716], [89.668502, 93.201594, 521.706953]]
### 8
fourier: [[161.936315, 169.025585, 798.777565]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[25.841771, 31.577088, 50.457853], [22.012311, 25.005625, 25.770543], [31.170351, 37.452744, 234.303064], [17.877160, 18.930603, 67.440507], [20.112176, 22.652730, 167.002240], [12.121842, 13.967719, 121.039245], [23.039652, 33.365828, 77.221362], [30.305489, 30.510272, 177.586280]]
### 2
fourier: [[6.209106, 6.213997, 80.567967], [25.478051, 26.198099, 171.117013], [27.899083, 28.760342, 190.110670], [17.688504, 18.738069, 21.963181], [12.235775, 13.481218, 67.706947], [14.256899, 14.343085, 117.529005], [14.737041, 15.632589, 46.109270], [32.781280, 33.327941, 221.016817]]
### 4
fourier: [[17.614666, 21.184239, 143.967412], [50.014845, 52.498458, 318.572208], [5.135327, 6.288827, 61.018359], [21.147134, 21.177928, 86.484283], [19.004507, 19.509933, 199.048897], [9.684323, 10.136518, 149.988200], [68.690634, 74.098538, 442.474010], [13.714387, 14.270539, 138.585641]]
### 6
fourier: [[58.433602, 66.610872, 237.077325], [18.346495, 20.518127, 35.967000], [84.490145, 87.266353, 482.279660], [56.099887, 56.210237, 344.460642], [68.404749, 74.017110, 327.893808], [14.259896, 19.807213, 51.244308], [48.114593, 51.951510, 217.427716], [89.668502, 93.201594, 521.706953]]
### 8
fourier: [[161.936315, 169.025585, 798.777565]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [25.841771182184527, 31.577087967079134, 50.45785257220268]}, "1": {"fourier": [22.01231133466456, 25.005624786019325, 25.770543202709057]}, "2": {"fourier": [31.170351479010446, 37.45274429015925, 234.3030644953251]}, "3": {"fourier": [17.877159639065674, 18.930602857009696, 67.44050669670105]}, "4": {"fourier": [20.11217645146546, 22.65273012086277, 167.00223991274834]}, "5": {"fourier": [12.12184193160327, 13.967718543006697, 121.03924486041069]}, "6": {"fourier": [23.039652317926368, 33.36582756063216, 77.22136236727238]}, "7": {"fourier": [30.30548923677187, 30.510271841376493, 177.58627966046333]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [6.2091063471998185, 6.213996615559149, 80.56796744465828]}, "1": {"fourier": [25.478050787133046, 26.19809879481834, 171.11701348423958]}, "2": {"fourier": [27.899083329758998, 28.760342284963297, 190.11067029833794]}, "3": {"fourier": [17.688504405884704, 18.73806887175705, 21.963180823892912]}, "4": {"fourier": [12.235775499697032, 13.481218445902691, 67.70694718137383]}, "5": {"fourier": [14.256898636474988, 14.343085427145626, 117.5290045440197]}, "6": {"fourier": [14.737041470293946, 15.632588682923599, 46.109270483255386]}, "7": {"fourier": [32.781280056832365, 33.32794109141613, 221.01681730151176]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [17.61466616973549, 21.184239423854326, 143.96741181612015]}, "1": {"fourier": [50.01484455050612, 52.498458150514324, 318.57220816612244]}, "2": {"fourier": [5.135326643309667, 6.2888265096392075, 61.01835939288139]}, "3": {"fourier": [21.147133571343083, 21.177928364430848, 86.48428289592266]}, "4": {"fourier": [19.00450719433387, 19.50993280452201, 199.0488966703415]}, "5": {"fourier": [9.684322852451578, 10.13651757143463, 149.9882003068924]}, "6": {"fourier": [68.69063387883423, 74.09853765248678, 442.47400999069214]}, "7": {"fourier": [13.714386983852485, 14.270538588823834, 138.58564084768295]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [58.43360232719288, 66.61087155447336, 237.0773250311613]}, "1": {"fourier": [18.346494618592832, 20.51812746919879, 35.96700023859739]}, "2": {"fourier": [84.49014531498094, 87.26635349628845, 482.2796599417925]}, "3": {"fourier": [56.09988740137474, 56.21023693234612, 344.46064165234566]}, "4": {"fourier": [68.4047492417744, 74.01710995517881, 327.8938083052635]}, "5": {"fourier": [14.259896431138209, 19.80721268336031, 51.24430847167969]}, "6": {"fourier": [48.114592892110274, 51.951509970454396, 217.4277158677578]}, "7": {"fourier": [89.66850171114609, 93.20159360709067, 521.7069531418383]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [161.93631486540212, 169.02558532080485, 798.7775646746159]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.448786, -0.441849, 0.413538, 0.397925, -0.061162], [0.015099, 0.527439, -0.093949, 0.079094, -0.263057], [0.230583, 0.69498, 0.313294, -0.225469, 0.228793], [0.492332, -0.022175, -0.153049, 0.034327, -0.032195], [-0.227764, -0.34594, -0.19186, -0.035415, -0.117588], [-0.033061, -0.358636, -0.032826, 0.034193, -0.095476], [0.353711, 0.289055, -0.416807, -0.008897, -0.47945], [0.276969, -0.258802, 0.247115, -0.522262, -0.590687]], "network.0.bias": [0.282549, -0.350988, 0.596902, 0.462865, -0.320018, -0.537224, -0.343849, -0.51398], "network.2.weight": [[-0.10141, 0.090336, -0.03489, 0.308771, -0.327868, 0.110511, 0.066981, 0.038991], [-0.347724, 0.580347, 0.352296, 0.516761, -0.003503, -0.179585, 0.18589, -0.069307], [-0.271872, 0.675673, 0.508893, 0.239433, 0.298073, -0.264882, 0.424952, 0.189966], [0.675225, -0.149249, -0.026934, -0.427464, 0.368418, -0.388339, -0.361601, -0.187617], [0.627489, -0.012098, 0.119711, -0.022687, -0.155332, 0.203873, -0.254945, -0.380437], [-0.152515, 0.187784, 0.243377, 0.299209, -0.169595, -0.163621, 0.338389, 0.02333], [0.606849, 0.015276, -0.008363, -0.343255, 0.109253, 0.056124, -0.058722, -0.224548], [-0.515621, 0.350836, 0.565534, 0.669129, -0.267579, 0.032488, 0.432858, -0.107395]], "network.2.bias": [0.764706, 0.511617, 0.337206, 0.070163, -0.020968, 0.383758, 0.272818, 0.620816], "network.4.weight": [[0.375652, -0.183585, 0.010332, 0.397275, 0.739251, -0.040461, 0.543685, 0.171795], [0.609446, 0.3397, 0.363495, -0.210189, 0.01592, 0.134533, -0.446159, 0.632766], [0.225436, -0.297269, -0.047733, -0.093027, -0.351017, -0.117288, -0.026798, 0.260167], [-0.018175, 0.150115, -0.209919, -0.292452, -0.071362, -0.08405, -0.023818, 0.606164], [-0.337212, -0.086453, -0.133976, -0.087282, 0.145457, 0.168535, -0.132966, -0.458935], [-0.211829, -0.215213, -0.174819, 0.105069, -0.369836, -0.013556, -0.10448, 0.035637], [0.720536, 0.66021, 0.407651, -0.376137, -0.471319, 0.517668, -0.214564, 0.658783], [-0.220088, -0.205937, -0.376539, -0.311179, -0.013458, 0.218905, 0.107317, -0.036148]], "network.4.bias": [0.09782, 0.21899, -0.367656, -0.034613, -0.526902, -0.467922, 0.534277, -0.249266], "network.6.weight": [[-0.715942, 0.520202, -0.243805, -0.236924, 0.280929, -0.088489, 0.413434, -0.187023], [-0.288241, 0.193319, -0.313265, 0.304455, -0.423192, -0.210375, -0.009426, 0.226739], [-0.229601, 0.681265, 0.046005, 0.372475, -0.114647, -0.517646, 0.584916, -0.284784], [0.064734, 0.298223, -0.209299, 0.198209, 0.136615, -0.073529, 0.550476, 0.079278], [-0.522913, 0.303362, 0.208804, 0.334021, -0.214351, -0.389428, 0.588907, 0.225021], [0.479922, -0.36091, -0.155622, 0.547514, 0.133518, -0.052584, -0.014095, -8.4e-05], [0.298149, -0.304605, -0.333728, 0.031804, -0.018572, 0.134351, -0.434317, -0.276361], [-0.244428, 0.685147, -0.294288, 0.175865, -0.119076, 0.143456, 0.709817, -0.065754]], "network.6.bias": [0.114582, -0.106541, -0.014016, -0.29048, 0.111905, 0.581484, 0.322624, 0.021257], "network.8.weight": [[-0.459613, -0.092041, -0.491355, 0.014417, -0.495021, 0.54684, 0.338509, -0.647446]], "network.8.bias": [0.422424]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6968017816543579, "train_acc": 0.43, "val_loss": 0.6834458708763123, "val_acc": 0.6}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6922330856323242, "train_acc": 0.54, "val_loss": 0.6609860062599182, "val_acc": 0.6}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6649974882602692, "train_acc": 0.54, "val_loss": 0.6321235299110413, "val_acc": 0.6}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6227662265300751, "train_acc": 0.525, "val_loss": 0.5487847924232483, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.49849945306777954, "train_acc": 0.88, "val_loss": 0.45780348777770996, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.41943544149398804, "train_acc": 0.87, "val_loss": 0.3850709795951843, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.34122392535209656, "train_acc": 0.875, "val_loss": 0.358539342880249, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.32002903521060944, "train_acc": 0.88, "val_loss": 0.408153772354126, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.3029025048017502, "train_acc": 0.905, "val_loss": 0.45003241300582886, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3093557506799698, "train_acc": 0.875, "val_loss": 0.4803730845451355, "val_acc": 0.8}], "summary": {"total_epochs": 10, "degraded_epochs": 3, "improved_epochs": 7, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6834458708763123, "final_val_loss": 0.6321235299110413, "initial_val_acc": 0.6, "final_val_acc": 0.6, "best_val_acc": 0.6}, "improved_stage": {"initial_val_loss": 0.5487847924232483, "final_val_loss": 0.4803730845451355, "initial_val_acc": 0.76, "final_val_acc": 0.8, "best_val_acc": 0.84, "best_epoch": 8}, "improvement": 0.24, "first_improvement_epoch": 2}} |
89 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.62, "improved_accuracy": 0.94, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1428, "learning_rate": 0.04296735297046316, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.085699,
-0.250134,
-0.061916,
-0.222805,
0.530398
],
[
-0.179335,
-0.216089,
-0.248409,
0.340105,
0.451389
],
[
-0.623418,
0.339321,
0.156741,
0.166875,
-0.170148
],
[
-0.391366,
-0.291775,
0.005171,
-0.019727,
-0.020203
],
[
-0.330435,
0.18684,
-0.032278,
-0.510089,
0.358357
]
],
"network.0.bias": [
-0.146301,
-0.231048,
0.335919,
-0.608974,
0.350195
],
"network.2.weight": [
[
-0.3939,
-0.539466,
-0.334062,
-0.055338,
-0.075041
],
[
0.502831,
0.130856,
0.545959,
-0.70227,
0.353568
],
[
0.632719,
0.642537,
0.335097,
-0.660966,
0.260145
],
[
0.056916,
0.251744,
0.46144,
0.199285,
0.394305
],
[
-0.114783,
-0.550003,
-0.199963,
-0.549869,
0.179697
]
],
"network.2.bias": [
0.822195,
0.236021,
-0.230188,
-0.252017,
0.461703
],
"network.4.weight": [
[
0.292294,
0.004148,
-0.228121,
-0.430331,
0.174579
],
[
-0.38642,
0.520893,
0.252108,
0.445958,
-0.06907
],
[
0.017701,
0.814792,
0.030212,
0.387304,
-0.110106
],
[
0.826304,
-0.157934,
-0.756781,
-0.50919,
0.237043
],
[
-0.228446,
-0.024242,
0.24566,
0.13703,
-0.744432
]
],
"network.4.bias": [
-0.23491,
0.500763,
0.064989,
0.230397,
-0.019931
],
"network.6.weight": [
[
-0.178427,
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-0.559817,
0.642846
],
[
-0.279959,
0.038846,
-0.077731,
-0.208713,
-0.009316
],
[
-0.433822,
0.386882,
0.607733,
-0.79736,
-0.131703
],
[
-0.141753,
0.378891,
-0.162191,
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0.508402
],
[
-0.398338,
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]
],
"network.6.bias": [
-0.178077,
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0.171353,
-0.007656,
0.405733
],
"network.8.weight": [
[
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],
[
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-0.706234,
-0.176074
],
[
-0.001006,
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0.302938
],
[
0.486601,
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-0.01395,
0.042978,
0.51012
],
[
-0.506002,
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-0.383505,
-0.49226,
-0.104399
]
],
"network.8.bias": [
-0.107442,
0.480371,
0.113296,
-0.13726,
0.371212
],
"network.10.weight": [
[
-0.282015,
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-0.205345,
0.157479,
-0.047648
],
[
0.124827,
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-0.306599,
-0.440691,
0.023906
],
[
-0.396314,
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0.125987,
0.325756,
-0.370242
],
[
-0.042524,
0.328917,
-0.561264,
-0.211722,
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],
[
-0.217702,
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-0.215892,
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]
],
"network.10.bias": [
0.063463,
0.095191,
-0.096205,
0.0861,
0.466971
],
"network.12.weight": [
[
0.176182,
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-0.144233,
0.290872,
0.498245
]
],
"network.12.bias": [
-0.21425
]
}
## Activation Signature
### 0
fourier: [[20.310741, 22.052624, 40.358085], [22.073582, 23.196935, 24.600584], [23.293627, 32.301729, 58.846223], [18.513979, 19.663570, 151.569244], [19.225567, 19.542710, 39.587526]]
### 2
fourier: [[12.713145, 12.742390, 25.016730], [10.144624, 11.803950, 86.110905], [15.450435, 16.457355, 44.610065], [9.520614, 11.121974, 24.888166], [10.192778, 10.308768, 14.983267]]
### 4
fourier: [[8.031535, 8.240961, 29.239725], [13.007494, 14.719189, 93.615059], [11.234356, 13.023387, 76.586493], [17.476513, 20.453462, 20.607806], [7.374689, 7.821845, 9.046945]]
### 6
fourier: [[7.845683, 9.619525, 16.604033], [1.818317, 2.026126, 25.677641], [16.681811, 20.168479, 71.608674], [8.228192, 9.072217, 10.538850], [16.086055, 19.436371, 100.257628]]
### 8
fourier: [[4.239980, 4.302854, 62.315554], [12.699152, 13.055398, 15.510940], [14.046584, 17.194296, 77.804656], [9.447378, 11.296147, 36.045167], [10.648844, 10.672149, 13.070221]]
### 10
fourier: [[4.889235, 5.180537, 7.507904], [8.359979, 10.108300, 27.183384], [5.826898, 7.278584, 12.171730], [9.180601, 10.809247, 38.987892], [9.571752, 12.078869, 15.872349]]
### 12
fourier: [[5.358761, 5.609772, 10.444850]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.085699,
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],
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],
[
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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],
[
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[
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"network.2.bias": [
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"network.4.weight": [
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],
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[
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[
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[
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[
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"network.12.bias": [
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}
## Activation Signature
### 0
fourier: [[20.310741, 22.052624, 40.358085], [22.073582, 23.196935, 24.600584], [23.293627, 32.301729, 58.846223], [18.513979, 19.663570, 151.569244], [19.225567, 19.542710, 39.587526]]
### 2
fourier: [[12.713145, 12.742390, 25.016730], [10.144624, 11.803950, 86.110905], [15.450435, 16.457355, 44.610065], [9.520614, 11.121974, 24.888166], [10.192778, 10.308768, 14.983267]]
### 4
fourier: [[8.031535, 8.240961, 29.239725], [13.007494, 14.719189, 93.615059], [11.234356, 13.023387, 76.586493], [17.476513, 20.453462, 20.607806], [7.374689, 7.821845, 9.046945]]
### 6
fourier: [[7.845683, 9.619525, 16.604033], [1.818317, 2.026126, 25.677641], [16.681811, 20.168479, 71.608674], [8.228192, 9.072217, 10.538850], [16.086055, 19.436371, 100.257628]]
### 8
fourier: [[4.239980, 4.302854, 62.315554], [12.699152, 13.055398, 15.510940], [14.046584, 17.194296, 77.804656], [9.447378, 11.296147, 36.045167], [10.648844, 10.672149, 13.070221]]
### 10
fourier: [[4.889235, 5.180537, 7.507904], [8.359979, 10.108300, 27.183384], [5.826898, 7.278584, 12.171730], [9.180601, 10.809247, 38.987892], [9.571752, 12.078869, 15.872349]]
### 12
fourier: [[5.358761, 5.609772, 10.444850]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [20.310740963776187, 22.05262416728942, 40.35808524489403]}, "1": {"fourier": [22.07358174774193, 23.19693476865748, 24.60058443985423]}, "2": {"fourier": [23.293627108963477, 32.30172874572969, 58.84622251987457]}, "3": {"fourier": [18.51397939764091, 19.663570493724883, 151.56924384832382]}, "4": {"fourier": [19.22556656462617, 19.542710340337436, 39.58752644062042]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [12.71314497920426, 12.742390238546339, 25.01673012971878]}, "1": {"fourier": [10.14462378778217, 11.803949909872763, 86.11090507358313]}, "2": {"fourier": [15.450435051521914, 16.45735485375466, 44.61006489396095]}, "3": {"fourier": [9.520614409989038, 11.121973575389092, 24.88816626369953]}, "4": {"fourier": [10.192778456686463, 10.308767757063316, 14.983267322182655]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [8.031534550110615, 8.240961094822543, 29.23972486704588]}, "1": {"fourier": [13.007493628042802, 14.719189321335731, 93.61505949497223]}, "2": {"fourier": [11.234355725305722, 13.023386848243478, 76.58649318292737]}, "3": {"fourier": [17.476512896291577, 20.45346225610241, 20.607806489684236]}, "4": {"fourier": [7.3746886174186805, 7.821845015483293, 9.046945186331868]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [7.84568285973584, 9.619524949875265, 16.604033209383488]}, "1": {"fourier": [1.8183169280232592, 2.026126066374951, 25.677640855312347]}, "2": {"fourier": [16.681811171091518, 20.168479477221627, 71.60867389291525]}, "3": {"fourier": [8.228192254900932, 9.07221731918206, 10.538850212455708]}, "4": {"fourier": [16.086055166808155, 19.43637073280284, 100.25762784481049]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [4.239980445157128, 4.302853573459127, 62.31555414199829]}, "1": {"fourier": [12.699152185321276, 13.055398225784302, 15.510939927311137]}, "2": {"fourier": [14.046584200451708, 17.194296074043105, 77.8046559765935]}, "3": {"fourier": [9.447378267197948, 11.296146925992625, 36.04516709595919]}, "4": {"fourier": [10.648843759835767, 10.67214861082918, 13.070221424599966]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [4.889235145174404, 5.180537455882853, 7.507904097437859]}, "1": {"fourier": [8.359979292319876, 10.10829950365534, 27.183384094387293]}, "2": {"fourier": [5.82689799342703, 7.278583609738176, 12.171730048954487]}, "3": {"fourier": [9.180600891977585, 10.809247196060939, 38.98789196461439]}, "4": {"fourier": [9.571752019194696, 12.078868619531669, 15.872349470853806]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [5.358760728286168, 5.609772302645185, 10.44485018402338]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.085699, -0.250134, -0.061916, -0.222805, 0.530398], [-0.179335, -0.216089, -0.248409, 0.340105, 0.451389], [-0.623418, 0.339321, 0.156741, 0.166875, -0.170148], [-0.391366, -0.291775, 0.005171, -0.019727, -0.020203], [-0.330435, 0.18684, 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0.498245]], "network.12.bias": [-0.21425]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6888768672943115, "train_acc": 0.55, "val_loss": 0.6813093423843384, "val_acc": 0.62}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6887668371200562, "train_acc": 0.55, "val_loss": 0.6771432757377625, "val_acc": 0.62}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6881997883319855, "train_acc": 0.55, "val_loss": 0.6641839742660522, "val_acc": 0.62}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6758156418800354, "train_acc": 0.55, "val_loss": 0.6331671476364136, "val_acc": 0.62}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.646536648273468, "train_acc": 0.635, "val_loss": 0.5517563819885254, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.530676931142807, "train_acc": 0.915, "val_loss": 0.3771916329860687, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.36896996200084686, "train_acc": 0.925, "val_loss": 0.22892990708351135, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.24411164224147797, "train_acc": 0.91, "val_loss": 0.23573219776153564, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.20457500964403152, "train_acc": 0.935, "val_loss": 0.23293541371822357, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.21302086114883423, "train_acc": 0.945, "val_loss": 0.23126213252544403, "val_acc": 0.94}], "summary": {"total_epochs": 10, "degraded_epochs": 4, "improved_epochs": 6, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6813093423843384, "final_val_loss": 0.6331671476364136, "initial_val_acc": 0.62, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.5517563819885254, "final_val_loss": 0.23126213252544403, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 4}, "improvement": 0.31999999999999995, "first_improvement_epoch": 3}} |
90 | {"target_pattern": "palindrome", "degraded_accuracy": 0.76, "improved_accuracy": 0.96, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3126, "learning_rate": 0.08469175679902498, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
fourier: [[62.528051, 63.177192, 543.042574], [47.145392, 54.576507, 216.630188], [35.742771, 37.627883, 40.498474], [46.718201, 64.619160, 79.899252], [61.225033, 65.700497, 227.945511], [88.701602, 114.070225, 274.935223], [17.691024, 20.134883, 144.074888]]
### 2
fourier: [[16.410295, 17.326905, 37.926451], [30.443167, 30.906512, 89.363573], [21.512122, 24.640897, 51.668071], [12.675409, 12.817796, 84.666532], [30.210946, 32.485366, 116.626098], [26.527089, 28.047045, 87.243403], [14.571617, 15.587602, 94.342113]]
### 4
fourier: [[26.141850, 28.578987, 30.187237], [65.183538, 69.980599, 280.299962], [96.978575, 103.316532, 323.391921], [33.447610, 35.337442, 121.578933], [91.157576, 99.379790, 345.587290], [117.521921, 124.787341, 383.920288], [40.050164, 42.626478, 128.845516]]
### 6
fourier: [[32.016346, 32.656206, 32.870912], [28.009762, 28.942430, 92.503283], [50.148276, 51.411198, 56.253379], [60.886240, 65.188131, 285.637225], [25.969645, 27.056039, 113.073110], [27.947772, 28.878789, 82.421262], [18.272183, 18.546751, 18.657784]]
### 8
fourier: [[40.815138, 42.454150, 43.979679], [44.032019, 46.109464, 74.059846], [14.631035, 14.997288, 15.983568], [25.623787, 29.156985, 120.394550], [23.011625, 24.072579, 25.094449], [52.508008, 53.576258, 129.492871], [24.068545, 25.265738, 44.825310]]
### 10
fourier: [[31.364971, 32.059287, 156.079061], [70.065467, 70.216119, 195.823707], [24.853268, 25.723016, 112.443366], [8.423035, 9.661783, 16.651580], [52.672669, 54.229122, 220.366430], [71.051210, 72.047848, 303.008629], [58.137792, 59.961263, 63.717290]]
### 12
fourier: [[34.893370, 34.938545, 101.031480]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[62.528051, 63.177192, 543.042574], [47.145392, 54.576507, 216.630188], [35.742771, 37.627883, 40.498474], [46.718201, 64.619160, 79.899252], [61.225033, 65.700497, 227.945511], [88.701602, 114.070225, 274.935223], [17.691024, 20.134883, 144.074888]]
### 2
fourier: [[16.410295, 17.326905, 37.926451], [30.443167, 30.906512, 89.363573], [21.512122, 24.640897, 51.668071], [12.675409, 12.817796, 84.666532], [30.210946, 32.485366, 116.626098], [26.527089, 28.047045, 87.243403], [14.571617, 15.587602, 94.342113]]
### 4
fourier: [[26.141850, 28.578987, 30.187237], [65.183538, 69.980599, 280.299962], [96.978575, 103.316532, 323.391921], [33.447610, 35.337442, 121.578933], [91.157576, 99.379790, 345.587290], [117.521921, 124.787341, 383.920288], [40.050164, 42.626478, 128.845516]]
### 6
fourier: [[32.016346, 32.656206, 32.870912], [28.009762, 28.942430, 92.503283], [50.148276, 51.411198, 56.253379], [60.886240, 65.188131, 285.637225], [25.969645, 27.056039, 113.073110], [27.947772, 28.878789, 82.421262], [18.272183, 18.546751, 18.657784]]
### 8
fourier: [[40.815138, 42.454150, 43.979679], [44.032019, 46.109464, 74.059846], [14.631035, 14.997288, 15.983568], [25.623787, 29.156985, 120.394550], [23.011625, 24.072579, 25.094449], [52.508008, 53.576258, 129.492871], [24.068545, 25.265738, 44.825310]]
### 10
fourier: [[31.364971, 32.059287, 156.079061], [70.065467, 70.216119, 195.823707], [24.853268, 25.723016, 112.443366], [8.423035, 9.661783, 16.651580], [52.672669, 54.229122, 220.366430], [71.051210, 72.047848, 303.008629], [58.137792, 59.961263, 63.717290]]
### 12
fourier: [[34.893370, 34.938545, 101.031480]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [62.528051398953615, 63.17719213628876, 543.0425738096237]}, "1": {"fourier": [47.1453920399648, 54.57650744164643, 216.6301875114441]}, "2": {"fourier": [35.74277147650719, 37.627883299811984, 40.498474047077835]}, "3": {"fourier": [46.718200624455044, 64.61915972822985, 79.89925169944763]}, "4": {"fourier": [61.22503299626329, 65.70049729491475, 227.94551104307175]}, "5": {"fourier": [88.70160217773042, 114.07022523126497, 274.9352234378457]}, "6": {"fourier": [17.69102412677391, 20.134883164404766, 144.07488763332367]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [16.410295015451688, 17.326904706491334, 37.9264507368207]}, "1": {"fourier": [30.44316697731602, 30.906512039440695, 89.36357332766056]}, "2": {"fourier": [21.51212235154767, 24.640897472098114, 51.6680713724345]}, "3": {"fourier": [12.675408899784541, 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"profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [34.893369858600835, 34.9385450562775, 101.03148049116135]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.214092, -0.679822, -1.037934, -0.367883, -0.462947], [-0.697582, 0.401038, -0.006792, -0.264385, -0.914393], [-0.438923, 0.156295, 0.402239, -0.227291, -0.870136], [-1.230903, 0.292435, 0.346116, 0.120095, -0.642618], [-0.135053, -1.142981, 0.666992, -0.714755, -0.7571], [-1.822682, 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-0.747536, -0.761746, -0.295147]], "network.6.bias": [0.500373, 0.318786, 0.734178, -0.79975, 0.427726, 0.208752, 0.160731], "network.8.weight": [[0.846299, -0.215656, 0.688187, -0.827226, -0.315425, -0.663485, 0.715593], [1.027402, -0.387453, 1.185339, -1.012425, -0.130103, -0.618173, 0.477602], [-0.57774, 0.15528, -0.526572, 0.13204, -0.278483, 0.448795, -0.045723], [-0.294274, -0.361051, -0.155267, 0.081408, -0.455607, -0.262745, -0.842828], [0.810096, -0.243077, 0.326384, 0.131251, -0.035105, -0.363238, 0.378071], [-0.293443, 0.708171, -0.511985, 0.068056, 0.521706, 0.475647, -0.741551], [0.751106, 0.017989, 0.411646, 0.536843, -0.471493, -0.188144, 0.65304]], "network.8.bias": [0.821452, 0.882681, 0.078638, 0.055473, -0.067438, 0.182006, -0.323449], "network.10.weight": [[0.034413, 0.276796, 0.336635, -0.335532, -0.246858, -0.623972, -0.287779], [0.892414, 1.106702, -1.03593, 0.208275, 0.632563, -0.207363, -0.107484], [-0.456734, -0.953784, 0.003784, -0.69294, 1.113211, 0.045165, 0.730359], [-0.064254, 0.147564, 0.850885, 0.411931, 0.136392, 0.039181, 0.074985], [0.869879, 1.035445, -0.222322, 0.268897, 0.242614, 0.078912, -0.109439], [0.535074, -0.11304, 0.300918, -0.724871, -0.764016, -1.436825, -0.095029], [-0.478613, -0.906197, 0.18253, -0.916981, 0.140663, 0.755035, 0.066356]], "network.10.bias": [-1.109514, -0.138637, -0.042068, -0.580546, -0.223413, -1.294381, 0.235294], "network.12.weight": [[0.316088, -0.228026, -0.035763, -0.201299, -0.172045, 0.639551, 0.490036]], "network.12.bias": [-0.674935]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.697492390871048, "train_acc": 0.585, "val_loss": 0.7135833501815796, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6806480884552002, "train_acc": 0.585, "val_loss": 0.6081570386886597, "val_acc": 0.76}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6392010152339935, "train_acc": 0.67, "val_loss": 0.5557979345321655, "val_acc": 0.8}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6491268277168274, "train_acc": 0.72, "val_loss": 0.7357564568519592, "val_acc": 0.48}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6945227384567261, "train_acc": 0.51, "val_loss": 0.6851651072502136, "val_acc": 0.5}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.6163231432437897, "train_acc": 0.615, "val_loss": 0.4786622226238251, "val_acc": 0.86}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.5355322659015656, "train_acc": 0.79, "val_loss": 0.4097675681114197, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.540764182806015, "train_acc": 0.8, "val_loss": 0.44005709886550903, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.4858192652463913, "train_acc": 0.805, "val_loss": 0.4690963625907898, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.4714643806219101, "train_acc": 0.825, "val_loss": 0.33844855427742004, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.4454854130744934, "train_acc": 0.855, "val_loss": 0.22968178987503052, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.4308978319168091, "train_acc": 0.825, "val_loss": 0.21233592927455902, "val_acc": 0.96}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7135833501815796, "final_val_loss": 0.6081570386886597, "initial_val_acc": 0.48, "final_val_acc": 0.76, "best_val_acc": 0.76}, "improved_stage": {"initial_val_loss": 0.5557979345321655, "final_val_loss": 0.21233592927455902, "initial_val_acc": 0.8, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.19999999999999996, "first_improvement_epoch": 1}} |
91 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.48, "improved_accuracy": 0.72, "improvement": 0.24, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2106, "learning_rate": 0.07254044620270297, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.084404
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[
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[
0.232155,
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],
"network.0.bias": [
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"network.2.weight": [
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[
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[
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],
"network.2.bias": [
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[
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[
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[
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[
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"network.6.bias": [
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"network.10.weight": [
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"network.10.bias": [
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}
## Activation Signature
### 0
fourier: [[48.214912, 50.059881, 275.601729], [34.139671, 35.462737, 39.829265], [38.636453, 43.304320, 164.651915], [29.472666, 36.844087, 95.897786], [28.671117, 32.770896, 34.279839], [25.032642, 27.078255, 97.171699]]
### 2
fourier: [[43.331121, 47.580031, 122.785494], [38.203421, 40.766630, 181.302867], [13.532292, 14.289982, 14.900453], [5.255060, 6.030823, 60.717752], [9.940032, 10.154901, 68.248699], [17.627643, 18.486061, 25.683676]]
### 4
fourier: [[45.802989, 45.940225, 161.916714], [44.761541, 46.500020, 181.352393], [45.937544, 48.527056, 137.372232], [11.018488, 13.417932, 27.775750], [36.609147, 37.090222, 176.631379], [8.010228, 9.915269, 91.489492]]
### 6
fourier: [[13.761250, 14.444065, 102.946303], [29.615845, 31.186729, 200.707254], [27.083657, 27.415081, 144.770969], [10.039279, 10.742350, 59.806562], [52.832223, 55.631942, 176.176979], [60.806055, 62.037017, 279.256970]]
### 8
fourier: [[19.420380, 20.745705, 57.463414], [6.459341, 6.900152, 79.741911], [18.784637, 20.066577, 74.879656], [17.308478, 18.489678, 57.938376], [0.106794, 0.114082, 11.395215], [22.947426, 24.513452, 65.849418]]
### 10
fourier: [[12.199303, 13.622194, 32.493192]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.043435,
-0.767854,
-0.09435,
-0.435752
],
[
-0.996278,
0.448653,
0.118759,
-0.116514,
0.46587
],
[
0.857853,
-0.458459,
0.265117,
0.274378,
0.084404
],
[
0.594782,
-0.525119,
-0.203093,
-0.383022,
0.331168
],
[
0.232155,
-0.906031,
0.266789,
0.2292,
0.093242
],
[
0.52415,
-0.318446,
0.103771,
0.471691,
0.034065
]
],
"network.0.bias": [
0.01061,
-0.001433,
0.351042,
-0.011654,
0.077426,
-0.262605
],
"network.2.weight": [
[
0.536442,
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0.428316,
0.688927
],
[
0.021333,
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0.541449,
0.561384,
0.211703,
0.305941
],
[
-0.061507,
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0.221064,
0.273047,
-0.027826,
-0.066634
],
[
0.256624,
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-0.255266,
0.196119,
-0.056837,
0.162977
],
[
0.514841,
0.066931,
-0.174843,
0.03123,
0.085414,
-0.145529
],
[
0.014985,
0.464565,
-0.092973,
-0.425695,
0.083758,
-0.18256
]
],
"network.2.bias": [
0.384747,
0.582327,
-0.001817,
-0.175317,
-0.360137,
0.38188
],
"network.4.weight": [
[
0.333556,
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0.516982,
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0.083042,
-0.475021
],
[
0.767416,
0.346101,
0.083804,
-0.099172,
-0.002945,
-0.129381
],
[
0.682719,
0.234878,
0.554007,
0.191083,
0.049496,
-0.620413
],
[
-0.323588,
0.085378,
0.151491,
-0.177171,
-0.003954,
0.450451
],
[
-0.335256,
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-0.096112,
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0.059181
],
[
-0.166327,
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0.136087,
0.354923
]
],
"network.4.bias": [
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],
"network.6.weight": [
[
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[
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[
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[
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0.241791,
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[
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0.038694,
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],
[
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-0.024707,
-0.005796
]
],
"network.6.bias": [
-0.128824,
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-0.244206,
-0.253706,
0.103135,
-0.193759
],
"network.8.weight": [
[
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0.388119,
-0.14169
],
[
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-0.372378,
-0.332729,
0.129091,
0.499252
],
[
0.373487,
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-0.390787,
-0.375414,
-0.131556
],
[
-0.209458,
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-0.082776,
0.082383,
0.345912,
-0.010172
],
[
-0.044391,
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0.002134,
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],
[
-0.031463,
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-0.019076
]
],
"network.8.bias": [
-0.162456,
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-0.131018,
-0.214741
],
"network.10.weight": [
[
-0.39412,
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-0.204455,
-0.054906,
-0.183035
]
],
"network.10.bias": [
-0.117291
]
}
## Activation Signature
### 0
fourier: [[48.214912, 50.059881, 275.601729], [34.139671, 35.462737, 39.829265], [38.636453, 43.304320, 164.651915], [29.472666, 36.844087, 95.897786], [28.671117, 32.770896, 34.279839], [25.032642, 27.078255, 97.171699]]
### 2
fourier: [[43.331121, 47.580031, 122.785494], [38.203421, 40.766630, 181.302867], [13.532292, 14.289982, 14.900453], [5.255060, 6.030823, 60.717752], [9.940032, 10.154901, 68.248699], [17.627643, 18.486061, 25.683676]]
### 4
fourier: [[45.802989, 45.940225, 161.916714], [44.761541, 46.500020, 181.352393], [45.937544, 48.527056, 137.372232], [11.018488, 13.417932, 27.775750], [36.609147, 37.090222, 176.631379], [8.010228, 9.915269, 91.489492]]
### 6
fourier: [[13.761250, 14.444065, 102.946303], [29.615845, 31.186729, 200.707254], [27.083657, 27.415081, 144.770969], [10.039279, 10.742350, 59.806562], [52.832223, 55.631942, 176.176979], [60.806055, 62.037017, 279.256970]]
### 8
fourier: [[19.420380, 20.745705, 57.463414], [6.459341, 6.900152, 79.741911], [18.784637, 20.066577, 74.879656], [17.308478, 18.489678, 57.938376], [0.106794, 0.114082, 11.395215], [22.947426, 24.513452, 65.849418]]
### 10
fourier: [[12.199303, 13.622194, 32.493192]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [48.214912104185245, 50.05988062150782, 275.6017291676253]}, "1": {"fourier": [34.139671302798284, 35.46273652725086, 39.82926481329774]}, "2": {"fourier": [38.636452662583785, 43.304319635674624, 164.6519154906273]}, "3": {"fourier": [29.472665802421222, 36.84408700287261, 95.89778555929661]}, "4": {"fourier": [28.671117177886945, 32.770896487791504, 34.27983943899535]}, "5": {"fourier": [25.03264244419499, 27.078254588238075, 97.17169913649559]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [43.33112146009581, 47.580030602405586, 122.78549388051033]}, "1": {"fourier": [38.2034212347508, 40.766630248967274, 181.3028669655323]}, "2": {"fourier": [13.532291980481965, 14.28998156104689, 14.900453275069594]}, "3": {"fourier": [5.255059767830409, 6.030823307274514, 60.717752143740654]}, "4": {"fourier": [9.940032094315338, 10.154901334564556, 68.24869881570339]}, "5": {"fourier": [17.627642965050846, 18.486061473020886, 25.683676436543465]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [45.80298906017403, 45.940224611834445, 161.9167144447565]}, "1": {"fourier": [44.76154082866112, 46.50001959492743, 181.3523931130767]}, "2": {"fourier": [45.93754380285236, 48.5270558833087, 137.37223178893328]}, "3": {"fourier": [11.018487787855822, 13.417932378462599, 27.77575020492077]}, "4": {"fourier": [36.60914675431856, 37.09022209120177, 176.6313793361187]}, "5": {"fourier": [8.010228230069579, 9.915269186200337, 91.48949187994003]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [13.761250267205163, 14.444065146236605, 102.94630348682404]}, "1": {"fourier": [29.61584488909527, 31.18672893851295, 200.70725405216217]}, "2": {"fourier": [27.083656588018354, 27.415080682772533, 144.77096903324127]}, "3": {"fourier": [10.039278980680058, 10.742350411512025, 59.80656227469444]}, "4": {"fourier": [52.832223146585974, 55.631941675469974, 176.1769793778658]}, "5": {"fourier": [60.806055105782455, 62.037017085462615, 279.25697016716003]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [19.42037982587384, 20.745705125136496, 57.46341370046139]}, "1": {"fourier": [6.45934060472786, 6.900152144929388, 79.7419114112854]}, "2": {"fourier": [18.784636960708767, 20.066577132632624, 74.8796557188034]}, "3": {"fourier": [17.30847773803546, 18.48967836180295, 57.93837584555149]}, "4": {"fourier": [0.10679389151720163, 0.11408190073249379, 11.395214773714542]}, "5": {"fourier": [22.947425976131115, 24.513451857682384, 65.84941823780537]}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [12.199303395242536, 13.622194186367093, 32.493192449212074]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.52231, -0.043435, -0.767854, -0.09435, -0.435752], [-0.996278, 0.448653, 0.118759, -0.116514, 0.46587], [0.857853, -0.458459, 0.265117, 0.274378, 0.084404], [0.594782, -0.525119, -0.203093, -0.383022, 0.331168], [0.232155, -0.906031, 0.266789, 0.2292, 0.093242], [0.52415, -0.318446, 0.103771, 0.471691, 0.034065]], "network.0.bias": [0.01061, -0.001433, 0.351042, -0.011654, 0.077426, -0.262605], "network.2.weight": [[0.536442, -0.750934, 0.176004, 0.807503, 0.428316, 0.688927], [0.021333, -0.254257, 0.541449, 0.561384, 0.211703, 0.305941], [-0.061507, -0.288866, 0.221064, 0.273047, -0.027826, -0.066634], [0.256624, -0.300504, -0.255266, 0.196119, -0.056837, 0.162977], [0.514841, 0.066931, -0.174843, 0.03123, 0.085414, -0.145529], [0.014985, 0.464565, -0.092973, -0.425695, 0.083758, -0.18256]], "network.2.bias": [0.384747, 0.582327, -0.001817, -0.175317, -0.360137, 0.38188], "network.4.weight": [[0.333556, 0.590812, 0.516982, -0.229569, 0.083042, -0.475021], [0.767416, 0.346101, 0.083804, -0.099172, -0.002945, -0.129381], [0.682719, 0.234878, 0.554007, 0.191083, 0.049496, -0.620413], [-0.323588, 0.085378, 0.151491, -0.177171, -0.003954, 0.450451], [-0.335256, -0.564823, -0.096112, -0.1819, -0.269581, 0.059181], [-0.166327, 0.469659, -0.055432, -0.458364, 0.136087, 0.354923]], "network.4.bias": [0.144461, 0.122779, 0.091026, 0.377327, -0.283342, 0.173537], "network.6.weight": [[-0.093365, 0.024536, -0.262411, -0.344827, 0.300324, -0.295235], [-0.161264, -0.270436, -0.173943, -0.285129, -0.109156, -0.692504], [-0.069314, -0.078035, -0.422411, -0.045139, -0.532557, -0.338895], [0.233976, -0.22772, -0.151588, 0.241791, 0.051544, -0.230527], [0.319462, 0.404518, 0.449659, -0.447242, 0.038694, -0.125397], [-0.461517, -0.594801, -0.397496, -0.399089, -0.024707, -0.005796]], "network.6.bias": [-0.128824, -0.264039, -0.244206, -0.253706, 0.103135, -0.193759], "network.8.weight": [[0.324917, 0.01778, 0.162649, -0.303867, 0.388119, -0.14169], [0.362703, -0.329068, -0.372378, -0.332729, 0.129091, 0.499252], [0.373487, 0.369959, 0.259153, -0.390787, -0.375414, -0.131556], [-0.209458, -0.126773, -0.082776, 0.082383, 0.345912, -0.010172], [-0.044391, 0.075589, -0.367049, -0.122779, 0.002134, 0.326082], [-0.031463, -0.125708, 0.038126, 0.009347, 0.458608, -0.019076]], "network.8.bias": [-0.162456, 0.619624, -0.057277, -0.070079, -0.131018, -0.214741], "network.10.weight": [[-0.39412, 0.350028, -0.039267, -0.204455, -0.054906, -0.183035]], "network.10.bias": [-0.117291]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6908522844314575, "train_acc": 0.575, "val_loss": 0.71909499168396, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6858526468276978, "train_acc": 0.575, "val_loss": 0.7130639553070068, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6919388771057129, "train_acc": 0.575, "val_loss": 0.6913810968399048, "val_acc": 0.48}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6651918888092041, "train_acc": 0.575, "val_loss": 0.659534215927124, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.792389839887619, "train_acc": 0.505, "val_loss": 0.6086311340332031, "val_acc": 0.72}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.6326349675655365, "train_acc": 0.695, "val_loss": 0.6656363010406494, "val_acc": 0.58}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.6823007762432098, "train_acc": 0.55, "val_loss": 0.6720402240753174, "val_acc": 0.58}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.6906833946704865, "train_acc": 0.54, "val_loss": 0.6529371738433838, "val_acc": 0.66}], "summary": {"total_epochs": 8, "degraded_epochs": 4, "improved_epochs": 4, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.71909499168396, "final_val_loss": 0.659534215927124, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6086311340332031, "final_val_loss": 0.6529371738433838, "initial_val_acc": 0.72, "final_val_acc": 0.66, "best_val_acc": 0.72, "best_epoch": 4}, "improvement": 0.24, "first_improvement_epoch": 3}} |
92 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.78, "improved_accuracy": 0.94, "improvement": 0.15999999999999992, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4908, "learning_rate": 0.07820043132053234, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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"network.0.bias": [
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[
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[
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[
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],
"network.2.bias": [
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"network.4.weight": [
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[
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[
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[
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"network.4.bias": [
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[
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[
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[
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[
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0.003756,
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],
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[
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0.318,
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],
[
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0.153204,
0.401777,
-0.036744,
0.029508
],
[
0.271987,
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0.268918
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[
-0.176356,
0.039516,
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0.005378,
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],
[
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],
"network.10.bias": [
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1.128407,
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],
"network.12.weight": [
[
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-1.441604,
0.326812,
0.374145
]
],
"network.12.bias": [
-0.126338
]
}
## Activation Signature
### 0
fourier: [[19.973504, 20.731803, 121.958336], [61.889126, 71.070799, 231.956106], [44.802142, 45.257286, 260.078093], [60.172321, 63.032361, 244.192401], [49.692999, 53.084521, 134.779332]]
### 2
fourier: [[10.883165, 12.488196, 93.889072], [6.015749, 7.568837, 32.715880], [48.103776, 61.500221, 153.508359], [45.233375, 54.506420, 168.637224], [53.888624, 68.854469, 137.159692]]
### 4
fourier: [[35.239342, 35.574451, 42.213792], [18.609647, 18.658487, 36.105060], [10.386463, 10.589741, 27.642513], [19.265212, 19.551190, 79.557702], [9.305605, 9.589933, 37.822969]]
### 6
fourier: [[2.944179, 3.016879, 12.305675], [34.031616, 34.871952, 72.099765], [11.723275, 12.385133, 12.690957], [8.062007, 8.261081, 48.437438], [12.829773, 13.146577, 45.577418]]
### 8
fourier: [[15.109682, 15.485253, 76.558619], [4.932428, 5.060012, 24.269268], [24.071131, 24.637805, 34.766333], [13.619154, 13.963632, 50.139166], [7.031693, 7.203886, 48.684745]]
### 10
fourier: [[5.491516, 5.637418, 6.152984], [9.180096, 9.619556, 9.875135], [11.686183, 11.996669, 83.871456], [0.169195, 0.173690, 9.830208], [0.330227, 0.339001, 25.792718]]
### 12
fourier: [[12.939608, 13.653727, 136.367342]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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],
[
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],
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
[
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],
[
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0.36394,
0.30798
],
[
0.272861,
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0.302036
],
[
0.20717,
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0.438417
]
],
"network.2.bias": [
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0.13657,
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0.502472
],
"network.4.weight": [
[
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0.311543,
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],
[
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],
[
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],
[
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],
[
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]
],
"network.4.bias": [
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],
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],
[
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[
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],
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[
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[
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],
[
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],
[
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],
"network.10.bias": [
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],
"network.12.weight": [
[
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]
],
"network.12.bias": [
-0.126338
]
}
## Activation Signature
### 0
fourier: [[19.973504, 20.731803, 121.958336], [61.889126, 71.070799, 231.956106], [44.802142, 45.257286, 260.078093], [60.172321, 63.032361, 244.192401], [49.692999, 53.084521, 134.779332]]
### 2
fourier: [[10.883165, 12.488196, 93.889072], [6.015749, 7.568837, 32.715880], [48.103776, 61.500221, 153.508359], [45.233375, 54.506420, 168.637224], [53.888624, 68.854469, 137.159692]]
### 4
fourier: [[35.239342, 35.574451, 42.213792], [18.609647, 18.658487, 36.105060], [10.386463, 10.589741, 27.642513], [19.265212, 19.551190, 79.557702], [9.305605, 9.589933, 37.822969]]
### 6
fourier: [[2.944179, 3.016879, 12.305675], [34.031616, 34.871952, 72.099765], [11.723275, 12.385133, 12.690957], [8.062007, 8.261081, 48.437438], [12.829773, 13.146577, 45.577418]]
### 8
fourier: [[15.109682, 15.485253, 76.558619], [4.932428, 5.060012, 24.269268], [24.071131, 24.637805, 34.766333], [13.619154, 13.963632, 50.139166], [7.031693, 7.203886, 48.684745]]
### 10
fourier: [[5.491516, 5.637418, 6.152984], [9.180096, 9.619556, 9.875135], [11.686183, 11.996669, 83.871456], [0.169195, 0.173690, 9.830208], [0.330227, 0.339001, 25.792718]]
### 12
fourier: [[12.939608, 13.653727, 136.367342]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [19.97350380454423, 20.731803068089743, 121.95833633840084]}, "1": {"fourier": [61.889125895918, 71.07079875353476, 231.9561061859131]}, "2": {"fourier": [44.80214229083198, 45.25728571397554, 260.0780931264162]}, "3": {"fourier": [60.17232139708573, 63.03236065796051, 244.1924007833004]}, "4": {"fourier": [49.69299900428033, 53.08452075948085, 134.77933153510094]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [10.883165347007708, 12.4881963302965, 93.88907206058502]}, "1": {"fourier": [6.015748636540671, 7.56883677017004, 32.7158800791949]}, "2": {"fourier": [48.10377574011958, 61.50022137338616, 153.50835919380188]}, "3": {"fourier": [45.233374884945526, 54.50642011535843, 168.63722431659698]}, "4": {"fourier": [53.88862360274421, 68.85446937130914, 137.15969240665436]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [35.23934165877578, 35.57445089945968, 42.213792368769646]}, "1": {"fourier": [18.609647187021256, 18.658487487010653, 36.10505993664265]}, "2": {"fourier": [10.386462618932834, 10.589741183369734, 27.642512507736683]}, "3": {"fourier": [19.2652115054348, 19.551189608168706, 79.55770182609558]}, "4": {"fourier": [9.305605315236795, 9.589932916733597, 37.8229688256979]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [2.944179308723616, 3.01687934919933, 12.305674776434898]}, "1": {"fourier": [34.031615558025926, 34.87195242678646, 72.09976464509964]}, "2": {"fourier": [11.723275057840544, 12.385133156414566, 12.690957179029352]}, "3": {"fourier": [8.062007319335317, 8.261081059748081, 48.4374378323555]}, "4": {"fourier": [12.829773080681269, 13.146576514423923, 45.57741802930832]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [15.109681622554993, 15.485253067291383, 76.55861914157867]}, "1": {"fourier": [4.932428067088173, 5.060012247688763, 24.26926825940609]}, "2": {"fourier": [24.071131011591227, 24.63780468216521, 34.76633267104626]}, "3": {"fourier": [13.61915432715143, 13.96363196092857, 50.1391661465168]}, "4": {"fourier": [7.0316927920359396, 7.203885825455552, 48.684745252132416]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [5.491515540718849, 5.637417619027588, 6.1529838517308235]}, "1": {"fourier": [9.180096012512893, 9.619556464513355, 9.875134960773476]}, "2": {"fourier": [11.686183429852894, 11.996669320424164, 83.87145614624023]}, "3": {"fourier": [0.16919503602090036, 0.17369032706568022, 9.830208487808704]}, "4": {"fourier": [0.3302273172654127, 0.3390010647714716, 25.792717784643173]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [12.93960836690112, 13.653726551246622, 136.3673419058323]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.151775, -0.059857, -0.068186, -0.095639, -0.394961], [-1.141669, -0.651772, -0.587295, 0.324206, 0.667087], [0.895158, 0.713608, 0.137016, -0.079878, -0.011579], [-0.73946, -1.314276, -0.448481, 0.356965, 0.498411], [-0.728066, -0.815816, 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0.374145]], "network.12.bias": [-0.126338]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7002740502357483, "train_acc": 0.465, "val_loss": 0.6883068680763245, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6886576414108276, "train_acc": 0.535, "val_loss": 0.687092125415802, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.7011158466339111, "train_acc": 0.535, "val_loss": 0.6779125928878784, "val_acc": 0.56}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6616133749485016, "train_acc": 0.615, "val_loss": 0.6785508990287781, "val_acc": 0.54}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6523878574371338, "train_acc": 0.62, "val_loss": 0.5955080389976501, "val_acc": 0.78}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6560131311416626, "train_acc": 0.705, "val_loss": 0.5432506203651428, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5435979068279266, "train_acc": 0.78, "val_loss": 0.5394535660743713, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5343502014875412, "train_acc": 0.755, "val_loss": 0.41592520475387573, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.45641475915908813, "train_acc": 0.825, "val_loss": 0.3890894651412964, "val_acc": 0.86}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.44187501072883606, "train_acc": 0.82, "val_loss": 0.2841700613498688, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.3897191882133484, "train_acc": 0.86, "val_loss": 0.31424471735954285, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.35870838165283203, "train_acc": 0.87, "val_loss": 0.2705923020839691, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.34277598559856415, "train_acc": 0.875, "val_loss": 0.24122856557369232, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.31535616517066956, "train_acc": 0.88, "val_loss": 0.23902274668216705, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.3011222183704376, "train_acc": 0.885, "val_loss": 0.24854713678359985, "val_acc": 0.92}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.6883068680763245, "final_val_loss": 0.5955080389976501, "initial_val_acc": 0.56, "final_val_acc": 0.78, "best_val_acc": 0.78}, "improved_stage": {"initial_val_loss": 0.5432506203651428, "final_val_loss": 0.24854713678359985, "initial_val_acc": 0.82, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 9}, "improvement": 0.15999999999999992, "first_improvement_epoch": 4}} |
93 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.78, "improved_accuracy": 0.98, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 5156, "learning_rate": 0.08113196529052372, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.00124,
-0.262231,
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0.036731
],
[
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[
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[
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[
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],
"network.0.bias": [
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],
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[
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],
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],
[
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[
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],
[
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]
],
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],
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],
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[
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[
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]
],
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],
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[
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],
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[
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],
[
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],
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]
],
"network.8.bias": [
-0.309587
]
}
## Activation Signature
### 0
fourier: [[21.954760, 26.265108, 59.948320], [47.014939, 47.991434, 233.028178], [43.642052, 43.879102, 44.315559], [36.731545, 36.773745, 147.696569], [37.371200, 38.066446, 131.694934]]
### 2
fourier: [[23.320107, 23.328932, 154.381971], [26.912793, 26.916240, 60.053966], [27.632373, 33.871999, 36.726737], [20.409656, 22.019811, 94.593671], [31.265392, 34.986276, 233.544861]]
### 4
fourier: [[7.128754, 7.320560, 18.546121], [52.163293, 61.839846, 173.034726], [29.659449, 34.472964, 101.074820], [38.528508, 47.087883, 139.030399], [36.703430, 44.315080, 123.086781]]
### 6
fourier: [[9.312739, 11.435182, 85.053781], [11.943123, 14.507672, 95.581179], [12.217963, 12.632114, 14.947214], [11.068562, 13.671386, 106.343494], [3.833140, 4.099316, 27.686455]]
### 8
fourier: [[43.090604, 52.633940, 320.773335]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.00124,
-0.262231,
0.587563,
0.320827,
0.036731
],
[
0.968635,
0.358314,
0.367164,
0.204328,
-0.140848
],
[
0.192384,
0.366224,
-1.246834,
0.275399,
0.058999
],
[
-0.990175,
-0.393953,
0.299336,
-0.103936,
-0.026939
],
[
-0.894725,
-0.444849,
0.001336,
0.001593,
-0.011045
]
],
"network.0.bias": [
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-0.30056,
0.61434,
-0.060154,
0.468186
],
"network.2.weight": [
[
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1.131588,
-0.103683,
0.054021
],
[
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0.334073,
0.561816,
-0.295849,
-0.059512
],
[
-1.261434,
0.359897,
0.553083,
-0.455273,
-0.171598
],
[
0.278404,
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0.617258,
-0.112632,
0.1622
],
[
-0.394822,
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-0.373415,
-0.324668,
-0.504058
]
],
"network.2.bias": [
-0.121226,
0.127523,
-0.140598,
-0.503144,
-0.437875
],
"network.4.weight": [
[
-0.044614,
-0.125098,
-0.066034,
-0.1559,
0.152384
],
[
-0.521298,
-1.186484,
-0.93214,
-0.229023,
-0.873085
],
[
-0.174462,
-0.695981,
-0.470205,
-0.316156,
-0.453831
],
[
-0.290974,
-0.975618,
-0.761627,
-0.128361,
-0.579226
],
[
-0.346887,
-0.714346,
-0.865809,
-0.097153,
-0.685844
]
],
"network.4.bias": [
0.172709,
0.601811,
0.283696,
0.250385,
0.337799
],
"network.6.weight": [
[
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-0.630348,
-0.701639,
-1.219501,
-0.829516
],
[
-0.699372,
-1.135098,
-0.656306,
-1.165011,
-1.173493
],
[
0.295149,
1.390466,
0.811636,
0.814412,
1.252894
],
[
-0.79403,
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-0.77015,
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-1.259827
],
[
0.476498,
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0.481631,
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]
],
"network.6.bias": [
0.950043,
1.109811,
-0.010114,
1.21426,
0.357853
],
"network.8.weight": [
[
-0.945312,
-1.19102,
1.224686,
-1.298455,
-0.187694
]
],
"network.8.bias": [
-0.309587
]
}
## Activation Signature
### 0
fourier: [[21.954760, 26.265108, 59.948320], [47.014939, 47.991434, 233.028178], [43.642052, 43.879102, 44.315559], [36.731545, 36.773745, 147.696569], [37.371200, 38.066446, 131.694934]]
### 2
fourier: [[23.320107, 23.328932, 154.381971], [26.912793, 26.916240, 60.053966], [27.632373, 33.871999, 36.726737], [20.409656, 22.019811, 94.593671], [31.265392, 34.986276, 233.544861]]
### 4
fourier: [[7.128754, 7.320560, 18.546121], [52.163293, 61.839846, 173.034726], [29.659449, 34.472964, 101.074820], [38.528508, 47.087883, 139.030399], [36.703430, 44.315080, 123.086781]]
### 6
fourier: [[9.312739, 11.435182, 85.053781], [11.943123, 14.507672, 95.581179], [12.217963, 12.632114, 14.947214], [11.068562, 13.671386, 106.343494], [3.833140, 4.099316, 27.686455]]
### 8
fourier: [[43.090604, 52.633940, 320.773335]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [21.954759974225453, 26.265108097851222, 59.94832020998001]}, "1": {"fourier": [47.01493854438025, 47.99143377694469, 233.0281783938408]}, "2": {"fourier": [43.64205188991232, 43.87910181452599, 44.31555891037419]}, "3": {"fourier": [36.7315451434126, 36.773745133188946, 147.69656871259212]}, "4": {"fourier": [37.37120025727013, 38.066445684394964, 131.69493395090103]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [23.32010684424919, 23.328932176068495, 154.38197146356106]}, "1": {"fourier": [26.912792858403364, 26.916240412298503, 60.05396576970816]}, "2": {"fourier": [27.632372893208537, 33.87199862954091, 36.726737105945745]}, "3": {"fourier": [20.409656102372114, 22.019811008950644, 94.59367051720619]}, "4": {"fourier": [31.26539233672714, 34.986276308800214, 233.5448606312275]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [7.128753909952957, 7.3205599783395225, 18.546120829880238]}, "1": {"fourier": [52.163293133774026, 61.83984601073375, 173.034726023674]}, "2": {"fourier": [29.659449395013482, 34.47296426355061, 101.07481986284256]}, "3": {"fourier": [38.52850780355242, 47.087882517815125, 139.03039894998074]}, "4": {"fourier": [36.703430120214435, 44.315080105474614, 123.08678084611893]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [9.312739420302185, 11.435181681101598, 85.053780823946]}, "1": {"fourier": [11.943122690570222, 14.507671664848393, 95.58117938041687]}, "2": {"fourier": [12.21796289566397, 12.632113696383723, 14.947214272884171]}, "3": {"fourier": [11.068562353072378, 13.671385894044509, 106.34349364042282]}, "4": {"fourier": [3.8331404749807656, 4.099316065919815, 27.686454966664314]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [43.090604438937426, 52.63393988689838, 320.77333521842957]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.00124, -0.262231, 0.587563, 0.320827, 0.036731], [0.968635, 0.358314, 0.367164, 0.204328, -0.140848], [0.192384, 0.366224, -1.246834, 0.275399, 0.058999], [-0.990175, -0.393953, 0.299336, -0.103936, -0.026939], [-0.894725, -0.444849, 0.001336, 0.001593, 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1.252894], [-0.79403, -0.922547, -0.77015, -0.919317, -1.259827], [0.476498, -0.391167, 0.481631, -0.611114, -0.885525]], "network.6.bias": [0.950043, 1.109811, -0.010114, 1.21426, 0.357853], "network.8.weight": [[-0.945312, -1.19102, 1.224686, -1.298455, -0.187694]], "network.8.bias": [-0.309587]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7169036567211151, "train_acc": 0.41, "val_loss": 0.6886897087097168, "val_acc": 0.74}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6782347857952118, "train_acc": 0.725, "val_loss": 0.7037112712860107, "val_acc": 0.42}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6473712623119354, "train_acc": 0.59, "val_loss": 0.6739474534988403, "val_acc": 0.42}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.5782712399959564, "train_acc": 0.59, "val_loss": 0.5635495781898499, "val_acc": 0.78}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.53939089179039, "train_acc": 0.78, "val_loss": 0.4777399003505707, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.38093438744544983, "train_acc": 0.855, "val_loss": 0.5328484177589417, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.39450494945049286, "train_acc": 0.835, "val_loss": 0.22884070873260498, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.2772766202688217, "train_acc": 0.915, "val_loss": 0.3066211938858032, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.2397649586200714, "train_acc": 0.92, "val_loss": 0.20296259224414825, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.1396372765302658, "train_acc": 0.955, "val_loss": 0.15614719688892365, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.13156352937221527, "train_acc": 0.955, "val_loss": 0.11676246672868729, "val_acc": 0.98}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.10111672431230545, "train_acc": 0.97, "val_loss": 0.1099473312497139, "val_acc": 0.98}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.09141432121396065, "train_acc": 0.98, "val_loss": 0.09517601132392883, "val_acc": 0.98}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.0702281016856432, "train_acc": 0.98, "val_loss": 0.06967326998710632, "val_acc": 0.98}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.6886897087097168, "final_val_loss": 0.5635495781898499, "initial_val_acc": 0.74, "final_val_acc": 0.78, "best_val_acc": 0.78}, "improved_stage": {"initial_val_loss": 0.4777399003505707, "final_val_loss": 0.06967326998710632, "initial_val_acc": 0.76, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 10}, "improvement": 0.19999999999999996, "first_improvement_epoch": 3}} |
94 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.58, "improved_accuracy": 0.92, "improvement": 0.3400000000000001, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5234, "learning_rate": 0.05054527604583981, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[58.111335, 58.217811, 214.541269], [67.457662, 71.650796, 155.394221], [46.081251, 46.094809, 235.680600], [26.460029, 26.990959, 34.187274], [20.167979, 22.689711, 70.374858], [35.967844, 38.040645, 232.309420], [37.916056, 45.681913, 126.437193]]
### 2
fourier: [[53.889385, 54.883581, 235.564635], [12.629242, 13.524897, 114.059087], [37.751135, 39.793977, 182.401848], [17.466745, 19.854639, 78.810922], [10.098843, 10.599981, 72.629778], [36.624687, 45.067080, 142.964457], [37.201921, 40.285185, 192.832336]]
### 4
fourier: [[25.008989, 26.735487, 160.383916], [25.447217, 27.044871, 149.268399], [37.379165, 40.280480, 220.105696], [54.891959, 55.494947, 259.229491], [49.171777, 50.122769, 207.256532], [19.775748, 20.835841, 139.978503], [33.595685, 35.497118, 217.631248]]
### 6
fourier: [[37.051948, 40.357856, 194.115537], [1.216552, 1.455835, 35.992377], [20.676963, 21.829124, 103.601811], [37.672367, 40.033318, 211.584645], [19.524643, 20.390882, 98.433646], [26.316001, 27.833487, 152.550767], [3.111957, 3.278729, 48.127530]]
### 8
fourier: [[40.348190, 43.913464, 236.569253], [22.301772, 23.582832, 125.153791], [19.278990, 20.815299, 170.569922], [44.864785, 48.793803, 261.583724], [22.461867, 24.200664, 120.056623], [42.690148, 46.194582, 233.534002], [46.657207, 50.599647, 231.592286]]
### 10
fourier: [[15.300623, 16.619988, 81.084138], [40.430574, 43.808247, 227.302537], [20.742522, 22.463476, 135.302258], [64.516004, 70.010868, 339.215204], [51.970994, 56.425044, 294.100478], [6.573520, 7.101282, 60.808829], [22.192548, 24.040499, 131.675802]]
### 12
fourier: [[47.885428, 51.939562, 195.150556]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[58.111335, 58.217811, 214.541269], [67.457662, 71.650796, 155.394221], [46.081251, 46.094809, 235.680600], [26.460029, 26.990959, 34.187274], [20.167979, 22.689711, 70.374858], [35.967844, 38.040645, 232.309420], [37.916056, 45.681913, 126.437193]]
### 2
fourier: [[53.889385, 54.883581, 235.564635], [12.629242, 13.524897, 114.059087], [37.751135, 39.793977, 182.401848], [17.466745, 19.854639, 78.810922], [10.098843, 10.599981, 72.629778], [36.624687, 45.067080, 142.964457], [37.201921, 40.285185, 192.832336]]
### 4
fourier: [[25.008989, 26.735487, 160.383916], [25.447217, 27.044871, 149.268399], [37.379165, 40.280480, 220.105696], [54.891959, 55.494947, 259.229491], [49.171777, 50.122769, 207.256532], [19.775748, 20.835841, 139.978503], [33.595685, 35.497118, 217.631248]]
### 6
fourier: [[37.051948, 40.357856, 194.115537], [1.216552, 1.455835, 35.992377], [20.676963, 21.829124, 103.601811], [37.672367, 40.033318, 211.584645], [19.524643, 20.390882, 98.433646], [26.316001, 27.833487, 152.550767], [3.111957, 3.278729, 48.127530]]
### 8
fourier: [[40.348190, 43.913464, 236.569253], [22.301772, 23.582832, 125.153791], [19.278990, 20.815299, 170.569922], [44.864785, 48.793803, 261.583724], [22.461867, 24.200664, 120.056623], [42.690148, 46.194582, 233.534002], [46.657207, 50.599647, 231.592286]]
### 10
fourier: [[15.300623, 16.619988, 81.084138], [40.430574, 43.808247, 227.302537], [20.742522, 22.463476, 135.302258], [64.516004, 70.010868, 339.215204], [51.970994, 56.425044, 294.100478], [6.573520, 7.101282, 60.808829], [22.192548, 24.040499, 131.675802]]
### 12
fourier: [[47.885428, 51.939562, 195.150556]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [58.111335159980605, 58.21781102459469, 214.54126869142056]}, "1": {"fourier": [67.45766168459383, 71.65079631673504, 155.39422146230936]}, "2": {"fourier": [46.08125054004752, 46.09480857922479, 235.6806000471115]}, "3": {"fourier": [26.46002931629041, 26.990959326431756, 34.18727373930164]}, "4": {"fourier": [20.16797859331106, 22.689710973983754, 70.37485791742802]}, "5": {"fourier": [35.9678440011358, 38.040644692047884, 232.30942042171955]}, "6": {"fourier": [37.91605598056193, 45.68191281360272, 126.43719321489334]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [53.88938486972609, 54.88358095928782, 235.5646349787712]}, "1": {"fourier": [12.62924188277674, 13.524897448494857, 114.05908712744713]}, "2": {"fourier": [37.751134542184175, 39.793977316824126, 182.40184766799212]}, "3": {"fourier": [17.466744927759255, 19.854639256418988, 78.81092220544815]}, "4": {"fourier": [10.098843205337817, 10.59998085790702, 72.62977766990662]}, "5": {"fourier": [36.6246866451221, 45.06708047440709, 142.96445711702108]}, "6": {"fourier": [37.20192053628262, 40.28518541545448, 192.8323363661766]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [25.008988707816854, 26.735486698585294, 160.3839156627655]}, "1": {"fourier": [25.44721675436079, 27.044870710750228, 149.2683993279934]}, "2": {"fourier": [37.379164937318976, 40.280480012501926, 220.10569623112679]}, "3": {"fourier": [54.89195917750433, 55.49494706986036, 259.22949086036533]}, "4": {"fourier": [49.17177725112114, 50.12276947842091, 207.2565322816372]}, "5": {"fourier": [19.77574832270717, 20.835841463134965, 139.97850300371647]}, "6": {"fourier": [33.59568502285608, 35.497118095936905, 217.6312476694584]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [37.05194803776239, 40.357856194817266, 194.11553705483675]}, "1": {"fourier": [1.216552078899488, 1.4558345199218279, 35.99237661063671]}, "2": {"fourier": [20.6769630979305, 21.82912350720252, 103.60181089490652]}, "3": {"fourier": [37.67236711639122, 40.03331803530408, 211.58464507758617]}, "4": {"fourier": [19.52464304108426, 20.390881799998567, 98.43364628776908]}, "5": {"fourier": [26.316000760475582, 27.83348652910337, 152.55076725035906]}, "6": {"fourier": [3.1119566294155376, 3.2787291967052603, 48.12752968072891]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [40.34818960791949, 43.91346374201417, 236.56925348937511]}, "1": {"fourier": [22.30177186662598, 23.58283172897652, 125.15379058942199]}, "2": {"fourier": [19.278990256269996, 20.81529914237465, 170.56992173194885]}, "3": {"fourier": [44.864785042493246, 48.79380289069674, 261.5837240666151]}, "4": {"fourier": [22.461867217056902, 24.200663816016252, 120.05662317760289]}, "5": {"fourier": [42.69014816255312, 46.194581998522736, 233.53400232829154]}, "6": {"fourier": [46.657206527018474, 50.59964700336385, 231.59228593111038]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [15.300623341921206, 16.619987693304125, 81.08413808047771]}, "1": {"fourier": [40.430574371795814, 43.80824663735675, 227.30253748223186]}, "2": {"fourier": [20.7425220176393, 22.46347640862696, 135.302257925272]}, "3": {"fourier": [64.51600364095447, 70.01086777819225, 339.2152043581009]}, "4": {"fourier": [51.97099379989966, 56.42504422785408, 294.10047828033566]}, "5": {"fourier": [6.573519639463393, 7.1012820431981725, 60.80882865190506]}, "6": {"fourier": [22.192547511769757, 24.040498840000172, 131.67580205574632]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [47.885428260912995, 51.93956206419543, 195.15055632591248]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-1.25297, -0.81243, 0.14394, 0.272992, -0.373397], [-1.563611, -0.980623, 0.314264, 0.54979, 0.01556], [0.861295, 0.921161, -0.084531, -0.334874, 0.301194], [0.259404, 0.008736, 0.362831, -0.590795, 0.246719], [-0.377395, -0.435032, 0.275861, 0.051013, -0.140161], 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"improved_epochs": 10, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6806833744049072, "final_val_loss": 0.6205902099609375, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.5824960470199585, "final_val_loss": 0.3239425718784332, "initial_val_acc": 0.58, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 14}, "improvement": 0.3400000000000001, "first_improvement_epoch": 4}} |
95 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.74, "improved_accuracy": 0.9, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1800, "learning_rate": 0.05216234752909743, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[35.787622, 38.017128, 254.939651], [22.191931, 28.297942, 70.120876], [28.225901, 30.198035, 128.850183], [11.319971, 12.356982, 67.568346], [35.312971, 37.388067, 49.191990], [26.489192, 30.083355, 89.615885], [27.352782, 27.807132, 33.756521], [20.288933, 20.759382, 146.685353]]
### 2
fourier: [[7.006416, 7.685548, 31.299159], [14.202715, 16.442129, 111.343258], [17.660867, 19.201329, 123.857132], [15.982153, 18.244307, 103.493047], [21.847283, 27.682087, 40.115086], [11.393620, 11.638069, 12.074533], [13.576581, 15.227027, 18.400178], [14.436756, 15.302996, 89.185467]]
### 4
fourier: [[19.864482, 22.887259, 151.724524], [7.614840, 8.368870, 101.260050], [1.829631, 2.382055, 10.886313], [18.158060, 19.540669, 159.133197], [16.839603, 22.006056, 65.701356], [5.646381, 5.838451, 75.228835], [7.008719, 8.529315, 61.743483], [19.869483, 25.926057, 45.865893]]
### 6
fourier: [[11.973949, 12.787077, 125.967303], [5.792435, 5.999960, 6.735793], [9.162002, 11.014399, 54.823815], [4.816597, 4.859801, 72.267122], [4.986417, 5.032253, 10.673866], [12.436991, 14.590371, 37.868889], [9.608205, 10.909194, 111.913138], [11.177904, 11.286869, 12.813118]]
### 8
fourier: [[10.358882, 11.384358, 18.749965], [8.895162, 10.202255, 71.583402], [1.621640, 1.847863, 33.776633], [7.439962, 8.395989, 28.097282], [9.127383, 10.073063, 70.461813], [19.132857, 21.460828, 189.768706], [5.184415, 5.728732, 43.307443], [11.175689, 12.273734, 123.923143]]
### 10
fourier: [[14.970167, 16.467073, 188.303421], [2.042189, 2.098530, 44.764698], [1.691139, 1.701792, 65.653775], [11.920783, 13.151893, 96.254668], [9.618902, 10.829134, 24.427930], [2.300781, 2.371016, 56.713843], [11.058658, 12.557622, 34.742326], [9.661206, 10.895551, 50.024505]]
### 12
fourier: [[14.305264, 16.082547, 132.427051]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[35.787622, 38.017128, 254.939651], [22.191931, 28.297942, 70.120876], [28.225901, 30.198035, 128.850183], [11.319971, 12.356982, 67.568346], [35.312971, 37.388067, 49.191990], [26.489192, 30.083355, 89.615885], [27.352782, 27.807132, 33.756521], [20.288933, 20.759382, 146.685353]]
### 2
fourier: [[7.006416, 7.685548, 31.299159], [14.202715, 16.442129, 111.343258], [17.660867, 19.201329, 123.857132], [15.982153, 18.244307, 103.493047], [21.847283, 27.682087, 40.115086], [11.393620, 11.638069, 12.074533], [13.576581, 15.227027, 18.400178], [14.436756, 15.302996, 89.185467]]
### 4
fourier: [[19.864482, 22.887259, 151.724524], [7.614840, 8.368870, 101.260050], [1.829631, 2.382055, 10.886313], [18.158060, 19.540669, 159.133197], [16.839603, 22.006056, 65.701356], [5.646381, 5.838451, 75.228835], [7.008719, 8.529315, 61.743483], [19.869483, 25.926057, 45.865893]]
### 6
fourier: [[11.973949, 12.787077, 125.967303], [5.792435, 5.999960, 6.735793], [9.162002, 11.014399, 54.823815], [4.816597, 4.859801, 72.267122], [4.986417, 5.032253, 10.673866], [12.436991, 14.590371, 37.868889], [9.608205, 10.909194, 111.913138], [11.177904, 11.286869, 12.813118]]
### 8
fourier: [[10.358882, 11.384358, 18.749965], [8.895162, 10.202255, 71.583402], [1.621640, 1.847863, 33.776633], [7.439962, 8.395989, 28.097282], [9.127383, 10.073063, 70.461813], [19.132857, 21.460828, 189.768706], [5.184415, 5.728732, 43.307443], [11.175689, 12.273734, 123.923143]]
### 10
fourier: [[14.970167, 16.467073, 188.303421], [2.042189, 2.098530, 44.764698], [1.691139, 1.701792, 65.653775], [11.920783, 13.151893, 96.254668], [9.618902, 10.829134, 24.427930], [2.300781, 2.371016, 56.713843], [11.058658, 12.557622, 34.742326], [9.661206, 10.895551, 50.024505]]
### 12
fourier: [[14.305264, 16.082547, 132.427051]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [35.78762210071351, 38.01712800706453, 254.9396507665515]}, "1": {"fourier": [22.19193117622994, 28.29794203563962, 70.12087559700012]}, "2": {"fourier": [28.225901211654374, 30.198034591471398, 128.85018345713615]}, "3": {"fourier": [11.319970919617084, 12.35698211998469, 67.5683455877006]}, "4": {"fourier": [35.31297086933268, 37.388067023918715, 49.19199038296938]}, "5": {"fourier": [26.48919153573463, 30.083354641998728, 89.61588540673256]}, "6": {"fourier": [27.35278153752258, 27.807131707807677, 33.75652143212289]}, "7": {"fourier": [20.28893261544284, 20.759382491084708, 146.6853533089161]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [7.006416459638089, 7.6855478696220905, 31.29915875196457]}, "1": {"fourier": [14.202715086081252, 16.44212904663532, 111.34325766563416]}, "2": {"fourier": [17.66086693925603, 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"8": {"neuron_profiles": {"0": {"fourier": [10.35888221647009, 11.384358383369381, 18.749964825809002]}, "1": {"fourier": [8.895162069622714, 10.202255334949172, 71.58340246975422]}, "2": {"fourier": [1.621639673226211, 1.8478626776258669, 33.77663305401802]}, "3": {"fourier": [7.439961788814837, 8.395988900050728, 28.09728203713894]}, "4": {"fourier": [9.12738314653781, 10.073063095537233, 70.46181251108646]}, "5": {"fourier": [19.132857264976124, 21.46082837998393, 189.76870623230934]}, "6": {"fourier": [5.184414657756498, 5.7287323107308135, 43.307442620396614]}, "7": {"fourier": [11.175688637401288, 12.273733649467818, 123.92314326763153]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [14.970166539045858, 16.467072575821526, 188.30342069268227]}, "1": {"fourier": [2.042189028977094, 2.0985303182280175, 44.76469802856445]}, "2": {"fourier": [1.6911389137146324, 1.7017917717249271, 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0, "global_epoch": 0, "train_loss": 0.6864830851554871, "train_acc": 0.575, "val_loss": 0.6887338161468506, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6627926528453827, "train_acc": 0.575, "val_loss": 0.6725373864173889, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6064549684524536, "train_acc": 0.655, "val_loss": 0.5365843772888184, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6570932865142822, "train_acc": 0.725, "val_loss": 0.4882015287876129, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.40028806030750275, "train_acc": 0.84, "val_loss": 0.48158103227615356, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.35644717514514923, "train_acc": 0.865, "val_loss": 0.3772534132003784, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.30123887956142426, "train_acc": 0.92, "val_loss": 0.3601030707359314, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.23668602108955383, "train_acc": 0.91, "val_loss": 0.46079421043395996, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.2318251058459282, "train_acc": 0.925, "val_loss": 0.5441784858703613, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.19878922030329704, "train_acc": 0.925, "val_loss": 0.5878233909606934, "val_acc": 0.86}], "summary": {"total_epochs": 10, "degraded_epochs": 3, "improved_epochs": 7, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6887338161468506, "final_val_loss": 0.5365843772888184, "initial_val_acc": 0.5, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.4882015287876129, "final_val_loss": 0.5878233909606934, "initial_val_acc": 0.82, "final_val_acc": 0.86, "best_val_acc": 0.9, "best_epoch": 5}, "improvement": 0.16000000000000003, "first_improvement_epoch": 2}} |
96 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.5, "improved_accuracy": 0.88, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3153, "learning_rate": 0.09375952855635061, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[60.666037, 68.381730, 335.749154], [42.850875, 44.051786, 132.199431], [35.826666, 49.244221, 109.722152], [36.269373, 44.205781, 152.324007], [37.538569, 37.892115, 216.580164], [35.169734, 39.889926, 236.307893], [33.611547, 34.091506, 98.352148], [37.715934, 37.987672, 38.077627]]
### 2
fourier: [[73.948923, 77.479048, 382.284383], [44.173514, 45.423222, 47.243949], [20.025289, 20.855532, 123.923514], [10.456383, 10.888701, 91.104603], [77.092094, 87.175749, 95.926205], [10.487844, 11.432848, 104.013205], [53.197510, 58.866682, 64.566169], [52.254119, 56.576100, 61.446824]]
### 4
fourier: [[90.653865, 95.053724, 467.010804], [53.622935, 59.452785, 210.589424], [87.657281, 93.815523, 365.095751], [11.444183, 13.566154, 87.794692], [63.049500, 63.880141, 73.926563], [127.074989, 130.284023, 457.604534], [26.683780, 26.809212, 175.474465], [63.970313, 64.776776, 69.684693]]
### 6
fourier: [[10.339086, 10.420973, 13.186930], [78.254084, 79.694416, 137.801261], [49.708889, 52.642669, 268.541377], [36.479630, 46.160810, 157.038935], [107.762677, 108.025146, 319.343896], [51.771480, 53.507855, 285.306512], [62.019343, 65.316754, 310.566542], [43.649683, 44.924934, 248.281363]]
### 8
fourier: [[62.901862, 64.833675, 294.805187], [74.886805, 76.450101, 353.891234], [11.205931, 14.400317, 129.543390], [23.238875, 24.256855, 146.444075], [117.485081, 121.907821, 473.214676], [78.759831, 79.477738, 147.580974], [12.319012, 15.957686, 150.914651], [73.351907, 77.199486, 444.589152]]
### 10
fourier: [[22.948591, 24.555303, 64.443629], [12.642811, 13.527979, 52.788460], [29.496449, 31.561600, 83.348066], [14.449955, 15.461647, 39.664121], [0.579644, 0.620227, 14.455152], [7.062969, 7.557472, 44.802569], [18.734168, 20.045813, 83.787451], [19.926222, 21.321327, 97.717568]]
### 12
fourier: [[15.048397, 16.174034, 22.944148]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[60.666037, 68.381730, 335.749154], [42.850875, 44.051786, 132.199431], [35.826666, 49.244221, 109.722152], [36.269373, 44.205781, 152.324007], [37.538569, 37.892115, 216.580164], [35.169734, 39.889926, 236.307893], [33.611547, 34.091506, 98.352148], [37.715934, 37.987672, 38.077627]]
### 2
fourier: [[73.948923, 77.479048, 382.284383], [44.173514, 45.423222, 47.243949], [20.025289, 20.855532, 123.923514], [10.456383, 10.888701, 91.104603], [77.092094, 87.175749, 95.926205], [10.487844, 11.432848, 104.013205], [53.197510, 58.866682, 64.566169], [52.254119, 56.576100, 61.446824]]
### 4
fourier: [[90.653865, 95.053724, 467.010804], [53.622935, 59.452785, 210.589424], [87.657281, 93.815523, 365.095751], [11.444183, 13.566154, 87.794692], [63.049500, 63.880141, 73.926563], [127.074989, 130.284023, 457.604534], [26.683780, 26.809212, 175.474465], [63.970313, 64.776776, 69.684693]]
### 6
fourier: [[10.339086, 10.420973, 13.186930], [78.254084, 79.694416, 137.801261], [49.708889, 52.642669, 268.541377], [36.479630, 46.160810, 157.038935], [107.762677, 108.025146, 319.343896], [51.771480, 53.507855, 285.306512], [62.019343, 65.316754, 310.566542], [43.649683, 44.924934, 248.281363]]
### 8
fourier: [[62.901862, 64.833675, 294.805187], [74.886805, 76.450101, 353.891234], [11.205931, 14.400317, 129.543390], [23.238875, 24.256855, 146.444075], [117.485081, 121.907821, 473.214676], [78.759831, 79.477738, 147.580974], [12.319012, 15.957686, 150.914651], [73.351907, 77.199486, 444.589152]]
### 10
fourier: [[22.948591, 24.555303, 64.443629], [12.642811, 13.527979, 52.788460], [29.496449, 31.561600, 83.348066], [14.449955, 15.461647, 39.664121], [0.579644, 0.620227, 14.455152], [7.062969, 7.557472, 44.802569], [18.734168, 20.045813, 83.787451], [19.926222, 21.321327, 97.717568]]
### 12
fourier: [[15.048397, 16.174034, 22.944148]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [62.90186174041016, 64.83367533758015, 294.8051868677139]}, "1": {"fourier": [74.88680535344608, 76.45010084086856, 353.89123380184174]}, "2": {"fourier": [11.205930530628692, 14.400317351571413, 129.54338991641998]}, "3": {"fourier": [23.23887471336374, 24.256855218136756, 146.44407498836517]}, "4": {"fourier": [117.4850806989471, 121.90782082191986, 473.2146755307913]}, "5": {"fourier": [78.75983107008626, 79.4777376766554, 147.58097414672375]}, "6": {"fourier": [12.319012344558443, 15.957685821355392, 150.9146511554718]}, "7": {"fourier": [73.35190667471811, 77.19948586004949, 444.589152097702]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [22.94859055780659, 24.555302599466494, 64.44362928718328]}, "1": {"fourier": [12.64281147224758, 13.527979218610163, 52.78846034407616]}, "2": {"fourier": [29.49644919162401, 31.561599899828238, 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0.7504766583442688, "final_val_loss": 0.6715295314788818, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 1.37939453125, "final_val_loss": 0.3656315505504608, "initial_val_acc": 0.5, "final_val_acc": 0.84, "best_val_acc": 0.88, "best_epoch": 5}, "improvement": 0.38, "first_improvement_epoch": 1}} |
97 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.4, "improved_accuracy": 0.96, "improvement": 0.5599999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8537, "learning_rate": 0.040863597474926766, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[29.699134, 31.586331, 167.503247], [28.976600, 33.334549, 152.371173], [48.031054, 48.264946, 316.188064], [39.973858, 42.847127, 92.042646], [36.825986, 38.819386, 124.462618]]
### 2
fourier: [[18.977216, 19.922350, 100.692423], [33.306347, 37.580886, 143.617840], [48.659909, 53.366080, 251.458779], [21.174241, 25.916047, 39.002005], [38.190658, 40.898121, 257.525502]]
### 4
fourier: [[70.842765, 79.830350, 294.287311], [47.698432, 53.146787, 304.470794], [8.427436, 8.568204, 36.919467], [69.660502, 76.575865, 359.141393], [24.538250, 28.656034, 151.399557]]
### 6
fourier: [[41.064867, 44.608186, 133.173804], [6.208530, 7.329684, 12.920160], [12.910572, 14.180741, 50.142009], [22.299236, 22.391353, 111.192398], [44.446378, 51.835934, 274.335668]]
### 8
fourier: [[25.270846, 26.467970, 99.328243], [34.010277, 35.202998, 139.717011], [40.589799, 45.020671, 118.575296], [33.658105, 33.875325, 148.037660], [31.770008, 35.950772, 167.434761]]
### 10
fourier: [[38.247001, 42.874943, 187.792819], [36.861065, 40.644002, 158.221181], [21.288812, 21.301797, 53.012080], [57.082316, 65.341516, 313.598819], [46.740309, 48.227221, 180.554717]]
### 12
fourier: [[56.727202, 65.820477, 277.166534]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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}
## Activation Signature
### 0
fourier: [[29.699134, 31.586331, 167.503247], [28.976600, 33.334549, 152.371173], [48.031054, 48.264946, 316.188064], [39.973858, 42.847127, 92.042646], [36.825986, 38.819386, 124.462618]]
### 2
fourier: [[18.977216, 19.922350, 100.692423], [33.306347, 37.580886, 143.617840], [48.659909, 53.366080, 251.458779], [21.174241, 25.916047, 39.002005], [38.190658, 40.898121, 257.525502]]
### 4
fourier: [[70.842765, 79.830350, 294.287311], [47.698432, 53.146787, 304.470794], [8.427436, 8.568204, 36.919467], [69.660502, 76.575865, 359.141393], [24.538250, 28.656034, 151.399557]]
### 6
fourier: [[41.064867, 44.608186, 133.173804], [6.208530, 7.329684, 12.920160], [12.910572, 14.180741, 50.142009], [22.299236, 22.391353, 111.192398], [44.446378, 51.835934, 274.335668]]
### 8
fourier: [[25.270846, 26.467970, 99.328243], [34.010277, 35.202998, 139.717011], [40.589799, 45.020671, 118.575296], [33.658105, 33.875325, 148.037660], [31.770008, 35.950772, 167.434761]]
### 10
fourier: [[38.247001, 42.874943, 187.792819], [36.861065, 40.644002, 158.221181], [21.288812, 21.301797, 53.012080], [57.082316, 65.341516, 313.598819], [46.740309, 48.227221, 180.554717]]
### 12
fourier: [[56.727202, 65.820477, 277.166534]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [29.699134424274796, 31.586331285810235, 167.5032474771142]}, "1": {"fourier": [28.97660042721382, 33.33454936307304, 152.37117294967175]}, "2": {"fourier": [48.031053538237124, 48.2649459189244, 316.18806371092796]}, "3": {"fourier": [39.973857567293415, 42.84712707831114, 92.04264578223228]}, "4": {"fourier": [36.82598582748413, 38.819385717200596, 124.46261754631996]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [18.977215649048066, 19.922349911524886, 100.69242294877768]}, "1": {"fourier": [33.306347337237085, 37.58088646308773, 143.6178403645754]}, "2": {"fourier": [48.65990867625744, 53.36607956380845, 251.45877930521965]}, "3": {"fourier": [21.174240891640213, 25.916046644458785, 39.00200515985489]}, "4": {"fourier": [38.190657534767354, 40.89812106158826, 257.52550211548805]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [70.8427652505579, 79.83035003887852, 294.28731122612953]}, "1": {"fourier": [47.69843167062485, 53.14678669906159, 304.47079353034496]}, "2": {"fourier": [8.427435576559722, 8.568203934882682, 36.919467482250184]}, "3": {"fourier": [69.66050220169983, 76.57586477222061, 359.1413932442665]}, "4": {"fourier": [24.538249593796568, 28.656033828976962, 151.39955657720566]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [41.06486734009229, 44.60818620687275, 133.1738037019968]}, "1": {"fourier": [6.2085295059697785, 7.329683781722009, 12.920159801840782]}, "2": {"fourier": [12.910571543040433, 14.180741020258004, 50.142009323462844]}, "3": {"fourier": [22.29923632387103, 22.39135340390547, 111.19239768385887]}, "4": {"fourier": [44.44637762684307, 51.83593424429299, 274.3356675505638]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [25.270845983076853, 26.46796967314504, 99.32824272848666]}, "1": {"fourier": [34.01027709196493, 35.20299847175486, 139.71701055765152]}, "2": {"fourier": [40.589799469181344, 45.02067051198893, 118.57529588788748]}, "3": {"fourier": [33.65810451938263, 33.87532515032592, 148.03765961527824]}, "4": {"fourier": [31.770008115612868, 35.950772416809095, 167.43476101383567]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [38.24700140003406, 42.87494346622121, 187.79281888902187]}, "1": {"fourier": [36.861065198673074, 40.64400178202495, 158.22118143737316]}, "2": {"fourier": [21.288812358898223, 21.30179693253593, 53.012080043554306]}, "3": {"fourier": [57.08231573729311, 65.34151560282251, 313.59881944954395]}, "4": {"fourier": [46.740309369880734, 48.22722061496903, 180.55471731722355]}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["fourier"]}}, "12": {"neuron_profiles": {"0": {"fourier": [56.72720233782158, 65.82047674250092, 277.1665339618921]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.553216, -0.380599, -0.212997, -0.088293, 0.028307], [-0.048092, -0.134441, 0.126493, -0.317579, -0.703302], [0.683199, 0.654251, 0.623108, -0.014967, -0.066995], [-0.72852, -0.754284, -0.038621, 0.039822, 0.426647], [0.278697, 0.707781, 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-0.368364], [0.574744, -0.182021, 0.288972, 0.534986, -0.154108], [-0.689265, 0.538127, -0.67432, -0.198601, 0.522228]], "network.6.bias": [0.21535, 0.218752, 0.035057, -0.517718, 0.508301], "network.8.weight": [[-0.443037, -0.429055, 0.189883, 0.109158, 0.414154], [-0.716702, -0.586722, 0.151671, -0.123291, 0.460796], [1.03574, 0.111123, 0.362014, 0.435771, -0.495125], [-0.608741, -0.220014, -0.146881, -0.131854, 0.495776], [-0.114823, -0.85535, 0.008446, -0.152456, 0.624934]], "network.8.bias": [-0.017529, 0.373899, -0.041167, 0.275632, 0.038118], "network.10.weight": [[0.51926, 0.206357, -0.347082, 0.423568, 0.330921], [-0.084227, 0.471061, -0.345226, 0.123748, 0.695424], [0.138137, 0.221712, -0.341354, 0.102132, 0.15336], [0.258742, 0.787927, -0.367558, 0.489995, 0.682247], [-0.6796, -0.498127, 0.62734, -0.661236, 0.180201]], "network.10.bias": [-0.14528, -0.394127, -0.313931, -0.227986, 0.255616], "network.12.weight": [[-0.159601, -0.245119, -0.398922, -0.68948, 0.563625]], "network.12.bias": [0.390348]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6975810527801514, "train_acc": 0.49, "val_loss": 0.7108409404754639, "val_acc": 0.4}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6714601516723633, "train_acc": 0.59, "val_loss": 0.7633012533187866, "val_acc": 0.4}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6526806354522705, "train_acc": 0.59, "val_loss": 0.6976295709609985, "val_acc": 0.4}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.5409204661846161, "train_acc": 0.59, "val_loss": 0.5447801351547241, "val_acc": 0.4}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.4525824189186096, "train_acc": 0.62, "val_loss": 0.40713202953338623, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.34240545332431793, "train_acc": 0.915, "val_loss": 0.29640820622444153, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.21919506788253784, "train_acc": 0.93, "val_loss": 0.2161056101322174, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.2008984386920929, "train_acc": 0.93, "val_loss": 0.17468205094337463, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.20505712926387787, "train_acc": 0.935, "val_loss": 0.1715618073940277, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.20987223833799362, "train_acc": 0.93, "val_loss": 0.1212630495429039, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.19738419353961945, "train_acc": 0.935, "val_loss": 0.1403549164533615, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.20178912580013275, "train_acc": 0.935, "val_loss": 0.13068944215774536, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.16592690348625183, "train_acc": 0.94, "val_loss": 0.12438246607780457, "val_acc": 0.94}], "summary": {"total_epochs": 13, "degraded_epochs": 4, "improved_epochs": 9, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.7108409404754639, "final_val_loss": 0.5447801351547241, "initial_val_acc": 0.4, "final_val_acc": 0.4, "best_val_acc": 0.4}, "improved_stage": {"initial_val_loss": 0.40713202953338623, "final_val_loss": 0.12438246607780457, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.5599999999999999, "first_improvement_epoch": 3}} |
98 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.48, "improved_accuracy": 0.9, "improvement": 0.42000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3299, "learning_rate": 0.06432301658833305, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.096877
]
],
"network.10.bias": [
0.166171
]
}
## Activation Signature
### 0
fourier: [[27.816266, 27.912402, 251.101425], [51.992767, 53.307847, 279.053811], [52.878283, 54.402982, 244.308502], [43.967986, 45.160551, 126.516246], [36.328642, 40.252208, 73.430193], [45.023890, 48.864185, 284.685029], [40.210887, 41.387732, 114.785014]]
### 2
fourier: [[53.546540, 55.107681, 327.377036], [53.941319, 54.554713, 263.699625], [34.057206, 38.838313, 226.599100], [51.360987, 52.235056, 168.192050], [58.138239, 58.492094, 162.075346], [15.718110, 16.163463, 67.129543], [34.494272, 37.720814, 255.386108]]
### 4
fourier: [[20.033896, 20.085650, 130.752704], [35.996016, 36.650687, 234.833898], [36.410817, 38.682459, 41.954618], [8.102951, 8.456848, 107.140173], [9.077060, 9.633941, 76.732555], [20.564446, 21.726795, 23.639814], [2.292847, 2.480539, 42.036472]]
### 6
fourier: [[13.400166, 13.754015, 58.654231], [16.502231, 16.858530, 17.265417], [30.674028, 31.457075, 77.590432], [17.614431, 18.046968, 38.420862], [0.823734, 0.833588, 30.670611], [21.382991, 21.941194, 52.797016], [18.674514, 18.981294, 19.485765]]
### 8
fourier: [[37.087711, 39.647770, 92.566366], [12.082476, 12.782213, 90.441345], [24.425751, 25.356350, 64.280144], [28.404156, 30.203339, 37.362206], [15.188122, 15.500761, 65.570002], [9.101030, 9.635456, 88.320305], [13.101165, 13.414432, 45.872784]]
### 10
fourier: [[29.401133, 32.394777, 136.908349]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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]
],
"network.10.bias": [
0.166171
]
}
## Activation Signature
### 0
fourier: [[27.816266, 27.912402, 251.101425], [51.992767, 53.307847, 279.053811], [52.878283, 54.402982, 244.308502], [43.967986, 45.160551, 126.516246], [36.328642, 40.252208, 73.430193], [45.023890, 48.864185, 284.685029], [40.210887, 41.387732, 114.785014]]
### 2
fourier: [[53.546540, 55.107681, 327.377036], [53.941319, 54.554713, 263.699625], [34.057206, 38.838313, 226.599100], [51.360987, 52.235056, 168.192050], [58.138239, 58.492094, 162.075346], [15.718110, 16.163463, 67.129543], [34.494272, 37.720814, 255.386108]]
### 4
fourier: [[20.033896, 20.085650, 130.752704], [35.996016, 36.650687, 234.833898], [36.410817, 38.682459, 41.954618], [8.102951, 8.456848, 107.140173], [9.077060, 9.633941, 76.732555], [20.564446, 21.726795, 23.639814], [2.292847, 2.480539, 42.036472]]
### 6
fourier: [[13.400166, 13.754015, 58.654231], [16.502231, 16.858530, 17.265417], [30.674028, 31.457075, 77.590432], [17.614431, 18.046968, 38.420862], [0.823734, 0.833588, 30.670611], [21.382991, 21.941194, 52.797016], [18.674514, 18.981294, 19.485765]]
### 8
fourier: [[37.087711, 39.647770, 92.566366], [12.082476, 12.782213, 90.441345], [24.425751, 25.356350, 64.280144], [28.404156, 30.203339, 37.362206], [15.188122, 15.500761, 65.570002], [9.101030, 9.635456, 88.320305], [13.101165, 13.414432, 45.872784]]
### 10
fourier: [[29.401133, 32.394777, 136.908349]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [27.816265810005916, 27.91240241584959, 251.10142517089844]}, "1": {"fourier": [51.99276662807231, 53.30784661778876, 279.05381125956774]}, "2": {"fourier": [52.87828337342989, 54.402982144143564, 244.30850239098072]}, "3": {"fourier": [43.96798569523968, 45.160551211080126, 126.51624605059624]}, "4": {"fourier": [36.32864201187629, 40.25220824760877, 73.43019276857376]}, "5": {"fourier": [45.023890403282955, 48.86418462288124, 284.6850293800235]}, "6": {"fourier": [40.210886794523574, 41.38773178397868, 114.78501412272453]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [53.546540323729346, 55.10768050431872, 327.3770357966423]}, "1": {"fourier": [53.941319269477866, 54.55471337700211, 263.69962488114834]}, "2": {"fourier": [34.05720640191745, 38.83831250212402, 226.59909969568253]}, "3": {"fourier": [51.36098743552902, 52.235056162971986, 168.19204998016357]}, "4": {"fourier": [58.13823885293744, 58.49209420074031, 162.07534649968147]}, "5": {"fourier": [15.718110173239497, 16.16346280547243, 67.12954307347536]}, "6": {"fourier": [34.49427239786291, 37.720813759911884, 255.38610762357712]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [20.033895611221766, 20.085650029892165, 130.75270435214043]}, "1": {"fourier": [35.99601610671601, 36.65068730451098, 234.83389848470688]}, "2": {"fourier": [36.41081686853823, 38.68245909783541, 41.954618278373616]}, "3": {"fourier": [8.102950728089613, 8.456848106927767, 107.14017289876938]}, "4": {"fourier": [9.077059803072206, 9.633940572159503, 76.73255547881126]}, "5": {"fourier": [20.564446433475883, 21.72679479603114, 23.63981385518117]}, "6": {"fourier": [2.292847033867869, 2.480539225950804, 42.036471754312515]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [13.400165735426603, 13.754015059391735, 58.654231041669846]}, "1": {"fourier": [16.50223056893591, 16.85853024072433, 17.265417390664844]}, "2": {"fourier": [30.674028170189292, 31.45707536268122, 77.59043208137155]}, "3": {"fourier": [17.614430575313992, 18.046967556456188, 38.42086239531636]}, "4": {"fourier": [0.8237336959797287, 0.8335877594994608, 30.670611023902893]}, "5": {"fourier": [21.382990546564407, 21.94119366629973, 52.797016102820635]}, "6": {"fourier": [18.674513992382103, 18.981293513857597, 19.485764859674333]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [37.087710608060995, 39.64777004907959, 92.56636559963226]}, "1": {"fourier": [12.082476294001829, 12.782213130162093, 90.44134467840195]}, "2": {"fourier": [24.425751222897617, 25.356350123252994, 64.28014408051968]}, "3": {"fourier": [28.404156182238488, 30.203339373919125, 37.362205505371094]}, "4": {"fourier": [15.188122011620154, 15.500760695148381, 65.57000213861465]}, "5": {"fourier": [9.101029565901335, 9.63545600886612, 88.32030522823334]}, "6": {"fourier": [13.101165024669408, 13.414431627230641, 45.87278373539448]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [29.401133280499064, 32.394776940932196, 136.90834921598434]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, 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0.3433059751987457, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.12554000690579414, "train_acc": 0.975, "val_loss": 0.33691897988319397, "val_acc": 0.9}], "summary": {"total_epochs": 12, "degraded_epochs": 5, "improved_epochs": 7, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.6991400718688965, "final_val_loss": 0.6222957372665405, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6446078419685364, "final_val_loss": 0.33691897988319397, "initial_val_acc": 0.48, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 8}, "improvement": 0.42000000000000004, "first_improvement_epoch": 4}} |
99 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.48, "improved_accuracy": 0.72, "improvement": 0.24, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4662, "learning_rate": 0.06516292890522583, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
fourier: [[48.554018, 48.622062, 49.263588], [35.530261, 45.390600, 99.932699], [46.699649, 50.385598, 186.615240], [39.255731, 41.750277, 188.724363], [33.514523, 34.804660, 35.766646], [45.170062, 58.805440, 219.183270], [45.484648, 50.933010, 163.937555]]
### 2
fourier: [[55.599669, 55.685678, 179.192448], [26.581104, 26.849947, 34.488688], [51.777670, 51.962689, 350.066269], [12.561302, 14.268838, 103.811186], [99.573609, 102.212693, 236.297886], [76.173954, 76.301390, 159.567365], [90.761635, 105.842884, 404.019612]]
### 4
fourier: [[114.624316, 123.072727, 375.241397], [100.837131, 104.334291, 417.295167], [45.043049, 49.133913, 231.732927], [160.677991, 172.479020, 593.387517], [65.054396, 67.647289, 249.997958], [103.895187, 107.992250, 342.228898], [90.912496, 94.332360, 458.925753]]
### 6
fourier: [[144.034202, 155.548150, 470.806076], [90.755813, 97.624452, 300.690459], [106.825583, 116.124832, 370.013390], [67.630407, 73.354945, 219.490846], [76.166319, 82.349393, 288.105608], [77.020917, 83.421267, 306.257445], [119.804543, 130.439115, 421.167732]]
### 8
fourier: [[155.868672, 169.151562, 530.888008]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.095401,
-0.388854,
-0.529484
],
[
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0.256474,
-0.348087,
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],
[
1.223458,
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-0.398933
],
[
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0.008349,
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0.892005
],
[
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],
[
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],
[
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]
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],
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[
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[
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[
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[
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0.108802,
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[
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0.538386,
0.264904,
0.108446,
0.001491
]
],
"network.6.bias": [
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-0.291708,
-0.268643,
-0.232675,
2.7e-05,
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],
"network.8.weight": [
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]
],
"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[48.554018, 48.622062, 49.263588], [35.530261, 45.390600, 99.932699], [46.699649, 50.385598, 186.615240], [39.255731, 41.750277, 188.724363], [33.514523, 34.804660, 35.766646], [45.170062, 58.805440, 219.183270], [45.484648, 50.933010, 163.937555]]
### 2
fourier: [[55.599669, 55.685678, 179.192448], [26.581104, 26.849947, 34.488688], [51.777670, 51.962689, 350.066269], [12.561302, 14.268838, 103.811186], [99.573609, 102.212693, 236.297886], [76.173954, 76.301390, 159.567365], [90.761635, 105.842884, 404.019612]]
### 4
fourier: [[114.624316, 123.072727, 375.241397], [100.837131, 104.334291, 417.295167], [45.043049, 49.133913, 231.732927], [160.677991, 172.479020, 593.387517], [65.054396, 67.647289, 249.997958], [103.895187, 107.992250, 342.228898], [90.912496, 94.332360, 458.925753]]
### 6
fourier: [[144.034202, 155.548150, 470.806076], [90.755813, 97.624452, 300.690459], [106.825583, 116.124832, 370.013390], [67.630407, 73.354945, 219.490846], [76.166319, 82.349393, 288.105608], [77.020917, 83.421267, 306.257445], [119.804543, 130.439115, 421.167732]]
### 8
fourier: [[155.868672, 169.151562, 530.888008]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [48.554017543792725, 48.62206178309929, 49.2635876656251]}, "1": {"fourier": [35.53026102892669, 45.390599555428196, 99.93269857764244]}, "2": {"fourier": [46.69964947595675, 50.38559830247182, 186.6152397096157]}, "3": {"fourier": [39.255731344691554, 41.75027670242005, 188.72436279058456]}, "4": {"fourier": [33.514523084083045, 34.80465971856347, 35.7666461841248]}, "5": {"fourier": [45.17006220490207, 58.80544040221888, 219.18326964974403]}, "6": {"fourier": [45.48464794334121, 50.933010232288105, 163.93755474686623]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [55.59966940378251, 55.68567776212732, 179.19244822859764]}, "1": {"fourier": [26.581104342051013, 26.849946725993327, 34.488688065563636]}, "2": {"fourier": [51.77766957357506, 51.96268942357699, 350.06626892089844]}, "3": {"fourier": [12.56130180466185, 14.268838046287907, 103.81118607521057]}, "4": {"fourier": [99.57360883702921, 102.2126930797893, 236.29788606613874]}, "5": {"fourier": [76.17395402594536, 76.30139020596033, 159.5673649609089]}, "6": {"fourier": [90.7616349448526, 105.84288401791629, 404.0196115374565]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [114.62431572775473, 123.07272695634715, 375.24139657616615]}, "1": {"fourier": [100.83713114941764, 104.33429122530151, 417.2951665520668]}, "2": {"fourier": [45.04304858097765, 49.1339131948483, 231.73292684555054]}, "3": {"fourier": [160.67799065911152, 172.4790202094566, 593.3875166773796]}, "4": {"fourier": [65.05439583519266, 67.64728867032458, 249.99795839190483]}, "5": {"fourier": [103.89518671977825, 107.99224999348927, 342.22889795154333]}, "6": {"fourier": [90.91249618765583, 94.33235997676833, 458.92575323581696]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [144.03420237329783, 155.54814987049178, 470.8060763180256]}, "1": {"fourier": [90.75581254301305, 97.62445239338263, 300.6904590725899]}, "2": {"fourier": [106.82558334441266, 116.12483243850767, 370.0133895277977]}, "3": {"fourier": [67.63040703887495, 73.35494463380412, 219.49084648489952]}, "4": {"fourier": [76.16631919628603, 82.34939275332034, 288.10560818761587]}, "5": {"fourier": [77.02091659807657, 83.4212673497517, 306.25744496285915]}, "6": {"fourier": [119.80454269441074, 130.43911546216012, 421.1677315235138]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [155.8686718029261, 169.15156194467014, 530.8880084306002]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[1.141556, -0.010147, -0.095401, -0.388854, -0.529484], [0.760496, -0.731183, 0.256474, -0.348087, -0.144421], [1.223458, 0.540273, -0.265917, -0.054541, -0.398933], [-0.682625, 0.008349, 0.486041, 0.257487, 0.892005], [0.752746, 0.010339, 0.007416, 0.23959, -0.943982], [0.844707, -0.797286, -0.02233, -0.929826, 0.279578], [1.143479, 0.379328, -0.008815, -0.229213, -0.214319]], "network.0.bias": [-0.255412, -0.335552, 0.73093, 0.263622, -0.15323, -0.337938, 0.481588], "network.2.weight": [[-0.020651, -0.079544, 0.363158, -0.325262, 0.30477, 0.246505, 0.611016], [0.226806, -0.173023, -0.201839, 0.505275, 0.154886, -0.32184, -0.273488], [-0.312079, -0.131667, -0.506344, -0.334198, -0.531187, 0.32693, -0.262681], [-0.183911, 0.041291, 0.154343, -0.300756, -0.294363, 0.099644, -0.176429], [0.479405, 0.27931, 0.628405, -0.573183, 0.548171, 0.605952, 0.705129], [0.579884, -0.178213, 0.50524, -0.36305, 0.09858, 0.830005, 0.535267], [0.559658, 0.875094, 0.617475, 0.031928, 0.493059, 0.907503, 0.57693]], "network.2.bias": [0.466436, -0.038358, -0.885648, -0.141345, 0.07504, -0.257483, 0.506131], "network.4.weight": [[0.084806, -0.313483, 0.035646, 0.270034, 0.227577, 0.442098, 0.595683], [-0.089669, -0.348356, 0.201651, 0.233208, -0.564198, -0.214203, -0.307455], [-0.264191, -0.432444, -0.077502, 0.178992, -0.187635, -0.211388, -0.007267], [0.456946, -0.392148, -0.227105, 0.058804, 0.613847, -0.062177, 0.874243], [-0.063823, -0.228728, -0.294199, -0.15381, -0.226113, -0.295744, -0.215337], [-0.272349, 0.340179, 0.201218, -0.138627, -0.329287, -0.357085, -0.326593], [-0.583501, -0.604081, 0.090821, 0.232871, 0.200172, -0.474655, -0.499221]], "network.4.bias": [-0.198151, -0.471679, -0.532407, 0.129047, -0.082022, -0.118413, -0.661976], "network.6.weight": [[-0.329616, -0.088488, -0.004142, -0.66571, 0.307204, 0.548358, 0.174765], [0.153475, 0.220528, 0.524611, 0.455831, -0.15273, -0.545479, 0.282554], [0.168042, 0.265984, -0.099688, 0.552449, 0.167493, 0.020897, 0.270037], [0.287089, -0.106881, -0.023509, 0.220202, -0.265916, -0.113734, 0.256157], [-0.114421, 0.267452, 0.450124, 0.558046, 0.334131, -0.178973, 0.066178], [-0.241505, 0.014893, 0.108802, -0.310927, 0.017939, 0.175127, 0.198881], [0.304135, 0.134612, 0.026252, 0.538386, 0.264904, 0.108446, 0.001491]], "network.6.bias": [0.541806, -0.291708, -0.268643, -0.232675, 2.7e-05, -0.328147, -0.192119], "network.8.weight": [[0.399948, 0.017212, -0.332039, -0.45044, -0.297798, 0.229523, -0.573206]], "network.8.bias": [0.133774]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6853665113449097, "train_acc": 0.57, "val_loss": 0.694990873336792, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6431417465209961, "train_acc": 0.57, "val_loss": 0.6814982891082764, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.5952019691467285, "train_acc": 0.57, "val_loss": 0.6136409640312195, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5714486539363861, "train_acc": 0.505, "val_loss": 0.6214572191238403, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.8841840624809265, "train_acc": 0.73, "val_loss": 0.58130943775177, "val_acc": 0.64}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4880569875240326, "train_acc": 0.77, "val_loss": 0.6532307267189026, "val_acc": 0.6}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.5813635289669037, "train_acc": 0.66, "val_loss": 0.6365640759468079, "val_acc": 0.64}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.5589389801025391, "train_acc": 0.675, "val_loss": 0.548572301864624, "val_acc": 0.68}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.5085608214139938, "train_acc": 0.755, "val_loss": 0.6568248271942139, "val_acc": 0.6}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.5421485602855682, "train_acc": 0.725, "val_loss": 0.5364956855773926, "val_acc": 0.72}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.485286146402359, "train_acc": 0.74, "val_loss": 0.5527236461639404, "val_acc": 0.68}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4862406700849533, "train_acc": 0.74, "val_loss": 0.5607572197914124, "val_acc": 0.68}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.48056940734386444, "train_acc": 0.745, "val_loss": 0.555532693862915, "val_acc": 0.68}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.694990873336792, "final_val_loss": 0.6136409640312195, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6214572191238403, "final_val_loss": 0.555532693862915, "initial_val_acc": 0.64, "final_val_acc": 0.68, "best_val_acc": 0.72, "best_epoch": 9}, "improvement": 0.24, "first_improvement_epoch": 2}} |
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