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gpriday
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midjourney-rank

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
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End of training

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  1. README.md +14 -11
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
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  ---
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- license: apache-2.0
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- base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -13,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # midjourney-rank
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- This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0497
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- - Mse: 0.0497
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  ## Model description
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@@ -41,17 +41,20 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Mse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.0591 | 0.34 | 100 | 0.0556 | 0.0556 |
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- | 0.0569 | 0.67 | 200 | 0.0537 | 0.0537 |
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- | 0.0543 | 1.01 | 300 | 0.0500 | 0.0500 |
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- | 0.0437 | 1.34 | 400 | 0.0566 | 0.0566 |
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- | 0.0432 | 1.68 | 500 | 0.0497 | 0.0497 |
 
 
 
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  ### Framework versions
 
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  ---
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+ license: mit
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+ base_model: microsoft/MiniLM-L12-H384-uncased
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # midjourney-rank
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+ This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0509
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+ - Mse: 0.0509
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Mse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.061 | 0.34 | 100 | 0.0565 | 0.0565 |
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+ | 0.0544 | 0.67 | 200 | 0.0562 | 0.0562 |
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+ | 0.0585 | 1.01 | 300 | 0.0509 | 0.0509 |
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+ | 0.0508 | 1.34 | 400 | 0.0523 | 0.0523 |
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+ | 0.0508 | 1.68 | 500 | 0.0518 | 0.0518 |
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+ | 0.0465 | 2.01 | 600 | 0.0509 | 0.0509 |
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+ | 0.0449 | 2.35 | 700 | 0.0526 | 0.0526 |
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+ | 0.0398 | 2.68 | 800 | 0.0509 | 0.0509 |
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  ### Framework versions
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