End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-uncased-finetuned-ner-combined-v1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distilbert-base-uncased-finetuned-ner-combined-v1
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2614
+- Precision: 0.7181
+- Recall: 0.7404
+- F1: 0.7291
+- Accuracy: 0.9201
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 240  | 0.3337          | 0.6076    | 0.6251 | 0.6162 | 0.8959   |
+| No log        | 2.0   | 480  | 0.2803          | 0.6819    | 0.6935 | 0.6876 | 0.9116   |
+| 0.3943        | 3.0   | 720  | 0.2579          | 0.7206    | 0.7040 | 0.7122 | 0.9172   |
+| 0.3943        | 4.0   | 960  | 0.2523          | 0.7225    | 0.7149 | 0.7187 | 0.9174   |
+| 0.2108        | 5.0   | 1200 | 0.2556          | 0.7153    | 0.7288 | 0.7220 | 0.9191   |
+| 0.2108        | 6.0   | 1440 | 0.2532          | 0.7234    | 0.7232 | 0.7233 | 0.9198   |
+| 0.1727        | 7.0   | 1680 | 0.2614          | 0.7181    | 0.7404 | 0.7291 | 0.9201   |
+| 0.1727        | 8.0   | 1920 | 0.2688          | 0.7013    | 0.7414 | 0.7208 | 0.9176   |
+| 0.1407        | 9.0   | 2160 | 0.2759          | 0.7061    | 0.7449 | 0.7250 | 0.9187   |
+| 0.1407        | 10.0  | 2400 | 0.2824          | 0.7161    | 0.7320 | 0.7239 | 0.9189   |
+| 0.1157        | 11.0  | 2640 | 0.2891          | 0.7295    | 0.7179 | 0.7237 | 0.9200   |
+| 0.1157        | 12.0  | 2880 | 0.3048          | 0.7210    | 0.7227 | 0.7218 | 0.9190   |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.0+cu126
+- Datasets 3.6.0
+- Tokenizers 0.22.1

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runs/Dec21_11-00-20_e716a92e04a6/events.out.tfevents.1766315659.e716a92e04a6.1245.1

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