| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: bert-base-cased-finetuned-ner |
| 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. --> |
|
|
| # bert-base-cased-finetuned-ner |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2415 |
| - Precision: 0.8271 |
| - Recall: 0.8524 |
| - F1: 0.8396 |
| - Accuracy: 0.9644 |
|
|
| ## 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: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 7 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.1239 | 1.0 | 9500 | 0.1210 | 0.8028 | 0.8243 | 0.8134 | 0.9614 | |
| | 0.0939 | 2.0 | 19000 | 0.1206 | 0.8218 | 0.8313 | 0.8265 | 0.9638 | |
| | 0.0737 | 3.0 | 28500 | 0.1306 | 0.8201 | 0.8447 | 0.8323 | 0.9642 | |
| | 0.0483 | 4.0 | 38000 | 0.1526 | 0.8239 | 0.8477 | 0.8356 | 0.9647 | |
| | 0.0301 | 5.0 | 47500 | 0.1939 | 0.8354 | 0.8529 | 0.8441 | 0.9649 | |
| | 0.0157 | 6.0 | 57000 | 0.2213 | 0.8310 | 0.8549 | 0.8428 | 0.9647 | |
| | 0.0099 | 7.0 | 66500 | 0.2415 | 0.8271 | 0.8524 | 0.8396 | 0.9644 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.50.1 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.4.1 |
| - Tokenizers 0.21.1 |
|
|
