| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: bert-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-finetuned-ner |
|
|
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0435 |
| - Precision: 0.9437 |
| - Recall: 0.9509 |
| - F1: 0.9473 |
| - Accuracy: 0.9909 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - 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: cosine |
| - lr_scheduler_warmup_ratio: 0.05 |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.0543 | 1.0 | 1756 | 0.0462 | 0.9206 | 0.9307 | 0.9256 | 0.9881 | |
| | 0.0227 | 2.0 | 3512 | 0.0450 | 0.9451 | 0.9465 | 0.9458 | 0.9906 | |
| | 0.0113 | 3.0 | 5268 | 0.0435 | 0.9437 | 0.9509 | 0.9473 | 0.9909 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.56.0 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.0 |
|
|
