| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: BAAI/bge-small-en-v1.5 |
| | 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 [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0872 |
| | - Precision: 0.9053 |
| | - Recall: 0.9278 |
| | - F1: 0.9164 |
| | - Accuracy: 0.9827 |
| |
|
| | ## 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: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | 0.0608 | 1.0 | 1252 | 0.0888 | 0.8833 | 0.9068 | 0.8949 | 0.9791 | |
| | | 0.0481 | 2.0 | 2504 | 0.0822 | 0.8849 | 0.9159 | 0.9001 | 0.9801 | |
| | | 0.0387 | 3.0 | 3756 | 0.0822 | 0.9000 | 0.9189 | 0.9093 | 0.9816 | |
| | | 0.0348 | 4.0 | 5008 | 0.0820 | 0.9000 | 0.9238 | 0.9117 | 0.9820 | |
| | | 0.038 | 5.0 | 6260 | 0.0810 | 0.8979 | 0.9233 | 0.9104 | 0.9818 | |
| | | 0.0202 | 6.0 | 7512 | 0.0872 | 0.9019 | 0.9249 | 0.9133 | 0.9813 | |
| | | 0.0147 | 7.0 | 8764 | 0.0894 | 0.9024 | 0.9241 | 0.9131 | 0.9817 | |
| | | 0.0357 | 8.0 | 10016 | 0.0880 | 0.9038 | 0.9253 | 0.9144 | 0.9822 | |
| | | 0.0289 | 9.0 | 11268 | 0.0867 | 0.9056 | 0.9278 | 0.9165 | 0.9827 | |
| | | 0.0115 | 10.0 | 12520 | 0.0872 | 0.9053 | 0.9278 | 0.9164 | 0.9827 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.1 |
| | |
