| --- |
| 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: ner-classification |
| 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. --> |
|
|
| # ner-classification |
|
|
| 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: 0.1650 |
| - Precision: 0.9019 |
| - Recall: 0.9266 |
| - F1: 0.9141 |
| - Accuracy: 0.9818 |
|
|
| ## 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.9605 | 1.0 | 625 | 0.3528 | 0.7730 | 0.8223 | 0.7969 | 0.9629 | |
| | 0.3424 | 2.0 | 1250 | 0.2244 | 0.8615 | 0.8933 | 0.8771 | 0.9763 | |
| | 0.2283 | 3.0 | 1875 | 0.1831 | 0.8656 | 0.9093 | 0.8869 | 0.9785 | |
| | 0.1363 | 4.0 | 2500 | 0.1691 | 0.8847 | 0.9172 | 0.9007 | 0.9806 | |
| | 0.1088 | 5.0 | 3125 | 0.1673 | 0.8939 | 0.9212 | 0.9073 | 0.9810 | |
| | 0.0874 | 6.0 | 3750 | 0.1587 | 0.8909 | 0.9222 | 0.9063 | 0.9814 | |
| | 0.0816 | 7.0 | 4375 | 0.1624 | 0.8948 | 0.9246 | 0.9095 | 0.9814 | |
| | 0.0642 | 8.0 | 5000 | 0.1657 | 0.9002 | 0.9241 | 0.9120 | 0.9817 | |
| | 0.0586 | 9.0 | 5625 | 0.1653 | 0.9006 | 0.9254 | 0.9128 | 0.9818 | |
| | 0.0574 | 10.0 | 6250 | 0.1650 | 0.9019 | 0.9266 | 0.9141 | 0.9818 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.16.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.8.5 |
| - Tokenizers 0.23.1 |
| |
