| | --- |
| | 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: 0.1049 |
| | - Precision: 0.8564 |
| | - Recall: 0.9036 |
| | - F1: 0.8794 |
| | - Accuracy: 0.9767 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - 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: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 313 | 0.1222 | 0.8456 | 0.8864 | 0.8655 | 0.9743 | |
| | | 0.1316 | 2.0 | 626 | 0.1075 | 0.8579 | 0.8982 | 0.8776 | 0.9768 | |
| | | 0.1316 | 3.0 | 939 | 0.1049 | 0.8564 | 0.9036 | 0.8794 | 0.9767 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.53.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 4.1.1 |
| | - Tokenizers 0.21.2 |
| |
|
