| | --- |
| | 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: 0.0805 |
| | - Precision: 0.8948 |
| | - Recall: 0.9219 |
| | - F1: 0.9082 |
| | - Accuracy: 0.9813 |
| |
|
| | ## 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 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | 0.4814 | 1.0 | 625 | 0.1769 | 0.7653 | 0.8186 | 0.7910 | 0.9624 | |
| | | 0.1733 | 2.0 | 1250 | 0.1109 | 0.8517 | 0.8918 | 0.8713 | 0.9759 | |
| | | 0.1143 | 3.0 | 1875 | 0.0935 | 0.8498 | 0.9047 | 0.8764 | 0.9774 | |
| | | 0.0675 | 4.0 | 2500 | 0.0851 | 0.8845 | 0.9142 | 0.8991 | 0.9805 | |
| | | 0.055 | 5.0 | 3125 | 0.0822 | 0.8897 | 0.9159 | 0.9026 | 0.9813 | |
| | | 0.0449 | 6.0 | 3750 | 0.0784 | 0.8927 | 0.9189 | 0.9056 | 0.9814 | |
| | | 0.0417 | 7.0 | 4375 | 0.0791 | 0.8898 | 0.9187 | 0.9040 | 0.9812 | |
| | | 0.0321 | 8.0 | 5000 | 0.0798 | 0.8993 | 0.9199 | 0.9095 | 0.9817 | |
| | | 0.0301 | 9.0 | 5625 | 0.0805 | 0.8948 | 0.9219 | 0.9082 | 0.9813 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.53.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 4.1.1 |
| | - Tokenizers 0.21.2 |
| |
|
