| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: bert-clf-biencoder-kl_divergence |
| 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-clf-biencoder-kl_divergence |
| |
| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9469 |
| - Accuracy: 0.6828 |
| - F1: 0.6844 |
| - Precision: 0.6937 |
| - Recall: 0.6828 |
| |
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - num_epochs: 7 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 1.1449 | 1.0 | 78 | 1.0565 | 0.5987 | 0.5820 | 0.6068 | 0.5987 | |
| | 0.8672 | 2.0 | 156 | 0.8471 | 0.6505 | 0.6449 | 0.6611 | 0.6505 | |
| | 0.6288 | 3.0 | 234 | 0.8003 | 0.6828 | 0.6858 | 0.6933 | 0.6828 | |
| | 0.5023 | 4.0 | 312 | 0.8179 | 0.6893 | 0.6911 | 0.7008 | 0.6893 | |
| | 0.332 | 5.0 | 390 | 0.8610 | 0.6861 | 0.6866 | 0.6907 | 0.6861 | |
| | 0.2637 | 6.0 | 468 | 0.9075 | 0.6861 | 0.6870 | 0.6890 | 0.6861 | |
| | 0.1895 | 7.0 | 546 | 0.9469 | 0.6828 | 0.6844 | 0.6937 | 0.6828 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.45.1 |
| - Pytorch 2.4.0 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
|
|
