| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - accuracy |
| model-index: |
| - name: classify |
| 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. --> |
|
|
| # classify |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5723 |
| - Precision: 0.0 |
| - Recall: 0.0 |
| - F1 Binary: 0.0 |
| - Accuracy: 0.7429 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 0 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 8 |
| - 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: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Binary | Accuracy | |
| |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:---------:|:--------:| |
| | No log | 0 | 0 | 0.7028 | 0.2437 | 0.7160 | 0.3636 | 0.3556 | |
| | 0.6 | 2.8181 | 1000 | 0.5779 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| | 0.5522 | 5.6347 | 2000 | 0.5709 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| | 0.5582 | 8.4513 | 3000 | 0.5709 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| | 0.5791 | 11.2680 | 4000 | 0.5703 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| | 0.5895 | 14.0846 | 5000 | 0.5701 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| | 0.5629 | 16.9027 | 6000 | 0.5730 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| | 0.5841 | 19.7193 | 7000 | 0.5723 | 0.0 | 0.0 | 0.0 | 0.7429 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.1 |
| - Pytorch 2.3.0 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
