| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: roberta-base-binary-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. --> |
|
|
| # roberta-base-binary-classification |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8437 |
| - Accuracy: 0.7197 |
| - F1 Macro: 0.7136 |
| - Precision Macro: 0.7122 |
| - Recall Macro: 0.7180 |
| - Auc: 0.7698 |
|
|
| ## 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 | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:------:| |
| | No log | 1.0 | 79 | 0.6399 | 0.6720 | 0.6078 | 0.6827 | 0.6172 | 0.7059 | |
| | No log | 2.0 | 158 | 0.5915 | 0.7038 | 0.6997 | 0.7000 | 0.7071 | 0.7527 | |
| | No log | 3.0 | 237 | 0.6490 | 0.7420 | 0.7148 | 0.7461 | 0.7089 | 0.7592 | |
| | No log | 4.0 | 316 | 0.8437 | 0.7197 | 0.7136 | 0.7122 | 0.7180 | 0.7698 | |
| | No log | 5.0 | 395 | 1.2274 | 0.7070 | 0.6369 | 0.7682 | 0.6466 | 0.7648 | |
| | No log | 6.0 | 474 | 1.1953 | 0.7038 | 0.6992 | 0.6990 | 0.7059 | 0.7482 | |
| | 0.3882 | 7.0 | 553 | 1.2941 | 0.7357 | 0.7231 | 0.7257 | 0.7212 | 0.7580 | |
| | 0.3882 | 8.0 | 632 | 1.4526 | 0.7261 | 0.7150 | 0.7156 | 0.7145 | 0.7441 | |
| | 0.3882 | 9.0 | 711 | 1.6187 | 0.6975 | 0.6917 | 0.6908 | 0.6967 | 0.7349 | |
| | 0.3882 | 10.0 | 790 | 1.5593 | 0.7389 | 0.7275 | 0.7289 | 0.7264 | 0.7492 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
