| | --- |
| | metrics: |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: aha_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. --> |
| |
|
| | # aha_classification |
| | |
| | - Loss: 0.1156 |
| | - F1: 0.9617 |
| | - Roc Auc: 0.9682 |
| | - Accuracy: 0.9478 |
| | |
| | ## 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 |
| | - num_epochs: 15 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
| | | No log | 1.0 | 42 | 0.3257 | 0.8718 | 0.8998 | 0.8522 | |
| | | No log | 2.0 | 84 | 0.1861 | 0.9451 | 0.9573 | 0.9217 | |
| | | No log | 3.0 | 126 | 0.1474 | 0.9492 | 0.9595 | 0.9304 | |
| | | No log | 4.0 | 168 | 0.1156 | 0.9617 | 0.9682 | 0.9478 | |
| | | No log | 5.0 | 210 | 0.1185 | 0.9536 | 0.9637 | 0.9391 | |
| | | No log | 6.0 | 252 | 0.1133 | 0.9492 | 0.9595 | 0.9304 | |
| | | No log | 7.0 | 294 | 0.1098 | 0.9580 | 0.9679 | 0.9391 | |
| | | No log | 8.0 | 336 | 0.1084 | 0.9536 | 0.9637 | 0.9391 | |
| | | No log | 9.0 | 378 | 0.1167 | 0.9536 | 0.9637 | 0.9391 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.42.3 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.19.1 |
