| --- |
| metrics: |
| - f1 |
| - accuracy |
| model-index: |
| - name: aha_class |
| 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_class |
| |
| This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0885 |
| - F1: 0.9580 |
| - Roc Auc: 0.9679 |
| - Accuracy: 0.9391 |
| |
| ## 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 | 0.1723 | 0.95 | 0.9635 | 0.9217 | |
| | No log | 2.0 | 84 | 0.1160 | 0.9576 | 0.9659 | 0.9391 | |
| | No log | 3.0 | 126 | 0.1064 | 0.9492 | 0.9595 | 0.9304 | |
| | No log | 4.0 | 168 | 0.0974 | 0.9540 | 0.9657 | 0.9304 | |
| | No log | 5.0 | 210 | 0.0968 | 0.9580 | 0.9679 | 0.9304 | |
| | No log | 6.0 | 252 | 0.0885 | 0.9580 | 0.9679 | 0.9391 | |
| | No log | 7.0 | 294 | 0.1005 | 0.9580 | 0.9679 | 0.9391 | |
| | No log | 8.0 | 336 | 0.0921 | 0.9664 | 0.9743 | 0.9478 | |
| | No log | 9.0 | 378 | 0.1055 | 0.9580 | 0.9679 | 0.9391 | |
| | No log | 10.0 | 420 | 0.0988 | 0.9664 | 0.9743 | 0.9478 | |
| | No log | 11.0 | 462 | 0.0993 | 0.9664 | 0.9743 | 0.9478 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.3 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.19.1 |
