| library_name: transformers | |
| license: mit | |
| base_model: indobenchmark/indobert-base-p1 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: results_fold_4 | |
| 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. --> | |
| # results_fold_4 | |
| This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2303 | |
| - F1: 0.8166 | |
| - Roc Auc: 0.8836 | |
| - Accuracy: 0.7468 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - 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 | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| | |
| | 0.2001 | 1.0 | 1186 | 0.2002 | 0.7755 | 0.8456 | 0.6785 | | |
| | 0.1439 | 2.0 | 2372 | 0.1855 | 0.8030 | 0.8729 | 0.7097 | | |
| | 0.1403 | 3.0 | 3558 | 0.1960 | 0.8141 | 0.8784 | 0.7367 | | |
| | 0.0556 | 4.0 | 4744 | 0.2235 | 0.8128 | 0.8770 | 0.7367 | | |
| | 0.0173 | 5.0 | 5930 | 0.2303 | 0.8166 | 0.8836 | 0.7468 | | |
| ### Framework versions | |
| - Transformers 4.51.3 | |
| - Pytorch 2.7.0+cu128 | |
| - Datasets 3.6.0 | |
| - Tokenizers 0.21.1 | |