metadata
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: []
results_fold_4
This model is a fine-tuned version of 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