metadata
library_name: transformers
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
results
This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.8
- F1 Weighted: 0.7852
- Loss: 0.7316
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: 2.7820079535067715e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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: 17
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Accuracy | F1 Weighted | Validation Loss |
|---|---|---|---|---|---|
| No log | 1.0 | 6 | 0.24 | 0.1029 | 1.2189 |
| 1.2118 | 2.0 | 12 | 0.32 | 0.2521 | 1.1035 |
| 1.2118 | 3.0 | 18 | 0.64 | 0.5214 | 1.0049 |
| 1.0516 | 4.0 | 24 | 0.68 | 0.6394 | 0.8500 |
| 1.0014 | 5.0 | 30 | 0.64 | 0.628 | 0.8799 |
| 1.0014 | 6.0 | 36 | 0.68 | 0.6835 | 0.7949 |
| 1.1235 | 7.0 | 42 | 0.72 | 0.6931 | 0.8320 |
| 1.1235 | 8.0 | 48 | 0.64 | 0.6368 | 0.7677 |
| 1.0837 | 9.0 | 54 | 0.8 | 0.7852 | 0.7316 |
| 0.9824 | 10.0 | 60 | 0.76 | 0.7324 | 0.7318 |
| 0.9824 | 11.0 | 66 | 0.72 | 0.6966 | 0.7191 |
| 0.8334 | 12.0 | 72 | 0.76 | 0.7346 | 0.7128 |
| 0.8334 | 13.0 | 78 | 0.68 | 0.6430 | 0.7165 |
| 0.7175 | 14.0 | 84 | 0.68 | 0.6430 | 0.7259 |
| 0.6813 | 15.0 | 90 | 0.68 | 0.6430 | 0.7139 |
| 0.6813 | 16.0 | 96 | 0.72 | 0.6981 | 0.6977 |
| 0.6765 | 17.0 | 102 | 0.72 | 0.6981 | 0.6941 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1