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fine-tuned-IndoNLI-Augmented-with-indobert-large-p2-LR-1e-05
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:
- Loss: 0.5974
- Accuracy: 0.8037
- F1: 0.8043
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5944 | 0.5 | 1574 | 0.5977 | 0.7628 | 0.7634 |
| 0.5543 | 1.0 | 3148 | 0.5370 | 0.7904 | 0.7906 |
| 0.4887 | 1.5 | 4722 | 0.5421 | 0.7937 | 0.7947 |
| 0.4772 | 2.0 | 6296 | 0.5125 | 0.8048 | 0.8052 |
| 0.416 | 2.5 | 7870 | 0.5305 | 0.8024 | 0.8028 |
| 0.4036 | 3.0 | 9444 | 0.5319 | 0.8050 | 0.8055 |
| 0.3326 | 3.5 | 11018 | 0.5629 | 0.8022 | 0.8028 |
| 0.3261 | 4.0 | 12592 | 0.5700 | 0.7999 | 0.8006 |
| 0.2904 | 4.5 | 14166 | 0.5974 | 0.8037 | 0.8043 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
