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fine-tuned-IndoNLI-Basic-with-indobert-large-p2
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: 1.2497
- Accuracy: 0.7751
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 16
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.978 | 1.0 | 161 | 0.8505 | 0.6236 |
0.6752 | 2.0 | 322 | 0.6163 | 0.7542 |
0.5579 | 3.0 | 483 | 0.6259 | 0.7551 |
0.4328 | 4.0 | 644 | 0.6153 | 0.7706 |
0.3217 | 5.0 | 805 | 0.6348 | 0.7711 |
0.229 | 6.0 | 966 | 0.7245 | 0.7720 |
0.1688 | 7.0 | 1127 | 0.8032 | 0.7774 |
0.1258 | 8.0 | 1288 | 0.8898 | 0.7742 |
0.0942 | 9.0 | 1449 | 0.9629 | 0.7651 |
0.0718 | 10.0 | 1610 | 0.9848 | 0.7783 |
0.0635 | 11.0 | 1771 | 1.0794 | 0.7674 |
0.0407 | 12.0 | 1932 | 1.1378 | 0.7679 |
0.0394 | 13.0 | 2093 | 1.2195 | 0.7651 |
0.0323 | 14.0 | 2254 | 1.2151 | 0.7756 |
0.0235 | 15.0 | 2415 | 1.2509 | 0.7711 |
0.0277 | 16.0 | 2576 | 1.2497 | 0.7751 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2