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fine-tuned-IndoNLI-Basic-with-indobert-base-uncased
This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6336
- Accuracy: 0.7779
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: 16
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0949 | 1.0 | 161 | 0.9773 | 0.4980 |
| 0.8844 | 2.0 | 322 | 0.7456 | 0.6859 |
| 0.7276 | 3.0 | 483 | 0.6554 | 0.7437 |
| 0.6326 | 4.0 | 644 | 0.6124 | 0.7615 |
| 0.5654 | 5.0 | 805 | 0.6057 | 0.7656 |
| 0.5108 | 6.0 | 966 | 0.6196 | 0.7747 |
| 0.4741 | 7.0 | 1127 | 0.6219 | 0.7738 |
| 0.4388 | 8.0 | 1288 | 0.6241 | 0.7783 |
| 0.4128 | 9.0 | 1449 | 0.6329 | 0.7792 |
| 0.3964 | 10.0 | 1610 | 0.6336 | 0.7779 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
