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fine-tuned-IndoNLI-Translated-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: 0.6141
- Accuracy: 0.8091
- F1: 0.8096
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 |
|---|---|---|---|---|---|
| 0.588 | 0.5 | 1533 | 0.5476 | 0.7836 | 0.7841 |
| 0.5415 | 1.0 | 3066 | 0.5186 | 0.8006 | 0.8014 |
| 0.4561 | 1.5 | 4599 | 0.5009 | 0.8088 | 0.8090 |
| 0.4711 | 2.0 | 6132 | 0.4981 | 0.8077 | 0.8071 |
| 0.4016 | 2.5 | 7665 | 0.5234 | 0.8057 | 0.8063 |
| 0.4101 | 3.0 | 9198 | 0.5096 | 0.8109 | 0.8114 |
| 0.3104 | 3.5 | 10731 | 0.5465 | 0.8113 | 0.8113 |
| 0.3256 | 4.0 | 12264 | 0.5440 | 0.8107 | 0.8113 |
| 0.2768 | 4.5 | 13797 | 0.6141 | 0.8091 | 0.8096 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
