CafeBERT-vinli-ph
This model is a fine-tuned version of uitnlp/CafeBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0114
- Accuracy: 0.9973
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
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0998 | 1.0 | 142 | 1.0549 | 0.4943 |
| 0.8445 | 2.0 | 284 | 0.5590 | 0.8110 |
| 0.4492 | 3.0 | 426 | 0.3256 | 0.8922 |
| 0.4196 | 4.0 | 568 | 0.1561 | 0.9461 |
| 0.2179 | 5.0 | 710 | 0.0965 | 0.9704 |
| 0.1302 | 6.0 | 852 | 0.0632 | 0.9841 |
| 0.1362 | 7.0 | 994 | 0.0418 | 0.9898 |
| 0.0038 | 8.0 | 1136 | 0.0220 | 0.9951 |
| 0.0394 | 9.0 | 1278 | 0.0173 | 0.9960 |
| 0.0034 | 10.0 | 1420 | 0.0114 | 0.9973 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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