tuning-sentiment-abp-pos
This model is a fine-tuned version of 5CD-AI/Vietnamese-Sentiment-visobert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5678
- Accuracy: 0.8153
- F1: 0.8137
- Precision: 0.8548
- Recall: 0.8001
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4963 | 1.0 | 799 | 0.4323 | 0.8203 | 0.8122 | 0.8699 | 0.7992 |
| 0.3918 | 2.0 | 1598 | 0.4477 | 0.8223 | 0.8175 | 0.8720 | 0.7997 |
| 0.3535 | 3.0 | 2397 | 0.4750 | 0.8223 | 0.8157 | 0.8747 | 0.8001 |
| 0.3221 | 4.0 | 3196 | 0.5362 | 0.8176 | 0.8150 | 0.8585 | 0.8001 |
| 0.3041 | 5.0 | 3995 | 0.5678 | 0.8153 | 0.8137 | 0.8548 | 0.8001 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for TungCan/tuning-sentiment-abp-pos
Base model
5CD-AI/Vietnamese-Sentiment-visobert