tuning-sentiment-abp-neu
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: 0.5203
- Accuracy: 0.7812
- F1: 0.6565
- Precision: 0.6573
- Recall: 0.6570
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 261 | 0.3318 | 0.8144 | 0.5907 | 0.6726 | 0.6565 |
| 0.3498 | 2.0 | 522 | 0.3483 | 0.8152 | 0.6042 | 0.6727 | 0.6586 |
| 0.3498 | 3.0 | 783 | 0.3772 | 0.8169 | 0.5855 | 0.6107 | 0.6562 |
| 0.2683 | 4.0 | 1044 | 0.4225 | 0.7887 | 0.6528 | 0.6581 | 0.6576 |
| 0.2683 | 5.0 | 1305 | 0.5203 | 0.7812 | 0.6565 | 0.6573 | 0.6570 |
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-neu
Base model
5CD-AI/Vietnamese-Sentiment-visobert