phobert-finetuned-victsd-constructiveness-v2
This model is a fine-tuned version of vinai/phobert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5120
- Accuracy: 0.816
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5246 | 1.0 | 219 | 0.4076 | 0.8115 |
| 0.3989 | 2.0 | 438 | 0.4152 | 0.8045 |
| 0.3335 | 3.0 | 657 | 0.4046 | 0.8225 |
| 0.2706 | 4.0 | 876 | 0.4414 | 0.8115 |
| 0.1958 | 5.0 | 1095 | 0.5120 | 0.816 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
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Model tree for funa21/phobert-finetuned-victsd-constructiveness-v2
Base model
vinai/phobert-base