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timi-domain-classification-phobert-v2
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3059
- Precision: 0.9083
- F1: 0.8713
- Accuracy: 0.9373
- Recall: 0.8372
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | F1 | Accuracy | Recall |
|---|---|---|---|---|---|---|---|
| 0.1591 | 1.0 | 489 | 0.2445 | 0.8407 | 0.8216 | 0.9116 | 0.8034 |
| 0.0688 | 2.0 | 978 | 0.2217 | 0.8657 | 0.8620 | 0.9303 | 0.8584 |
| 0.0239 | 3.0 | 1467 | 0.3059 | 0.9083 | 0.8713 | 0.9373 | 0.8372 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.1.0
- Tokenizers 0.13.3
