intent-classification
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1902
- Accuracy: 0.9597
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 93 | 1.0236 | 0.8468 |
| No log | 2.0 | 186 | 0.4412 | 0.9355 |
| No log | 3.0 | 279 | 0.2577 | 0.9462 |
| No log | 4.0 | 372 | 0.2303 | 0.9409 |
| No log | 5.0 | 465 | 0.2056 | 0.9516 |
| 0.623 | 6.0 | 558 | 0.2172 | 0.9516 |
| 0.623 | 7.0 | 651 | 0.1973 | 0.9516 |
| 0.623 | 8.0 | 744 | 0.1938 | 0.9597 |
| 0.623 | 9.0 | 837 | 0.1921 | 0.9543 |
| 0.623 | 10.0 | 930 | 0.1902 | 0.9597 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for nguyenvanvi0812/intent-classification
Base model
vinai/phobert-base-v2