--- base_model: vinai/phobert-base-v2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: intent-classification results: [] --- # intent-classification This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/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