--- base_model: vinai/phobert-base-v2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: model results: [] --- # model 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: 0.1123 - Accuracy: 0.9762 ## 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 | 95 | 1.0711 | 0.8386 | | No log | 2.0 | 190 | 0.5620 | 0.9286 | | No log | 3.0 | 285 | 0.2919 | 0.9471 | | No log | 4.0 | 380 | 0.1902 | 0.9550 | | No log | 5.0 | 475 | 0.1740 | 0.9656 | | 0.6945 | 6.0 | 570 | 0.1462 | 0.9709 | | 0.6945 | 7.0 | 665 | 0.1347 | 0.9735 | | 0.6945 | 8.0 | 760 | 0.1146 | 0.9762 | | 0.6945 | 9.0 | 855 | 0.1154 | 0.9762 | | 0.6945 | 10.0 | 950 | 0.1123 | 0.9762 | ### Framework versions - Transformers 4.36.0 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0