--- 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: 0.0319 - Accuracy: 0.9918 ## 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 | 122 | 0.8579 | 0.8574 | | No log | 2.0 | 244 | 0.3430 | 0.9645 | | No log | 3.0 | 366 | 0.1552 | 0.9810 | | No log | 4.0 | 488 | 0.0981 | 0.9840 | | 0.6956 | 5.0 | 610 | 0.0636 | 0.9887 | | 0.6956 | 6.0 | 732 | 0.0499 | 0.9892 | | 0.6956 | 7.0 | 854 | 0.0398 | 0.9907 | | 0.6956 | 8.0 | 976 | 0.0346 | 0.9918 | | 0.0742 | 9.0 | 1098 | 0.0321 | 0.9918 | | 0.0742 | 10.0 | 1220 | 0.0319 | 0.9918 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0