--- 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: 0.2895 - Accuracy: 0.9434 ## 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 | 1.1467 | 0.7871 | | No log | 2.0 | 186 | 0.5867 | 0.9057 | | No log | 3.0 | 279 | 0.3947 | 0.9272 | | No log | 4.0 | 372 | 0.3269 | 0.9407 | | No log | 5.0 | 465 | 0.3065 | 0.9407 | | 0.7171 | 6.0 | 558 | 0.2895 | 0.9434 | | 0.7171 | 7.0 | 651 | 0.2980 | 0.9407 | | 0.7171 | 8.0 | 744 | 0.3061 | 0.9407 | | 0.7171 | 9.0 | 837 | 0.3153 | 0.9407 | | 0.7171 | 10.0 | 930 | 0.3177 | 0.9407 | ### Framework versions - Transformers 4.36.0 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0