--- base_model: vinai/phobert-base-v2 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: PhoBERT-cls-detail-in-Non_OCR results: [] --- # PhoBERT-cls-detail-in-Non_OCR 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: 0.2037 - Accuracy: 0.93 - F1: 0.9339 ## 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: 2e-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: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 1.1155 | 1.0 | 25 | 0.9023 | 0.68 | 0.5898 | | 0.725 | 2.0 | 50 | 0.4912 | 0.91 | 0.8689 | | 0.4564 | 3.0 | 75 | 0.3118 | 0.92 | 0.8911 | | 0.3084 | 4.0 | 100 | 0.2391 | 0.93 | 0.9339 | | 0.2426 | 5.0 | 125 | 0.2064 | 0.93 | 0.9339 | | 0.182 | 6.0 | 150 | 0.1888 | 0.96 | 0.96 | | 0.1705 | 7.0 | 175 | 0.2049 | 0.93 | 0.9339 | | 0.1599 | 8.0 | 200 | 0.2037 | 0.93 | 0.9339 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3