--- base_model: vinai/phobert-base-v2 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: PhoBERT-cls-OCR results: [] --- # PhoBERT-cls-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: 0.5749 - Accuracy: 0.8515 - F1: 0.8504 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.5828 | 1.0 | 25 | 0.4474 | 0.8119 | 0.8093 | | 0.3067 | 2.0 | 50 | 0.3924 | 0.8218 | 0.8199 | | 0.1806 | 3.0 | 75 | 0.3979 | 0.8416 | 0.8399 | | 0.1043 | 4.0 | 100 | 0.4770 | 0.8317 | 0.8294 | | 0.0688 | 5.0 | 125 | 0.5007 | 0.8614 | 0.8607 | | 0.0406 | 6.0 | 150 | 0.5332 | 0.8614 | 0.8614 | | 0.0387 | 7.0 | 175 | 0.5748 | 0.8515 | 0.8504 | | 0.0328 | 8.0 | 200 | 0.5749 | 0.8515 | 0.8504 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1