--- base_model: vinai/phobert-base-v2 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: PhoBERT-Final_Mixed-aug_swap-2 results: [] --- # PhoBERT-Final_Mixed-aug_swap-2 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: 1.2527 - Accuracy: 0.7 - F1: 0.7091 ## 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: 40 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.8968 | 1.0 | 86 | 0.7005 | 0.68 | 0.6386 | | 0.5324 | 2.0 | 172 | 0.6756 | 0.72 | 0.7272 | | 0.3248 | 3.0 | 258 | 0.7112 | 0.75 | 0.7482 | | 0.2139 | 4.0 | 344 | 0.8172 | 0.75 | 0.7545 | | 0.1439 | 5.0 | 430 | 0.9876 | 0.7 | 0.7041 | | 0.108 | 6.0 | 516 | 1.1343 | 0.72 | 0.7280 | | 0.0784 | 7.0 | 602 | 1.1912 | 0.7 | 0.7091 | | 0.0688 | 8.0 | 688 | 1.2527 | 0.7 | 0.7091 | ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3