--- license: cc-by-4.0 base_model: pythainlp/thainer-corpus-v2-base-model tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: token_classification_data_pythainlp results: [] --- # token_classification_data_pythainlp ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 247 | 0.1026 | 0.8297 | 0.8810 | 0.8546 | 0.9736 | | No log | 2.0 | 494 | 0.1113 | 0.8250 | 0.8818 | 0.8524 | 0.9730 | | 0.0356 | 3.0 | 741 | 0.1131 | 0.8300 | 0.8852 | 0.8567 | 0.9726 | | 0.0356 | 4.0 | 988 | 0.1188 | 0.8307 | 0.8899 | 0.8593 | 0.9730 | | 0.02 | 5.0 | 1235 | 0.1187 | 0.8363 | 0.8886 | 0.8616 | 0.9734 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1