--- base_model: clicknext/phayathaibert tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: phayathaibert-thainer results: [] widget: - text: >- ประเทศไทยอยู่ในทวีปเอเชีย example_title: test_example_1 - text: ไทยอยู่ในเจอ example_title: test_example_2 license: mit language: - th library_name: transformers pipeline_tag: token-classification datasets: - pythainlp/thainer-corpus-v2 --- # phayathaibert-thainer This model is a fine-tuned version of [clicknext/phayathaibert](https://huggingface.co/clicknext/phayathaibert) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1324 - Precision: 0.8432 - Recall: 0.8915 - F1: 0.8666 - Accuracy: 0.9735 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 493 | 0.1401 | 0.7300 | 0.7941 | 0.7607 | 0.9607 | | 0.3499 | 2.0 | 986 | 0.1201 | 0.7863 | 0.8464 | 0.8152 | 0.9688 | | 0.0961 | 3.0 | 1479 | 0.1169 | 0.8050 | 0.8663 | 0.8345 | 0.9715 | | 0.0617 | 4.0 | 1972 | 0.1137 | 0.8155 | 0.8656 | 0.8398 | 0.9718 | | 0.0438 | 5.0 | 2465 | 0.1280 | 0.8201 | 0.8714 | 0.8450 | 0.9725 | | 0.0302 | 6.0 | 2958 | 0.1386 | 0.8266 | 0.8730 | 0.8492 | 0.9726 | | 0.0239 | 7.0 | 3451 | 0.1401 | 0.8353 | 0.8789 | 0.8565 | 0.9733 | | 0.0166 | 8.0 | 3944 | 0.1444 | 0.8356 | 0.8782 | 0.8564 | 0.9738 | | 0.0139 | 9.0 | 4437 | 0.1530 | 0.8341 | 0.8785 | 0.8557 | 0.9735 | | 0.0106 | 10.0 | 4930 | 0.1508 | 0.8394 | 0.8782 | 0.8583 | 0.9738 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0