--- base_model: airesearch/wangchanberta-base-att-spm-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: sentence-tokenizer-th results: [] --- # sentence-tokenizer-th This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1955 - Precision: 0.0 - Recall: 0.0 - F1: 0.0 - Accuracy: 0.9244 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:| | 0.2171 | 1.0 | 9624 | 0.1903 | 0.0 | 0.0 | 0.0 | 0.9239 | | 0.1923 | 2.0 | 19248 | 0.1868 | 0.0 | 0.0 | 0.0 | 0.9253 | | 0.1645 | 3.0 | 28872 | 0.1955 | 0.0 | 0.0 | 0.0 | 0.9244 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1