--- tags: - generated_from_trainer base_model: airesearch/wangchanberta-base-att-spm-uncased metrics: - accuracy model-index: - name: fine-tune-wangchanberta-TNR-split-headline1 results: [] --- # fine-tune-wangchanberta-TNR-split-headline1 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: 1.0717 - Accuracy: 0.5 ## 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: 32 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.0875 | 1.0 | 5 | 1.0611 | 0.4737 | | 1.0901 | 2.0 | 10 | 1.0551 | 0.4737 | | 1.0898 | 3.0 | 15 | 1.0502 | 0.4737 | | 1.0673 | 4.0 | 20 | 1.0592 | 0.4737 | | 1.0673 | 5.0 | 25 | 1.0477 | 0.4474 | | 1.0689 | 6.0 | 30 | 1.0554 | 0.5263 | | 1.055 | 7.0 | 35 | 1.0717 | 0.5 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1