| --- |
| library_name: transformers |
| base_model: airesearch/wangchanberta-base-att-spm-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - orchid_corpus |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: my_test_model |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: orchid_corpus |
| type: orchid_corpus |
| config: thai_orchid_dataset |
| split: test |
| args: thai_orchid_dataset |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.6866152910160211 |
| - name: Recall |
| type: recall |
| value: 0.6612566160817172 |
| - name: F1 |
| type: f1 |
| value: 0.673697406254042 |
| - name: Accuracy |
| type: accuracy |
| value: 0.8615229701891011 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # my_test_model |
|
|
| 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 orchid_corpus dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4402 |
| - Precision: 0.6866 |
| - Recall: 0.6613 |
| - F1: 0.6737 |
| - Accuracy: 0.8615 |
| |
| ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.6071 | 1.0 | 1157 | 0.4812 | 0.6686 | 0.6451 | 0.6566 | 0.8524 | |
| | 0.4831 | 2.0 | 2314 | 0.4402 | 0.6866 | 0.6613 | 0.6737 | 0.8615 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
