| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: output | |
| results: [] | |
| <!-- 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. --> | |
| # output | |
| This model was trained from scratch on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5522 | |
| - Accuracy: 0.8706 | |
| - Precision: 0.9221 | |
| - Recall: 0.8285 | |
| - F1: 0.8728 | |
| ## 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: 5e-05 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 16 | |
| - seed: 0 | |
| - 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 | Accuracy | Precision | Recall | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | |
| | 0.2351 | 0.49 | 500 | 0.4091 | 0.8641 | 0.8835 | 0.8596 | 0.8714 | | |
| | 0.206 | 0.98 | 1000 | 0.4545 | 0.8594 | 0.9210 | 0.8068 | 0.8601 | | |
| | 0.1315 | 1.47 | 1500 | 0.5653 | 0.8660 | 0.8769 | 0.8722 | 0.8745 | | |
| | 0.1503 | 1.96 | 2000 | 0.5522 | 0.8706 | 0.9221 | 0.8285 | 0.8728 | | |
| ### Framework versions | |
| - Transformers 4.27.4 | |
| - Pytorch 1.13.1+cu116 | |
| - Tokenizers 0.13.2 | |