| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: medlid-identify | |
| 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. --> | |
| # medlid-identify | |
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1248 | |
| - Precision: 0.4410 | |
| - Recall: 0.4209 | |
| - F1: 0.4307 | |
| - Accuracy: 0.9541 | |
| ## 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: 81 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 4 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | No log | 1.0 | 381 | 0.1297 | 0.3898 | 0.3032 | 0.3411 | 0.9525 | | |
| | 0.1774 | 2.0 | 762 | 0.1191 | 0.4485 | 0.3489 | 0.3925 | 0.9551 | | |
| | 0.1177 | 3.0 | 1143 | 0.1216 | 0.4341 | 0.4209 | 0.4274 | 0.9544 | | |
| | 0.0974 | 4.0 | 1524 | 0.1248 | 0.4410 | 0.4209 | 0.4307 | 0.9541 | | |
| ### Framework versions | |
| - Transformers 4.30.2 | |
| - Pytorch 1.11.0 | |
| - Datasets 2.13.1 | |
| - Tokenizers 0.13.3 | |