| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: deepset-Covid-bert-LitCovid-v1.0 | |
| 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. --> | |
| # deepset-Covid-bert-LitCovid-v1.0 | |
| This model is a fine-tuned version of [deepset/covid_bert_base](https://huggingface.co/deepset/covid_bert_base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1135 | |
| - F1: 0.8906 | |
| - Roc Auc: 0.9280 | |
| - Accuracy: 0.7860 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| | |
| | 0.1188 | 1.0 | 3120 | 0.1135 | 0.8906 | 0.9280 | 0.7860 | | |
| ### Framework versions | |
| - Transformers 4.28.0 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |