| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: bert-paper-classifier | |
| 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. --> | |
| # bert-paper-classifier | |
| This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.8059 | |
| - Accuracy: 0.586 | |
| ## 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: 64 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - 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 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 1.8012 | 1.0 | 16 | 1.8824 | 0.584 | | |
| | 1.4111 | 2.0 | 32 | 1.8159 | 0.568 | | |
| | 1.3755 | 3.0 | 48 | 1.8059 | 0.586 | | |
| ### Framework versions | |
| - Transformers 4.28.1 | |
| - Pytorch 2.0.0+cu117 | |
| - Datasets 2.11.0 | |
| - Tokenizers 0.13.3 | |