| license: mit | |
| base_model: microsoft/biogpt | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: test-trainer | |
| 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. --> | |
| # test-trainer | |
| This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1628 | |
| - Precision: 0.5127 | |
| - Recall: 0.5849 | |
| - F1: 0.5464 | |
| - Accuracy: 0.9564 | |
| ## 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: 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: 3.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.3056 | 1.0 | 680 | 0.1724 | 0.4135 | 0.5029 | 0.4538 | 0.9478 | | |
| | 0.1401 | 2.0 | 1360 | 0.1542 | 0.4719 | 0.5521 | 0.5089 | 0.9538 | | |
| | 0.0738 | 3.0 | 2040 | 0.1628 | 0.5127 | 0.5849 | 0.5464 | 0.9564 | | |
| ### Framework versions | |
| - Transformers 4.38.2 | |
| - Pytorch 2.2.1+cu121 | |
| - Datasets 2.18.0 | |
| - Tokenizers 0.15.2 | |