| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: vit-base-molecul | |
| 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. --> | |
| # vit-base-molecul | |
| This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.6052 | |
| - Accuracy: 0.69 | |
| - F1: 0.6900 | |
| ## 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: 32 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 10 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 0.4633 | 3.85 | 50 | 0.6052 | 0.69 | 0.6900 | | |
| | 0.0341 | 7.69 | 100 | 0.8705 | 0.71 | 0.7100 | | |
| ### Framework versions | |
| - Transformers 4.31.0.dev0 | |
| - Pytorch 2.0.1 | |
| - Datasets 2.13.1 | |
| - Tokenizers 0.11.0 | |