| license: apache-2.0 | |
| tags: | |
| - image-classification | |
| - vision | |
| - generated_from_trainer | |
| datasets: | |
| - beans | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: vit-base-beans | |
| results: | |
| - task: | |
| name: Image Classification | |
| type: image-classification | |
| dataset: | |
| name: beans | |
| type: beans | |
| config: default | |
| split: validation | |
| args: default | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9924812030075187 | |
| <!-- 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-beans | |
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0818 | |
| - Accuracy: 0.9925 | |
| ## 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: 1337 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.254 | 1.0 | 130 | 0.2244 | 0.9624 | | |
| | 0.2885 | 2.0 | 260 | 0.1098 | 0.9925 | | |
| | 0.1555 | 3.0 | 390 | 0.1041 | 0.9850 | | |
| | 0.092 | 4.0 | 520 | 0.0818 | 0.9925 | | |
| | 0.1591 | 5.0 | 650 | 0.0826 | 0.9850 | | |
| ### Framework versions | |
| - Transformers 4.29.0.dev0 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.11.0 | |
| - Tokenizers 0.13.3 | |