--- license: apache-2.0 tags: - generated_from_trainer datasets: - AI-Lab-Makerere/beans metrics: - accuracy model-index: - name: vit_beans results: - task: type: image-classification name: Image Classification dataset: name: beans type: beans args: default metrics: - type: accuracy value: 0.9699248120300752 name: Accuracy --- # vit_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: 0.1176 - Accuracy: 0.9699 ## 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: 0.0002 - train_batch_size: 16 - 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 ### Framework versions - Transformers 4.14.1 - Pytorch 1.10.2 - Datasets 2.0.0 - Tokenizers 0.10.3