--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - image-classification - vision - generated_from_trainer metrics: - accuracy model-index: - name: vit-base-beans results: [] --- # 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: 0.0670 - 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.2797 | 1.0 | 130 | 0.2151 | 0.9624 | | 0.1301 | 2.0 | 260 | 0.1259 | 0.9774 | | 0.1385 | 3.0 | 390 | 0.0962 | 0.9774 | | 0.0764 | 4.0 | 520 | 0.0670 | 0.9925 | | 0.1154 | 5.0 | 650 | 0.0809 | 0.9774 | ### Framework versions - Transformers 4.47.0.dev0 - Pytorch 2.5.1+cu124 - Datasets 3.1.0 - Tokenizers 0.20.2