--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer datasets: - beans metrics: - accuracy widget: - src: https://huggingface.co/daniejps10/platzi-vit-model-djps10/resolve/main/bean_rust.jpeg example_title: Bean rust - src: https://huggingface.co/daniejps10/platzi-vit-model-djps10/resolve/main/bean_healthy.jpeg example_title: Healthy model-index: - name: platzi-vit-model-djps10 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: 1.0 --- # platzi-vit-model-djps10 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: 0.0022 - Accuracy: 1.0 ## 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: 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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0024 | 3.85 | 500 | 0.0022 | 1.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.3 - Tokenizers 0.13.3