Vit Plant Disease

--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vit-plant-disease results: - task: type: image-classification name: Image Classification dataset: name: imagefolder type: imagefolder config: default split: validation args: default metrics: - type: accuracy value: 0.9948979591836735 name: Accuracy --- <!-- 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-plant-disease This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0230 - Accuracy: 0.9949 ## 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: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7876 | 1.0 | 25 | 0.1737 | 0.9538 | | 0.0816 | 2.0 | 50 | 0.0704 | 0.9641 | | 0.0165 | 3.0 | 75 | 0.0628 | 0.9692 | | 0.0051 | 4.0 | 100 | 0.0625 | 0.9744 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.8.5 - Tokenizers 0.22.2

Source context: 3 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo Alan04020/vit-plant-disease