--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy - f1 model-index: - name: Rice-Plant-Disease-Detection-Model results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.8958333333333334 - name: F1 type: f1 value: 0.8965189410560187 --- # Rice-Plant-Disease-Detection-Model 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 imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.2929 - Accuracy: 0.8958 - F1: 0.8965 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.5517 | 1.0 | 18 | 0.5222 | 0.875 | 0.8754 | | 0.2996 | 2.0 | 36 | 0.3833 | 0.8542 | 0.8564 | | 0.1529 | 3.0 | 54 | 0.3152 | 0.875 | 0.8763 | | 0.0843 | 4.0 | 72 | 0.2929 | 0.8958 | 0.8965 | | 0.0549 | 5.0 | 90 | 0.2756 | 0.875 | 0.8754 | | 0.0402 | 6.0 | 108 | 0.2765 | 0.875 | 0.8754 | | 0.0327 | 7.0 | 126 | 0.2875 | 0.875 | 0.8754 | | 0.0277 | 8.0 | 144 | 0.2938 | 0.875 | 0.8754 | | 0.0244 | 9.0 | 162 | 0.2992 | 0.875 | 0.8754 | | 0.0222 | 10.0 | 180 | 0.2996 | 0.8958 | 0.8960 | | 0.0203 | 11.0 | 198 | 0.3052 | 0.8958 | 0.8960 | | 0.019 | 12.0 | 216 | 0.3087 | 0.8958 | 0.8960 | | 0.018 | 13.0 | 234 | 0.3143 | 0.8958 | 0.8960 | | 0.0171 | 14.0 | 252 | 0.3206 | 0.8958 | 0.8960 | | 0.0164 | 15.0 | 270 | 0.3227 | 0.8958 | 0.8960 | | 0.0158 | 16.0 | 288 | 0.3250 | 0.8958 | 0.8960 | | 0.0155 | 17.0 | 306 | 0.3257 | 0.8958 | 0.8960 | | 0.0152 | 18.0 | 324 | 0.3264 | 0.8958 | 0.8960 | | 0.015 | 19.0 | 342 | 0.3276 | 0.8958 | 0.8960 | | 0.0149 | 20.0 | 360 | 0.3275 | 0.8958 | 0.8960 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cpu - Datasets 2.14.5 - Tokenizers 0.14.0