--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: swin-tiny-patch4-window7-224-blank_img 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: 0.9796511627906976 --- # swin-tiny-patch4-window7-224-blank_img This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0726 - Accuracy: 0.9797 ## 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: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1329 | 0.99 | 72 | 0.0882 | 0.9767 | | 0.1247 | 1.99 | 144 | 0.0805 | 0.9767 | | 0.0742 | 2.99 | 216 | 0.0721 | 0.9767 | | 0.0745 | 3.99 | 288 | 0.0726 | 0.9797 | | 0.1289 | 4.99 | 360 | 0.0848 | 0.9729 | ### Framework versions - Transformers 4.26.1 - Pytorch 2.1.0+cu121 - Datasets 2.15.0 - Tokenizers 0.13.3