--- license: apache-2.0 base_model: microsoft/swin-tiny-patch4-window7-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: swin-original-5 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: 0.985320172108327 --- # swin-original-5 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: 0.1231 - Accuracy: 0.9853 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 4.9811 | 1.0 | 247 | 2.3893 | 0.5847 | | 1.6282 | 2.0 | 494 | 0.4871 | 0.9393 | | 0.6306 | 3.0 | 741 | 0.2507 | 0.9709 | | 0.478 | 4.0 | 988 | 0.1513 | 0.9830 | | 0.3531 | 5.0 | 1235 | 0.1231 | 0.9853 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu121 - Datasets 3.0.0 - Tokenizers 0.15.2