Swin.ham Finetuned SkinDisease

--- library_name: transformers license: apache-2.0 base_model: microsoft/swin-base-patch4-window7-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: swin.ham-finetuned-SkinDisease results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: test args: default metrics: - name: Accuracy type: accuracy value: 0.9100899100899101 --- # swin.ham-finetuned-SkinDisease This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.2795 - Accuracy: 0.9101 ## 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: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - 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 - lr_scheduler_warmup_steps: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.0891 | 1.0 | 110 | 0.5916 | 0.7812 | | 1.8750 | 2.0 | 220 | 0.4399 | 0.8402 | | 1.3808 | 3.0 | 330 | 0.4319 | 0.8452 | | 1.1637 | 4.0 | 440 | 0.3230 | 0.8821 | | 0.9251 | 5.0 | 550 | 0.3200 | 0.8841 | | 0.8611 | 6.0 | 660 | 0.4317 | 0.8571 | | 0.5843 | 7.0 | 770 | 0.3354 | 0.8931 | | 0.4426 | 8.0 | 880 | 0.3014 | 0.9021 | | 0.3569 | 9.0 | 990 | 0.2857 | 0.9131 | | 0.3473 | 10.0 | 1100 | 0.2795 | 0.9101 | ### Framework versions - Transformers 5.5.4 - Pytorch 2.10.0+cu128 - Datasets 4.8.4 - Tokenizers 0.22.2