--- license: apache-2.0 base_model: microsoft/swin-tiny-patch4-window7-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: swin-tiny-patch4-window7-224-finetuned-eurosat 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: 0.9918293236495688 --- # swin-tiny-patch4-window7-224-finetuned-eurosat 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: 0.0520 - Accuracy: 0.9918 ## 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: 6 - eval_batch_size: 6 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0765 | 1.0 | 428 | 0.1101 | 0.9773 | | 0.1014 | 2.0 | 857 | 0.0692 | 0.9825 | | 0.0425 | 3.0 | 1285 | 0.0766 | 0.9814 | | 0.1229 | 4.0 | 1714 | 0.0515 | 0.9873 | | 0.074 | 5.0 | 2142 | 0.0497 | 0.9891 | | 0.0133 | 6.0 | 2571 | 0.0537 | 0.9882 | | 0.0753 | 7.0 | 2999 | 0.0490 | 0.9911 | | 0.0263 | 8.0 | 3428 | 0.0520 | 0.9918 | | 0.0423 | 9.0 | 3856 | 0.0513 | 0.9914 | | 0.0266 | 9.99 | 4280 | 0.0485 | 0.9916 | ### Framework versions - Transformers 4.33.0 - Pytorch 2.0.1+cu117 - Datasets 2.16.0 - Tokenizers 0.13.3