--- library_name: transformers license: apache-2.0 base_model: microsoft/swin-tiny-patch4-window7-224 tags: - generated_from_trainer datasets: - image_folder metrics: - accuracy model-index: - name: win_eurosat results: - task: name: Image Classification type: image-classification dataset: name: image_folder type: image_folder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.986574074074074 --- # win_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 image_folder dataset. It achieves the following results on the evaluation set: - Loss: 0.0414 - Accuracy: 0.9866 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.6619 | 1.0 | 608 | 0.0794 | 0.9731 | | 0.7688 | 2.0 | 1216 | 0.0729 | 0.9778 | | 0.3537 | 2.9959 | 1821 | 0.0414 | 0.9866 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.2.0+cpu - Datasets 2.0.0 - Tokenizers 0.21.0