--- license: apache-2.0 base_model: Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat 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: 0.9661016949152542 --- # swin-tiny-patch4-window7-224-finetuned-eurosat This model is a fine-tuned version of [Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat](https://huggingface.co/Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.1318 - Accuracy: 0.9661 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 0.94 | 4 | 0.1318 | 0.9661 | | No log | 1.88 | 8 | 0.0986 | 0.9661 | | 0.1962 | 2.82 | 12 | 0.0766 | 0.9661 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2