--- license: apache-2.0 base_model: microsoft/swinv2-tiny-patch4-window8-256 tags: - generated_from_trainer metrics: - accuracy model-index: - name: swinv2-tiny-patch4-window8-256-finetuned-eurosat results: [] --- # swinv2-tiny-patch4-window8-256-finetuned-eurosat This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5112 - Accuracy: 0.7969 ## 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: 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 | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.6594 | 0.9955 | 167 | 0.6860 | 0.7426 | | 0.5427 | 1.9970 | 335 | 0.5231 | 0.7836 | | 0.523 | 2.9985 | 503 | 0.5246 | 0.7912 | | 0.4991 | 4.0 | 671 | 0.5136 | 0.7950 | | 0.4512 | 4.9776 | 835 | 0.5112 | 0.7969 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.2.2 - Datasets 2.19.1 - Tokenizers 0.19.1