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# 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: 0.6599
- Accuracy: 0.5614

## 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: Use OptimizerNames.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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 0.6771          | 0.5789   |
| No log        | 2.0   | 8    | 0.6415          | 0.6140   |
| 0.6754        | 3.0   | 12   | 0.6351          | 0.6667   |
| 0.6754        | 4.0   | 16   | 0.6629          | 0.5614   |
| 0.6122        | 5.0   | 20   | 0.6631          | 0.5789   |
| 0.6122        | 6.0   | 24   | 0.6529          | 0.5789   |
| 0.6122        | 7.0   | 28   | 0.6541          | 0.5614   |
| 0.5894        | 8.0   | 32   | 0.6599          | 0.5614   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0

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