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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: 1.8388
- Accuracy: 0.2857

## 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 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.6667 | 1    | 1.8176          | 0.0952   |
| No log        | 2.0    | 3    | 1.8961          | 0.1429   |
| No log        | 2.6667 | 4    | 1.9159          | 0.1429   |
| No log        | 4.0    | 6    | 1.8906          | 0.1905   |
| No log        | 4.6667 | 7    | 1.8720          | 0.1905   |
| No log        | 6.0    | 9    | 1.8452          | 0.1905   |
| 1.8626        | 6.6667 | 10   | 1.8388          | 0.2857   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3

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