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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: 0.2235
- Accuracy: 0.9167

## 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: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 24

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 0.5572          | 0.7917   |
| No log        | 2.0   | 7    | 0.4659          | 0.75     |
| 0.4694        | 2.86  | 10   | 0.4492          | 0.7917   |
| 0.4694        | 4.0   | 14   | 0.2875          | 0.875    |
| 0.4694        | 4.86  | 17   | 0.2463          | 0.875    |
| 0.3403        | 6.0   | 21   | 0.2235          | 0.9167   |
| 0.3403        | 6.86  | 24   | 0.2371          | 0.9167   |
| 0.3403        | 8.0   | 28   | 0.1865          | 0.9167   |
| 0.2581        | 8.86  | 31   | 0.3179          | 0.8333   |
| 0.2581        | 10.0  | 35   | 0.2050          | 0.8333   |
| 0.2581        | 10.86 | 38   | 0.2885          | 0.8333   |
| 0.192         | 12.0  | 42   | 0.2371          | 0.7917   |
| 0.192         | 12.86 | 45   | 0.1783          | 0.875    |
| 0.192         | 14.0  | 49   | 0.1164          | 0.9167   |
| 0.1479        | 14.86 | 52   | 0.1250          | 0.9167   |
| 0.1479        | 16.0  | 56   | 0.1491          | 0.875    |
| 0.1479        | 16.86 | 59   | 0.1409          | 0.875    |
| 0.1348        | 18.0  | 63   | 0.1192          | 0.9167   |
| 0.1348        | 18.86 | 66   | 0.1168          | 0.9167   |
| 0.1461        | 20.0  | 70   | 0.1106          | 0.9167   |
| 0.1461        | 20.57 | 72   | 0.1101          | 0.9167   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

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