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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: 0.6247
- Accuracy: 0.8279

## 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: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.6684        | 1.0     | 43   | 1.5274          | 0.5386   |
| 1.422         | 2.0     | 86   | 1.2167          | 0.5964   |
| 1.2303        | 3.0     | 129  | 0.9840          | 0.6617   |
| 1.0419        | 4.0     | 172  | 0.8583          | 0.7255   |
| 0.886         | 5.0     | 215  | 0.7485          | 0.7389   |
| 0.8443        | 6.0     | 258  | 0.7898          | 0.7463   |
| 0.7685        | 7.0     | 301  | 0.6678          | 0.7745   |
| 0.6999        | 8.0     | 344  | 0.7002          | 0.7730   |
| 0.6128        | 9.0     | 387  | 0.6634          | 0.7982   |
| 0.5588        | 10.0    | 430  | 0.6644          | 0.7789   |
| 0.5829        | 11.0    | 473  | 0.6318          | 0.8116   |
| 0.5234        | 12.0    | 516  | 0.6662          | 0.7864   |
| 0.4712        | 13.0    | 559  | 0.6781          | 0.8042   |
| 0.4042        | 14.0    | 602  | 0.6542          | 0.8131   |
| 0.3966        | 15.0    | 645  | 0.6432          | 0.8086   |
| 0.41          | 16.0    | 688  | 0.6346          | 0.8145   |
| 0.3848        | 17.0    | 731  | 0.6295          | 0.8323   |
| 0.3612        | 18.0    | 774  | 0.6841          | 0.8042   |
| 0.3258        | 19.0    | 817  | 0.6613          | 0.8145   |
| 0.3163        | 20.0    | 860  | 0.6340          | 0.8279   |
| 0.3469        | 21.0    | 903  | 0.6621          | 0.8205   |
| 0.3523        | 22.0    | 946  | 0.6655          | 0.8131   |
| 0.3533        | 23.0    | 989  | 0.6541          | 0.8131   |
| 0.3312        | 24.0    | 1032 | 0.6445          | 0.8116   |
| 0.3095        | 25.0    | 1075 | 0.6519          | 0.8205   |
| 0.2425        | 26.0    | 1118 | 0.6363          | 0.8145   |
| 0.2956        | 27.0    | 1161 | 0.6318          | 0.8294   |
| 0.2629        | 28.0    | 1204 | 0.6217          | 0.8249   |
| 0.2755        | 29.0    | 1247 | 0.6243          | 0.8279   |
| 0.29          | 29.3077 | 1260 | 0.6247          | 0.8279   |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1

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