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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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1758
- Accuracy: 0.4685
- F1: 0.2481
- Precision: 0.4916
- Recall: 0.1894
- Auc Roc: 0.8295

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | F1     | Precision | Recall | Auc Roc |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 0.2027        | 1.0     | 1963  | 0.1984          | 0.3955   | 0.0496 | 0.1271    | 0.0500 | 0.7076  |
| 0.1966        | 2.0     | 3926  | 0.1890          | 0.4000   | 0.0776 | 0.1877    | 0.0655 | 0.7667  |
| 0.1899        | 3.0     | 5889  | 0.1839          | 0.4160   | 0.1013 | 0.3830    | 0.0821 | 0.7890  |
| 0.186         | 4.0     | 7852  | 0.1829          | 0.4555   | 0.1097 | 0.3752    | 0.0904 | 0.7985  |
| 0.1833        | 5.0     | 9815  | 0.1797          | 0.4205   | 0.1424 | 0.3515    | 0.1073 | 0.8092  |
| 0.1845        | 6.0     | 11778 | 0.1771          | 0.4400   | 0.1255 | 0.4225    | 0.1026 | 0.8153  |
| 0.1788        | 7.0     | 13741 | 0.1769          | 0.4430   | 0.1472 | 0.3464    | 0.1114 | 0.8186  |
| 0.1769        | 8.0     | 15704 | 0.1756          | 0.4426   | 0.1448 | 0.3627    | 0.1132 | 0.8227  |
| 0.1792        | 9.0     | 17667 | 0.1745          | 0.4323   | 0.1653 | 0.3995    | 0.1252 | 0.8250  |
| 0.1755        | 10.0    | 19630 | 0.1745          | 0.4319   | 0.1842 | 0.4664    | 0.1400 | 0.8261  |
| 0.171         | 11.0    | 21593 | 0.1735          | 0.4400   | 0.1868 | 0.5672    | 0.1441 | 0.8285  |
| 0.17          | 12.0    | 23556 | 0.1744          | 0.4540   | 0.1907 | 0.5407    | 0.1462 | 0.8293  |
| 0.1726        | 13.0    | 25519 | 0.1745          | 0.4630   | 0.1750 | 0.4862    | 0.1339 | 0.8304  |
| 0.1715        | 14.0    | 27482 | 0.1732          | 0.4362   | 0.2047 | 0.5735    | 0.1524 | 0.8308  |
| 0.17          | 15.0    | 29445 | 0.1734          | 0.4504   | 0.2080 | 0.4848    | 0.1581 | 0.8316  |
| 0.168         | 16.0    | 31408 | 0.1736          | 0.4515   | 0.2320 | 0.5226    | 0.1791 | 0.8299  |
| 0.1688        | 17.0    | 33371 | 0.1729          | 0.4524   | 0.2315 | 0.5568    | 0.1780 | 0.8317  |
| 0.1663        | 18.0    | 35334 | 0.1748          | 0.4683   | 0.2146 | 0.5260    | 0.1617 | 0.8295  |
| 0.1631        | 19.0    | 37297 | 0.1747          | 0.4529   | 0.2444 | 0.5011    | 0.1908 | 0.8285  |
| 0.1649        | 20.0    | 39260 | 0.1748          | 0.4522   | 0.2404 | 0.4746    | 0.1850 | 0.8298  |
| 0.1634        | 21.0    | 41223 | 0.1747          | 0.4486   | 0.2213 | 0.5125    | 0.1655 | 0.8295  |
| 0.1621        | 22.0    | 43186 | 0.1745          | 0.4499   | 0.2420 | 0.4825    | 0.1865 | 0.8297  |
| 0.1605        | 23.0    | 45149 | 0.1753          | 0.4676   | 0.2206 | 0.4963    | 0.1669 | 0.8298  |
| 0.1573        | 24.0    | 47112 | 0.1762          | 0.4605   | 0.2409 | 0.4814    | 0.1854 | 0.8286  |
| 0.161         | 25.0    | 49075 | 0.1758          | 0.4685   | 0.2481 | 0.4916    | 0.1894 | 0.8295  |
| 0.158         | 26.0    | 51038 | 0.1761          | 0.4604   | 0.2445 | 0.4856    | 0.1883 | 0.8274  |
| 0.1576        | 27.0    | 53001 | 0.1765          | 0.4608   | 0.2539 | 0.4742    | 0.1981 | 0.8290  |
| 0.1567        | 28.0    | 54964 | 0.1767          | 0.4558   | 0.2550 | 0.4835    | 0.1959 | 0.8285  |
| 0.1585        | 29.0    | 56927 | 0.1767          | 0.4602   | 0.2485 | 0.4882    | 0.1898 | 0.8276  |
| 0.1551        | 29.9851 | 58860 | 0.1768          | 0.4616   | 0.2527 | 0.4797    | 0.1941 | 0.8281  |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.5.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1

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