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# swin-small-patch4-window7-224-finetuned-eurosat

This model is a fine-tuned version of [microsoft/swin-small-patch4-window7-224](https://huggingface.co/microsoft/swin-small-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5541
- Accuracy: 0.8472

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.8572        | 1.0     | 48   | 2.6775          | 0.2226   |
| 1.6357        | 2.0     | 96   | 1.3411          | 0.5519   |
| 1.076         | 3.0     | 144  | 0.9200          | 0.6973   |
| 1.0091        | 4.0     | 192  | 0.8266          | 0.7062   |
| 0.777         | 5.0     | 240  | 0.6904          | 0.7685   |
| 0.6453        | 6.0     | 288  | 0.6149          | 0.7864   |
| 0.6124        | 7.0     | 336  | 0.6207          | 0.7923   |
| 0.5204        | 8.0     | 384  | 0.6130          | 0.7908   |
| 0.529         | 9.0     | 432  | 0.6334          | 0.8042   |
| 0.4394        | 10.0    | 480  | 0.5370          | 0.8249   |
| 0.4398        | 11.0    | 528  | 0.5589          | 0.8249   |
| 0.3996        | 12.0    | 576  | 0.5391          | 0.8501   |
| 0.3585        | 13.0    | 624  | 0.5796          | 0.8205   |
| 0.3276        | 14.0    | 672  | 0.5851          | 0.8338   |
| 0.3382        | 15.0    | 720  | 0.5508          | 0.8457   |
| 0.3212        | 16.0    | 768  | 0.5279          | 0.8605   |
| 0.3226        | 17.0    | 816  | 0.5769          | 0.8338   |
| 0.2836        | 18.0    | 864  | 0.5942          | 0.8294   |
| 0.2743        | 19.0    | 912  | 0.5862          | 0.8309   |
| 0.2637        | 20.0    | 960  | 0.5586          | 0.8234   |
| 0.2567        | 21.0    | 1008 | 0.5335          | 0.8427   |
| 0.2932        | 22.0    | 1056 | 0.5653          | 0.8383   |
| 0.2532        | 23.0    | 1104 | 0.5493          | 0.8368   |
| 0.2286        | 24.0    | 1152 | 0.5798          | 0.8383   |
| 0.206         | 25.0    | 1200 | 0.5623          | 0.8487   |
| 0.2288        | 26.0    | 1248 | 0.5566          | 0.8442   |
| 0.2059        | 27.0    | 1296 | 0.5437          | 0.8457   |
| 0.1904        | 28.0    | 1344 | 0.5500          | 0.8338   |
| 0.2416        | 29.0    | 1392 | 0.5563          | 0.8487   |
| 0.1967        | 29.3789 | 1410 | 0.5541          | 0.8472   |


### Framework versions

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

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