---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8532818532818532
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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: 0.6144
- Accuracy: 0.8533

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1952        | 0.99  | 18   | 1.5914          | 0.5985   |
| 1.3705        | 1.97  | 36   | 1.2164          | 0.6873   |
| 1.026         | 2.96  | 54   | 0.9974          | 0.7375   |
| 0.829         | 4.0   | 73   | 0.7667          | 0.7722   |
| 0.6513        | 4.99  | 91   | 0.6674          | 0.8224   |
| 0.5516        | 5.97  | 109  | 0.5810          | 0.8378   |
| 0.4978        | 6.96  | 127  | 0.5498          | 0.8263   |
| 0.4568        | 8.0   | 146  | 0.5999          | 0.8185   |
| 0.4047        | 8.99  | 164  | 0.5211          | 0.8494   |
| 0.3696        | 9.97  | 182  | 0.5201          | 0.8571   |
| 0.3479        | 10.96 | 200  | 0.5310          | 0.8263   |
| 0.329         | 12.0  | 219  | 0.5439          | 0.8494   |
| 0.3376        | 12.99 | 237  | 0.5050          | 0.8494   |
| 0.2804        | 13.97 | 255  | 0.5709          | 0.8263   |
| 0.2941        | 14.96 | 273  | 0.6376          | 0.8147   |
| 0.3026        | 16.0  | 292  | 0.5447          | 0.8494   |
| 0.2578        | 16.99 | 310  | 0.5056          | 0.8803   |
| 0.219         | 17.97 | 328  | 0.5620          | 0.8610   |
| 0.2403        | 18.96 | 346  | 0.5582          | 0.8456   |
| 0.2258        | 20.0  | 365  | 0.5458          | 0.8494   |
| 0.2265        | 20.99 | 383  | 0.5411          | 0.8533   |
| 0.1893        | 21.97 | 401  | 0.5477          | 0.8494   |
| 0.1896        | 22.96 | 419  | 0.5125          | 0.8494   |
| 0.1976        | 24.0  | 438  | 0.5672          | 0.8340   |
| 0.1725        | 24.99 | 456  | 0.5581          | 0.8456   |
| 0.168         | 25.97 | 474  | 0.5965          | 0.8456   |
| 0.1821        | 26.96 | 492  | 0.5567          | 0.8610   |
| 0.1805        | 28.0  | 511  | 0.5998          | 0.8533   |
| 0.1616        | 28.99 | 529  | 0.5451          | 0.8533   |
| 0.1467        | 29.97 | 547  | 0.5574          | 0.8494   |
| 0.1439        | 30.96 | 565  | 0.5707          | 0.8571   |
| 0.13          | 32.0  | 584  | 0.6019          | 0.8378   |
| 0.1353        | 32.99 | 602  | 0.5952          | 0.8610   |
| 0.1329        | 33.97 | 620  | 0.6262          | 0.8378   |
| 0.1258        | 34.96 | 638  | 0.6314          | 0.8456   |
| 0.1408        | 36.0  | 657  | 0.5761          | 0.8494   |
| 0.1197        | 36.99 | 675  | 0.5703          | 0.8610   |
| 0.1208        | 37.97 | 693  | 0.6247          | 0.8456   |
| 0.1197        | 38.96 | 711  | 0.6026          | 0.8533   |
| 0.1271        | 40.0  | 730  | 0.5953          | 0.8533   |
| 0.1053        | 40.99 | 748  | 0.6070          | 0.8533   |
| 0.0846        | 41.97 | 766  | 0.6094          | 0.8610   |
| 0.1206        | 42.96 | 784  | 0.5912          | 0.8494   |
| 0.1225        | 44.0  | 803  | 0.6074          | 0.8494   |
| 0.1184        | 44.99 | 821  | 0.5943          | 0.8494   |
| 0.1027        | 45.97 | 839  | 0.6084          | 0.8494   |
| 0.1113        | 46.96 | 857  | 0.6034          | 0.8533   |
| 0.0945        | 48.0  | 876  | 0.6106          | 0.8494   |
| 0.1159        | 48.99 | 894  | 0.6143          | 0.8533   |
| 0.0963        | 49.32 | 900  | 0.6144          | 0.8533   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2