---
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: 0.9503105590062112
---

<!-- 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: 0.1879
- Accuracy: 0.9503

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6144        | 0.96  | 11   | 1.0071          | 0.8447   |
| 0.8116        | 2.0   | 23   | 0.5227          | 0.8571   |
| 0.6078        | 2.96  | 34   | 0.4213          | 0.8571   |
| 0.5151        | 4.0   | 46   | 0.3357          | 0.8758   |
| 0.4499        | 4.96  | 57   | 0.3467          | 0.9068   |
| 0.4254        | 6.0   | 69   | 0.2344          | 0.9193   |
| 0.3266        | 6.96  | 80   | 0.2107          | 0.9379   |
| 0.3018        | 8.0   | 92   | 0.1818          | 0.9379   |
| 0.3339        | 8.96  | 103  | 0.1928          | 0.9379   |
| 0.2594        | 10.0  | 115  | 0.1936          | 0.9317   |
| 0.2476        | 10.96 | 126  | 0.1543          | 0.9317   |
| 0.2294        | 12.0  | 138  | 0.1827          | 0.9441   |
| 0.2193        | 12.96 | 149  | 0.1676          | 0.9317   |
| 0.1924        | 14.0  | 161  | 0.1553          | 0.9379   |
| 0.2148        | 14.96 | 172  | 0.1387          | 0.9379   |
| 0.1674        | 16.0  | 184  | 0.1449          | 0.9379   |
| 0.1815        | 16.96 | 195  | 0.1833          | 0.9317   |
| 0.1861        | 18.0  | 207  | 0.1818          | 0.9441   |
| 0.1629        | 18.96 | 218  | 0.2484          | 0.9255   |
| 0.1609        | 20.0  | 230  | 0.1661          | 0.9503   |
| 0.132         | 20.96 | 241  | 0.1538          | 0.9441   |
| 0.1468        | 22.0  | 253  | 0.1597          | 0.9565   |
| 0.0926        | 22.96 | 264  | 0.1613          | 0.9565   |
| 0.102         | 24.0  | 276  | 0.1420          | 0.9441   |
| 0.1178        | 24.96 | 287  | 0.1429          | 0.9441   |
| 0.1311        | 26.0  | 299  | 0.1832          | 0.9503   |
| 0.0982        | 26.96 | 310  | 0.2140          | 0.9441   |
| 0.0865        | 28.0  | 322  | 0.2040          | 0.9565   |
| 0.0919        | 28.96 | 333  | 0.1878          | 0.9503   |
| 0.085         | 30.0  | 345  | 0.1935          | 0.9565   |
| 0.0918        | 30.96 | 356  | 0.1787          | 0.9503   |
| 0.0939        | 32.0  | 368  | 0.1932          | 0.9441   |
| 0.1236        | 32.96 | 379  | 0.1736          | 0.9379   |
| 0.0819        | 34.0  | 391  | 0.1798          | 0.9503   |
| 0.0906        | 34.96 | 402  | 0.1937          | 0.9379   |
| 0.0865        | 36.0  | 414  | 0.1809          | 0.9379   |
| 0.0709        | 36.96 | 425  | 0.2062          | 0.9379   |
| 0.0781        | 38.0  | 437  | 0.1749          | 0.9503   |
| 0.0772        | 38.96 | 448  | 0.2176          | 0.9441   |
| 0.0535        | 40.0  | 460  | 0.2164          | 0.9503   |
| 0.0608        | 40.96 | 471  | 0.1976          | 0.9503   |
| 0.072         | 42.0  | 483  | 0.1837          | 0.9441   |
| 0.0657        | 42.96 | 494  | 0.2000          | 0.9565   |
| 0.0824        | 44.0  | 506  | 0.1865          | 0.9503   |
| 0.0584        | 44.96 | 517  | 0.1870          | 0.9565   |
| 0.0556        | 46.0  | 529  | 0.1863          | 0.9503   |
| 0.0516        | 46.96 | 540  | 0.1894          | 0.9503   |
| 0.06          | 47.83 | 550  | 0.1879          | 0.9503   |


### Framework versions

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