---
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: 0.7674418604651163
---

<!-- 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: 0.6503
- Accuracy: 0.7674

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0764        | 0.99  | 18   | 0.8915          | 0.6318   |
| 0.7888        | 1.97  | 36   | 0.7533          | 0.6860   |
| 0.707         | 2.96  | 54   | 0.7525          | 0.6977   |
| 0.6115        | 4.0   | 73   | 0.6723          | 0.7403   |
| 0.5552        | 4.99  | 91   | 0.7092          | 0.7093   |
| 0.5057        | 5.97  | 109  | 0.6733          | 0.7326   |
| 0.4761        | 6.96  | 127  | 0.6893          | 0.7326   |
| 0.4393        | 8.0   | 146  | 0.6933          | 0.7287   |
| 0.4284        | 8.99  | 164  | 0.6348          | 0.7519   |
| 0.4084        | 9.86  | 180  | 0.6503          | 0.7674   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0