---
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: 0.8571428571428571
---

<!-- 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: 0.4634
- Accuracy: 0.8571

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0639        | 0.99  | 18   | 1.1575          | 0.6873   |
| 1.0962        | 1.97  | 36   | 0.8400          | 0.7336   |
| 0.8715        | 2.96  | 54   | 0.7163          | 0.7915   |
| 0.7241        | 4.0   | 73   | 0.6331          | 0.7992   |
| 0.6171        | 4.99  | 91   | 0.5140          | 0.8340   |
| 0.5467        | 5.97  | 109  | 0.4848          | 0.8610   |
| 0.518         | 6.96  | 127  | 0.4585          | 0.8456   |
| 0.4543        | 8.0   | 146  | 0.4549          | 0.8726   |
| 0.4378        | 8.99  | 164  | 0.4448          | 0.8571   |
| 0.431         | 9.86  | 180  | 0.4634          | 0.8571   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2