---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-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: 0.9828042328042328
---

<!-- 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-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: 0.0684
- Accuracy: 0.9828

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2075        | 0.98  | 33   | 0.5666          | 0.8519   |
| 0.2022        | 1.98  | 66   | 0.2523          | 0.9127   |
| 0.1206        | 2.98  | 99   | 0.1576          | 0.9497   |
| 0.0897        | 3.98  | 132  | 0.1421          | 0.9563   |
| 0.0564        | 4.98  | 165  | 0.1114          | 0.9656   |
| 0.0475        | 5.98  | 198  | 0.0678          | 0.9815   |
| 0.0332        | 6.98  | 231  | 0.0819          | 0.9775   |
| 0.0234        | 7.98  | 264  | 0.0679          | 0.9802   |
| 0.0126        | 8.98  | 297  | 0.0684          | 0.9828   |
| 0.0306        | 9.98  | 330  | 0.0719          | 0.9815   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2