---
license: apache-2.0
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: 1.0
---

<!-- 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: 0.0133
- Accuracy: 1.0

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8235        | 1.0   | 13   | 0.6034          | 0.9239   |
| 0.5091        | 2.0   | 26   | 0.1870          | 0.9728   |
| 0.273         | 3.0   | 39   | 0.0895          | 0.9946   |
| 0.1401        | 4.0   | 52   | 0.0543          | 0.9946   |
| 0.0936        | 5.0   | 65   | 0.0484          | 0.9891   |
| 0.091         | 6.0   | 78   | 0.0498          | 0.9891   |
| 0.0603        | 7.0   | 91   | 0.0133          | 1.0      |
| 0.0421        | 8.0   | 104  | 0.0196          | 0.9946   |
| 0.0557        | 9.0   | 117  | 0.0172          | 0.9946   |
| 0.0552        | 10.0  | 130  | 0.0103          | 1.0      |
| 0.045         | 11.0  | 143  | 0.0082          | 1.0      |
| 0.0355        | 12.0  | 156  | 0.0071          | 1.0      |
| 0.0491        | 13.0  | 169  | 0.0087          | 1.0      |
| 0.0384        | 14.0  | 182  | 0.0065          | 1.0      |
| 0.0324        | 15.0  | 195  | 0.0061          | 1.0      |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3