---
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: 0.7289719626168224
---

<!-- 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: 0.6419
- Accuracy: 0.7290

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0627        | 1.0   | 15   | 0.9620          | 0.5467   |
| 0.8137        | 2.0   | 30   | 0.7780          | 0.6589   |
| 0.7516        | 3.0   | 45   | 0.7737          | 0.6822   |
| 0.6395        | 4.0   | 60   | 0.7195          | 0.6869   |
| 0.579         | 5.0   | 75   | 0.6742          | 0.7150   |
| 0.5505        | 6.0   | 90   | 0.6526          | 0.7243   |
| 0.5312        | 7.0   | 105  | 0.6616          | 0.7290   |
| 0.4793        | 8.0   | 120  | 0.6470          | 0.7430   |
| 0.4443        | 9.0   | 135  | 0.6375          | 0.7383   |
| 0.4685        | 10.0  | 150  | 0.6419          | 0.7290   |


### Framework versions

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