---
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: 0.9100719424460432
---

<!-- 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: 0.2633
- Accuracy: 0.9101

## 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: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8026        | 0.96  | 19   | 0.9313          | 0.5612   |
| 0.7571        | 1.97  | 39   | 0.8835          | 0.5755   |
| 0.7061        | 2.99  | 59   | 0.7589          | 0.6871   |
| 0.5911        | 4.0   | 79   | 0.6329          | 0.7482   |
| 0.5194        | 4.96  | 98   | 0.5634          | 0.7698   |
| 0.4471        | 5.97  | 118  | 0.4552          | 0.8165   |
| 0.3743        | 6.99  | 138  | 0.3760          | 0.8525   |
| 0.3686        | 8.0   | 158  | 0.3233          | 0.8705   |
| 0.318         | 8.96  | 177  | 0.3141          | 0.8777   |
| 0.3163        | 9.97  | 197  | 0.2772          | 0.8993   |
| 0.2871        | 10.99 | 217  | 0.2707          | 0.9029   |
| 0.2909        | 11.54 | 228  | 0.2633          | 0.9101   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2