---
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: 0.796756082345602
---

<!-- 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: 0.6838
- Accuracy: 0.7968

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.5891        | 0.9966  | 218  | 1.3833          | 0.5723   |
| 1.2997        | 1.9977  | 437  | 1.0831          | 0.6700   |
| 1.1166        | 2.9989  | 656  | 0.9937          | 0.6958   |
| 1.0464        | 4.0     | 875  | 0.9180          | 0.7231   |
| 0.982         | 4.9966  | 1093 | 0.8399          | 0.7432   |
| 0.9472        | 5.9977  | 1312 | 0.8127          | 0.7536   |
| 0.8751        | 6.9989  | 1531 | 0.7852          | 0.7639   |
| 0.9107        | 8.0     | 1750 | 0.7644          | 0.7713   |
| 0.8464        | 8.9966  | 1968 | 0.7322          | 0.7830   |
| 0.8398        | 9.9977  | 2187 | 0.7243          | 0.7798   |
| 0.7534        | 10.9989 | 2406 | 0.7088          | 0.7845   |
| 0.7051        | 12.0    | 2625 | 0.6982          | 0.7935   |
| 0.7359        | 12.9966 | 2843 | 0.6985          | 0.7916   |
| 0.7641        | 13.9977 | 3062 | 0.6838          | 0.7968   |
| 0.7372        | 14.9486 | 3270 | 0.6781          | 0.7968   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1