---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat-people
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: images
      split: train
      args: images
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.952
---

<!-- 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-people

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: 0.1711
- Accuracy: 0.952

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 0.3073          | 0.912    |
| No log        | 2.0   | 8    | 0.2076          | 0.92     |
| 0.4055        | 3.0   | 12   | 0.1789          | 0.928    |
| 0.4055        | 4.0   | 16   | 0.1911          | 0.928    |
| 0.3045        | 5.0   | 20   | 0.1695          | 0.928    |
| 0.3045        | 6.0   | 24   | 0.1756          | 0.944    |
| 0.3045        | 7.0   | 28   | 0.1751          | 0.944    |
| 0.2419        | 8.0   | 32   | 0.1727          | 0.944    |
| 0.2419        | 9.0   | 36   | 0.1711          | 0.952    |
| 0.2375        | 10.0  | 40   | 0.1711          | 0.952    |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3