---
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: 0.9341978866474544
---

<!-- 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: 0.1507
- Accuracy: 0.9342

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2891        | 1.0   | 146  | 0.2322          | 0.9068   |
| 0.2609        | 2.0   | 292  | 0.1710          | 0.9227   |
| 0.2417        | 3.0   | 438  | 0.1830          | 0.9251   |
| 0.2406        | 4.0   | 584  | 0.1809          | 0.9198   |
| 0.2113        | 5.0   | 730  | 0.1631          | 0.9289   |
| 0.1812        | 6.0   | 876  | 0.1561          | 0.9308   |
| 0.2082        | 7.0   | 1022 | 0.1507          | 0.9342   |
| 0.1922        | 8.0   | 1168 | 0.1611          | 0.9294   |
| 0.1715        | 9.0   | 1314 | 0.1536          | 0.9308   |
| 0.1675        | 10.0  | 1460 | 0.1609          | 0.9289   |
| 0.194         | 11.0  | 1606 | 0.1499          | 0.9337   |
| 0.1706        | 12.0  | 1752 | 0.1514          | 0.9323   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1