---
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: 0.9966577540106952
---

<!-- 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: 0.0271
- Accuracy: 0.9967

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0898        | 1.0   | 327  | 0.0707          | 0.9757   |
| 0.0221        | 2.0   | 654  | 0.0278          | 0.9920   |
| 0.06          | 3.0   | 981  | 0.0345          | 0.9913   |
| 0.0094        | 4.0   | 1309 | 0.0300          | 0.9947   |
| 0.0004        | 5.0   | 1636 | 0.0398          | 0.9942   |
| 0.0035        | 6.0   | 1963 | 0.0136          | 0.9975   |
| 0.0246        | 7.0   | 2290 | 0.0339          | 0.9940   |
| 0.0012        | 8.0   | 2618 | 0.0316          | 0.9958   |
| 0.0           | 9.0   | 2945 | 0.0302          | 0.9964   |
| 0.0           | 10.0  | 3272 | 0.0201          | 0.9973   |
| 0.0003        | 11.0  | 3599 | 0.0222          | 0.9955   |
| 0.0           | 12.0  | 3927 | 0.0218          | 0.9962   |
| 0.0001        | 13.0  | 4254 | 0.0293          | 0.9962   |
| 0.0002        | 14.0  | 4581 | 0.0272          | 0.9962   |
| 0.0           | 14.99 | 4905 | 0.0271          | 0.9967   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0