---
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: 0.805
---

<!-- 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: 0.6650
- Accuracy: 0.805

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.2566        | 0.9825 | 14   | 0.7227          | 0.74     |
| 0.2729        | 1.9649 | 28   | 0.3916          | 0.815    |
| 0.1553        | 2.9474 | 42   | 0.8409          | 0.75     |
| 0.1371        | 4.0    | 57   | 0.3706          | 0.885    |
| 0.1588        | 4.9825 | 71   | 0.8758          | 0.765    |
| 0.1093        | 5.9649 | 85   | 0.6063          | 0.82     |
| 0.102         | 6.9474 | 99   | 0.5308          | 0.84     |
| 0.0713        | 8.0    | 114  | 0.3536          | 0.88     |
| 0.1045        | 8.9825 | 128  | 0.3858          | 0.875    |
| 0.0661        | 9.8246 | 140  | 0.6650          | 0.805    |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1