---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-main-gpu-20e-final
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9913265306122448
---

<!-- 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-main-gpu-20e-final

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: 0.0254
- Accuracy: 0.9913

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5767        | 1.0   | 551   | 0.5565          | 0.7463   |
| 0.3985        | 2.0   | 1102  | 0.3165          | 0.8711   |
| 0.2988        | 3.0   | 1653  | 0.1835          | 0.9293   |
| 0.2449        | 4.0   | 2204  | 0.1150          | 0.9572   |
| 0.2037        | 5.0   | 2755  | 0.0993          | 0.9632   |
| 0.1646        | 6.0   | 3306  | 0.0750          | 0.9717   |
| 0.1995        | 7.0   | 3857  | 0.0610          | 0.9776   |
| 0.1659        | 8.0   | 4408  | 0.0485          | 0.9815   |
| 0.1449        | 9.0   | 4959  | 0.0505          | 0.9821   |
| 0.1315        | 10.0  | 5510  | 0.0444          | 0.9843   |
| 0.102         | 11.0  | 6061  | 0.0440          | 0.9838   |
| 0.1039        | 12.0  | 6612  | 0.0359          | 0.9870   |
| 0.0798        | 13.0  | 7163  | 0.0393          | 0.9869   |
| 0.1033        | 14.0  | 7714  | 0.0343          | 0.9890   |
| 0.078         | 15.0  | 8265  | 0.0298          | 0.9902   |
| 0.0765        | 16.0  | 8816  | 0.0299          | 0.9901   |
| 0.0769        | 17.0  | 9367  | 0.0275          | 0.9908   |
| 0.0751        | 18.0  | 9918  | 0.0271          | 0.9910   |
| 0.0822        | 19.0  | 10469 | 0.0251          | 0.9917   |
| 0.0756        | 20.0  | 11020 | 0.0254          | 0.9913   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2