---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-rawdata-finetuned-SkinDisease
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8818737270875764
---

<!-- 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-base-patch4-window7-224-rawdata-finetuned-SkinDisease

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3867
- Accuracy: 0.8819

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7301        | 0.98  | 34   | 2.0665          | 0.3910   |
| 1.3672        | 1.99  | 69   | 1.0139          | 0.6660   |
| 0.7673        | 2.99  | 104  | 0.7393          | 0.7760   |
| 0.605         | 4.0   | 139  | 0.6480          | 0.7841   |
| 0.5142        | 4.98  | 173  | 0.5229          | 0.8248   |
| 0.4081        | 5.99  | 208  | 0.4561          | 0.8615   |
| 0.3966        | 6.99  | 243  | 0.4206          | 0.8656   |
| 0.3247        | 8.0   | 278  | 0.4001          | 0.8717   |
| 0.3235        | 8.98  | 312  | 0.3867          | 0.8819   |
| 0.2788        | 9.78  | 340  | 0.3801          | 0.8737   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3