---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Psoriasis-500-100aug-224-swinv2-base-patch4-window12-192-22k
  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: 0.8200873362445414
---

<!-- 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. -->

# Psoriasis-500-100aug-224-swinv2-base-patch4-window12-192-22k

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1589
- Accuracy: 0.8201

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5248        | 0.9973 | 92   | 0.7503          | 0.7694   |
| 0.2461        | 1.9946 | 184  | 0.8202          | 0.7764   |
| 0.1164        | 2.9919 | 276  | 0.8260          | 0.8052   |
| 0.0656        | 4.0    | 369  | 1.0366          | 0.7860   |
| 0.0525        | 4.9973 | 461  | 1.0025          | 0.8148   |
| 0.0223        | 5.9946 | 553  | 1.1363          | 0.7965   |
| 0.0022        | 6.9919 | 645  | 1.1911          | 0.8061   |
| 0.009         | 8.0    | 738  | 1.2139          | 0.7965   |
| 0.0073        | 8.9973 | 830  | 1.2066          | 0.8166   |
| 0.0014        | 9.9729 | 920  | 1.1589          | 0.8201   |

# Classification Report

| Class               | Precision (%) | Recall (%) | F1-Score (%) | Support |
|---------------------|---------------|------------|--------------|---------|
| Abnormal            | 68            | 67         | 67           | 108     |
| Erythrodermic       | 99            | 75         | 85           | 100     |
| Guttate             | 94            | 84         | 89           | 114     |
| Inverse             | 88            | 93         | 90           | 108     |
| Nail                | 88            | 86         | 87           | 99      |
| Normal              | 84            | 87         | 85           | 82      |
| Not Define          | 98            | 99         | 98           | 92      |
| Palm Soles          | 80            | 80         | 80           | 102     |
| Plaque              | 73            | 92         | 81           | 84      |
| Psoriatic Arthritis | 88            | 75         | 81           | 104     |
| Pustular            | 76            | 86         | 80           | 112     |
| Scalp               | 86            | 94         | 90           | 80      |
| **Accuracy**        |               |            | **84**       | 1185    |
| **Macro Avg**       | **85**        | **85**     | **84**       | 1185    |
| **Weighted Avg**    | **85**        | **84**     | **84**       | 1185    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1