---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k
  results: []
pipeline_tag: image-classification
---

<!-- 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-Project-Aug-M2-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0088
- Accuracy: 1.0

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7078        | 0.99  | 36   | 0.1447          | 0.9375   |
| 0.1858        | 1.99  | 72   | 0.0584          | 0.9792   |
| 0.0891        | 2.98  | 108  | 0.0082          | 1.0      |
| 0.0619        | 4.0   | 145  | 0.0215          | 1.0      |
| 0.0252        | 4.99  | 181  | 0.0120          | 1.0      |
| 0.018         | 5.99  | 217  | 0.0139          | 1.0      |
| 0.0112        | 6.95  | 252  | 0.0088          | 1.0      |

### Training results
                     precision    recall  f1-score   support

       Erythromelal       1.00      1.00      1.00         5
            Guttate       1.00      1.00      1.00         7
            Inverse       1.00      1.00      1.00         4
               Nail       1.00      1.00      1.00        10
             Normal       1.00      1.00      1.00        11
             Plaque       1.00      1.00      1.00        10
Psoriatic Arthritis       1.00      1.00      1.00         6

           Pustular       1.00      1.00      1.00         6
           accuracy                           1.00        59
          macro avg       1.00      1.00      1.00        59
       weighted avg       1.00      1.00      1.00        59

### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2