---
license: apache-2.0
base_model: ahmedesmail16/Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Train-Augmentation-Psoriasis-Project
  results: []
---

<!-- 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. -->

# Train-Augmentation-Psoriasis-Project

This model is a fine-tuned version of [ahmedesmail16/Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k](https://huggingface.co/ahmedesmail16/Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0793
- Accuracy: 0.8182

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4867        | 0.99  | 93   | 0.8388          | 0.7075   |
| 0.2164        | 2.0   | 187  | 0.8105          | 0.7470   |
| 0.1503        | 2.99  | 280  | 0.8719          | 0.7470   |
| 0.1074        | 4.0   | 374  | 0.8725          | 0.7708   |
| 0.0649        | 4.99  | 467  | 0.8323          | 0.7984   |
| 0.0259        | 6.0   | 561  | 1.2222          | 0.7945   |
| 0.0162        | 6.99  | 654  | 1.0419          | 0.8024   |
| 0.0135        | 8.0   | 748  | 0.9799          | 0.8300   |
| 0.0031        | 8.99  | 841  | 1.1125          | 0.8063   |
| 0.0041        | 9.95  | 930  | 1.0793          | 0.8182   |

### Test results

|   class              |precision  |    recall | f1-score |  support|
|:--------------------:|:---------:|:---------:|:--------:|:-------:|
|      Erythrodermic   |    0.75   |   0.86   |   0.80   |      7|
|            Guttate   |    0.91   |   0.87   |   0.89   |     23|
|            Inverse   |    1.00   |   0.82   |   0.90   |     17|
|               Nail   |    0.95   |   0.95   |   0.95   |     20|
|             Normal   |    0.95   |   0.80   |   0.87   |     25|
|         Not Define   |    1.00   |   1.00   |   1.00   |     29|
|         Palm Soles   |    0.83   |   0.90   |  0.86    |    21|
|             Plaque   |    0.90   |   0.76   |   0.83   |     25|
|Psoriatic Arthritis   |    0.73   |   1.00   |   0.84   |      8|
|           Pustular   |    0.88   |   0.82   |   0.85   |     17|
|              Scalp   |    0.87   |   0.83   |   0.85   |    24|
|           UPNormal   |    0.82   |   0.94   |   0.87   |     52|
|                      |           |          |          |         |
|           accuracy   |           |          |   0.88   |    268|
|          macro avg   |    0.88   |  0.88    |  0.88    |  268|
|       weighted avg   |    0.89    |  0.88    | 0.88     |  268|

### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2