---
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12-192-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Psoriasis-500-100aug-224-swinv2-large
  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: 0.8305676855895197
---

<!-- 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-large

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-large-patch4-window12-192-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9383
- Accuracy: 0.8306

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8251        | 0.9840 | 46   | 0.8572          | 0.7118   |
| 0.3662        | 1.9893 | 93   | 0.8063          | 0.7389   |
| 0.1443        | 2.9947 | 140  | 0.8198          | 0.7755   |
| 0.0974        | 4.0    | 187  | 0.8232          | 0.8105   |
| 0.0464        | 4.9840 | 233  | 0.9549          | 0.7904   |
| 0.0234        | 5.9893 | 280  | 0.9775          | 0.7956   |
| 0.0125        | 6.9947 | 327  | 0.9146          | 0.8192   |
| 0.0066        | 8.0    | 374  | 0.9364          | 0.8279   |
| 0.0025        | 8.9840 | 420  | 0.9412          | 0.8288   |
| 0.0006        | 9.8396 | 460  | 0.9383          | 0.8306   |


### Framework versions

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