---
license: apache-2.0
base_model: microsoft/swin-large-patch4-window7-224
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: 0.8227074235807861
---

<!-- 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/swin-large-patch4-window7-224](https://huggingface.co/microsoft/swin-large-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7383
- Accuracy: 0.8227

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.4126        | 0.9840 | 46   | 0.9408          | 0.6882   |
| 0.3672        | 1.9893 | 93   | 0.6431          | 0.7703   |
| 0.133         | 2.9947 | 140  | 0.5938          | 0.7921   |
| 0.0624        | 4.0    | 187  | 0.6128          | 0.8035   |
| 0.0473        | 4.9840 | 233  | 0.6654          | 0.8114   |
| 0.0276        | 5.9893 | 280  | 0.7090          | 0.8166   |
| 0.0111        | 6.9947 | 327  | 0.7133          | 0.8140   |
| 0.0081        | 8.0    | 374  | 0.7639          | 0.8183   |
| 0.0039        | 8.9840 | 420  | 0.7387          | 0.8236   |
| 0.0065        | 9.8396 | 460  | 0.7383          | 0.8227   |


### Framework versions

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