---
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-500-100-224-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: 0.8262008733624454
---

<!-- 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-500-100-224-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: 1.2393
- Accuracy: 0.8262

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4281        | 0.9973 | 92   | 0.7147          | 0.7747   |
| 0.2234        | 1.9946 | 184  | 0.8100          | 0.7930   |
| 0.1221        | 2.9919 | 276  | 0.9876          | 0.7843   |
| 0.0639        | 4.0    | 369  | 1.0562          | 0.7869   |
| 0.0124        | 4.9973 | 461  | 1.2498          | 0.7869   |
| 0.026         | 5.9946 | 553  | 1.2058          | 0.8052   |
| 0.0014        | 6.9919 | 645  | 1.3110          | 0.8061   |
| 0.0007        | 8.0    | 738  | 1.2566          | 0.8210   |
| 0.0058        | 8.9973 | 830  | 1.2338          | 0.8218   |
| 0.0056        | 9.9729 | 920  | 1.2393          | 0.8262   |


### Framework versions

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