---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-skin-cancer
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8772455089820359
---

<!-- 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. -->

# swin-tiny-patch4-window7-224-finetuned-skin-cancer

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3211
- Accuracy: 0.8772

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8717        | 0.9929 | 35   | 0.8160          | 0.6916   |
| 0.6289        | 1.9858 | 70   | 0.5764          | 0.8034   |
| 0.4878        | 2.9787 | 105  | 0.4994          | 0.8174   |
| 0.4392        | 4.0    | 141  | 0.4301          | 0.8493   |
| 0.3867        | 4.9929 | 176  | 0.4034          | 0.8573   |
| 0.3653        | 5.9858 | 211  | 0.3476          | 0.8693   |
| 0.3359        | 6.9787 | 246  | 0.3681          | 0.8643   |
| 0.2865        | 8.0    | 282  | 0.3578          | 0.8653   |
| 0.3041        | 8.9929 | 317  | 0.3245          | 0.8792   |
| 0.2869        | 9.9291 | 350  | 0.3211          | 0.8772   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0