---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-vit-finetuned-melanoma
  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. -->

# swin-tiny-patch4-window7-224-vit-finetuned-melanoma

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2687
- Accuracy: 0.9017

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5392        | 1.0   | 112  | 0.5796          | 0.7884   |
| 0.4716        | 2.0   | 224  | 0.4380          | 0.8304   |
| 0.3932        | 3.0   | 336  | 0.3749          | 0.8534   |
| 0.3446        | 4.0   | 448  | 0.3851          | 0.8423   |
| 0.3401        | 5.0   | 560  | 0.3141          | 0.8708   |
| 0.2842        | 6.0   | 672  | 0.3309          | 0.8685   |
| 0.3126        | 7.0   | 784  | 0.3493          | 0.8629   |
| 0.2748        | 8.0   | 896  | 0.3391          | 0.8772   |
| 0.2455        | 9.0   | 1008 | 0.3053          | 0.8843   |
| 0.2361        | 10.0  | 1120 | 0.2749          | 0.8954   |
| 0.2218        | 11.0  | 1232 | 0.2842          | 0.8994   |
| 0.2071        | 12.0  | 1344 | 0.2507          | 0.9089   |
| 0.2228        | 13.0  | 1456 | 0.2614          | 0.8994   |
| 0.2018        | 14.0  | 1568 | 0.2664          | 0.9105   |
| 0.1774        | 15.0  | 1680 | 0.2687          | 0.9017   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3