---
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: 0.4590
- Accuracy: 0.8384

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2892        | 1.0   | 10   | 0.8297          | 0.7377   |
| 0.6913        | 2.0   | 20   | 0.6707          | 0.7670   |
| 0.5364        | 3.0   | 30   | 0.5587          | 0.7956   |
| 0.4568        | 4.0   | 40   | 0.5270          | 0.8122   |
| 0.4103        | 5.0   | 50   | 0.5141          | 0.8106   |
| 0.3411        | 6.0   | 60   | 0.4820          | 0.8273   |
| 0.2993        | 7.0   | 70   | 0.4801          | 0.8304   |
| 0.2608        | 8.0   | 80   | 0.4643          | 0.8384   |
| 0.2291        | 9.0   | 90   | 0.4703          | 0.8384   |
| 0.224         | 10.0  | 100  | 0.4590          | 0.8384   |


### Framework versions

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