---
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-3

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0112
- Accuracy: 0.9951

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1885        | 1.0   | 114  | 0.8718          | 0.6593   |
| 0.7037        | 2.0   | 228  | 0.4208          | 0.8637   |
| 0.5085        | 2.99  | 342  | 0.3446          | 0.8744   |
| 0.2874        | 4.0   | 457  | 0.2027          | 0.9327   |
| 0.355         | 5.0   | 571  | 0.1666          | 0.9401   |
| 0.2493        | 6.0   | 685  | 0.0969          | 0.9655   |
| 0.1909        | 6.99  | 799  | 0.0558          | 0.9836   |
| 0.1821        | 8.0   | 914  | 0.0412          | 0.9901   |
| 0.1853        | 9.0   | 1028 | 0.0239          | 0.9943   |
| 0.0666        | 9.98  | 1140 | 0.0112          | 0.9951   |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3