---
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-S
  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-S

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: 0.0069
- Accuracy: 0.9975

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2378        | 1.0   | 114  | 0.9976          | 0.5936   |
| 0.7272        | 2.0   | 228  | 0.4749          | 0.8309   |
| 0.4335        | 2.99  | 342  | 0.2488          | 0.9195   |
| 0.3298        | 4.0   | 457  | 0.1700          | 0.9310   |
| 0.177         | 5.0   | 571  | 0.2116          | 0.9261   |
| 0.2299        | 6.0   | 685  | 0.0933          | 0.9754   |
| 0.2586        | 6.99  | 799  | 0.0316          | 0.9869   |
| 0.1053        | 8.0   | 914  | 0.0256          | 0.9910   |
| 0.2159        | 9.0   | 1028 | 0.0147          | 0.9959   |
| 0.0607        | 9.98  | 1140 | 0.0069          | 0.9975   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3