---
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: 0.0007
- Accuracy: 1.0

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3289        | 1.0   | 114  | 1.0633          | 0.6248   |
| 0.7956        | 2.0   | 228  | 0.5050          | 0.8103   |
| 0.5253        | 2.99  | 342  | 0.3013          | 0.9031   |
| 0.2958        | 4.0   | 457  | 0.1534          | 0.9524   |
| 0.276         | 5.0   | 571  | 0.1825          | 0.9335   |
| 0.2556        | 6.0   | 685  | 0.0723          | 0.9729   |
| 0.3624        | 6.99  | 799  | 0.1268          | 0.9483   |
| 0.1986        | 8.0   | 914  | 0.0522          | 0.9778   |
| 0.1554        | 9.0   | 1028 | 0.0205          | 0.9926   |
| 0.1636        | 10.0  | 1142 | 0.0197          | 0.9951   |
| 0.1147        | 10.99 | 1256 | 0.0517          | 0.9836   |
| 0.1663        | 12.0  | 1371 | 0.0056          | 0.9959   |
| 0.094         | 13.0  | 1485 | 0.0030          | 0.9992   |
| 0.1308        | 14.0  | 1599 | 0.0011          | 0.9992   |
| 0.1557        | 14.97 | 1710 | 0.0007          | 1.0      |


### Framework versions

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