---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-base-patch4-window8-256-isic217
  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. -->

# swinv2-base-patch4-window8-256-isic217

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1588
- Accuracy: 0.65

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.1681        | 0.9888 | 22   | 2.0018          | 0.25     |
| 1.9254        | 1.9775 | 44   | 1.7653          | 0.35     |
| 1.6706        | 2.9663 | 66   | 1.6649          | 0.6      |
| 1.2834        | 4.0    | 89   | 1.5579          | 0.5      |
| 1.2039        | 4.9888 | 111  | 1.4087          | 0.55     |
| 0.9395        | 5.9775 | 133  | 1.3115          | 0.5      |
| 0.7532        | 6.9663 | 155  | 1.3599          | 0.6      |
| 0.6573        | 8.0    | 178  | 1.1588          | 0.65     |
| 0.6663        | 8.9888 | 200  | 1.2074          | 0.6      |
| 0.4686        | 9.8876 | 220  | 1.2285          | 0.6      |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1