---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-isic217
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5909090909090909
---

<!-- 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-finetuned-isic217

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3724
- Accuracy: 0.5909

## 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: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.2679        | 0.9796  | 24   | 2.1550          | 0.0909   |
| 2.0504        | 2.0     | 49   | 2.0559          | 0.2727   |
| 1.8943        | 2.9796  | 73   | 2.0186          | 0.2273   |
| 1.5671        | 4.0     | 98   | 1.8154          | 0.2273   |
| 1.3425        | 4.9796  | 122  | 2.0475          | 0.2273   |
| 1.2758        | 6.0     | 147  | 2.1914          | 0.2273   |
| 0.9808        | 6.9796  | 171  | 2.0478          | 0.3636   |
| 0.7246        | 8.0     | 196  | 1.8840          | 0.4091   |
| 0.7323        | 8.9796  | 220  | 2.1831          | 0.4091   |
| 0.4881        | 10.0    | 245  | 2.2868          | 0.3636   |
| 0.4346        | 10.9796 | 269  | 2.2312          | 0.4545   |
| 0.5647        | 12.0    | 294  | 1.9897          | 0.4091   |
| 0.1464        | 12.9796 | 318  | 2.0579          | 0.4545   |
| 0.5575        | 14.0    | 343  | 2.1859          | 0.4545   |
| 0.3894        | 14.9796 | 367  | 2.7353          | 0.3636   |
| 0.4326        | 16.0    | 392  | 2.4455          | 0.3636   |
| 0.3715        | 16.9796 | 416  | 2.3104          | 0.5455   |
| 0.3966        | 18.0    | 441  | 2.4597          | 0.4545   |
| 0.1855        | 18.9796 | 465  | 2.3335          | 0.3636   |
| 0.1528        | 20.0    | 490  | 2.3630          | 0.4091   |
| 0.2036        | 20.9796 | 514  | 2.3520          | 0.4545   |
| 0.2026        | 22.0    | 539  | 2.7012          | 0.4091   |
| 0.2127        | 22.9796 | 563  | 2.3724          | 0.5909   |
| 0.2719        | 24.0    | 588  | 3.0376          | 0.3182   |
| 0.1292        | 24.9796 | 612  | 2.5684          | 0.5      |
| 0.2533        | 26.0    | 637  | 2.6974          | 0.4091   |
| 0.1947        | 26.9796 | 661  | 2.6957          | 0.4091   |
| 0.1805        | 28.0    | 686  | 2.8953          | 0.4091   |
| 0.1123        | 28.9796 | 710  | 2.8240          | 0.4091   |
| 0.2143        | 30.0    | 735  | 2.3880          | 0.4545   |
| 0.1845        | 30.9796 | 759  | 2.6072          | 0.3636   |
| 0.0921        | 32.0    | 784  | 2.7256          | 0.4545   |
| 0.0276        | 32.9796 | 808  | 2.4074          | 0.4091   |
| 0.0876        | 34.0    | 833  | 2.6043          | 0.4545   |
| 0.0253        | 34.9796 | 857  | 2.7620          | 0.4545   |
| 0.1904        | 36.0    | 882  | 2.6911          | 0.4091   |
| 0.072         | 36.9796 | 906  | 2.6528          | 0.4545   |
| 0.169         | 38.0    | 931  | 2.6454          | 0.4545   |
| 0.0978        | 38.9796 | 955  | 2.6269          | 0.5      |
| 0.069         | 40.0    | 980  | 2.4154          | 0.4545   |
| 0.0159        | 40.9796 | 1004 | 2.7026          | 0.4545   |
| 0.2046        | 42.0    | 1029 | 2.5213          | 0.4545   |
| 0.0329        | 42.9796 | 1053 | 2.6399          | 0.5      |
| 0.0166        | 44.0    | 1078 | 2.7787          | 0.4545   |
| 0.0812        | 44.9796 | 1102 | 2.8176          | 0.4545   |
| 0.0197        | 46.0    | 1127 | 2.8049          | 0.4545   |
| 0.0989        | 46.9796 | 1151 | 2.7479          | 0.4545   |
| 0.054         | 48.0    | 1176 | 2.7614          | 0.4545   |
| 0.1095        | 48.9796 | 1200 | 2.7604          | 0.5      |


### Framework versions

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