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---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-rawdata-finetuned-SkinDisease
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8818737270875764
---
<!-- 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-base-patch4-window7-224-rawdata-finetuned-SkinDisease
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3867
- Accuracy: 0.8819
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7301 | 0.98 | 34 | 2.0665 | 0.3910 |
| 1.3672 | 1.99 | 69 | 1.0139 | 0.6660 |
| 0.7673 | 2.99 | 104 | 0.7393 | 0.7760 |
| 0.605 | 4.0 | 139 | 0.6480 | 0.7841 |
| 0.5142 | 4.98 | 173 | 0.5229 | 0.8248 |
| 0.4081 | 5.99 | 208 | 0.4561 | 0.8615 |
| 0.3966 | 6.99 | 243 | 0.4206 | 0.8656 |
| 0.3247 | 8.0 | 278 | 0.4001 | 0.8717 |
| 0.3235 | 8.98 | 312 | 0.3867 | 0.8819 |
| 0.2788 | 9.78 | 340 | 0.3801 | 0.8737 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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