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# swin-tiny-patch4-window7-224-finetuned-leukemia-08-2024

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: 0.1282
- Accuracy: 0.9527

## Model description

This model was developed to aid in the diagnosis of Leukemia. Leukemia is the cancer that most affects children between 4 and 10 years of age.

![Logo do Projeto](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRGFeEW1ZNiBniuKsdZcsGHcHnacRjlvsDt-kd2Mb8U3PYjUg9OoKzWVz76s-m84SCXtq8&usqp=CAU)



## Intended uses & limitations

In this version, the images used for testing correspond to 10% of the images in the image dataset. Consider that the images in the dataset are originally:

- All: 7,272
- Hem: 3,389

Applying Data augmentation, we arrive at: 20,000 images for each segment. Totaling 36,000 images for training and 4,000 for testing.

## Important Note: 
The images used in the test may be similar to those used in training, which may cause overfit..

## Training and evaluation data

DataSet: Dataset ISBI-2019 (ISIC 2019 Challenge) 

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.328         | 0.9991 | 281  | 0.7951          | 0.6827   |
| 0.2832        | 1.9982 | 562  | 0.4021          | 0.8433   |
| 0.1886        | 2.9973 | 843  | 0.3305          | 0.8718   |
| 0.1789        | 4.0    | 1125 | 0.2242          | 0.9123   |
| 0.1269        | 4.9991 | 1406 | 0.1856          | 0.9315   |
| 0.0904        | 5.9982 | 1687 | 0.1282          | 0.9527   |
| 0.0754        | 6.9973 | 1968 | 0.1824          | 0.9377   |
| 0.0549        | 8.0    | 2250 | 0.2908          | 0.9105   |
| 0.0616        | 8.9991 | 2531 | 0.2961          | 0.9215   |
| 0.0502        | 9.9911 | 2810 | 0.2343          | 0.9345   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1

## Author
Douglas Braga https://www.linkedin.com/in/douglas-braga-891a701/
all hem