
# vit-base-patch16-224-in21k_lung_and_colon_cancer

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k).

It achieves the following results on the evaluation set:
- Loss: 0.0016
- Accuracy: 0.9994
- F1
  - Weighted: 0.9994
  - Micro: 0.9994
  - Macro: 0.9994
- Recall
  - Weighted: 0.9994
  - Micro: 0.9994
  - Macro: 0.9994
- Precision
  - Weighted: 0.9994
  - Micro: 0.9994
  - Macro: 0.9994

## Model description

This is a multiclass image classification model of lung and colon cancers.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Lung%20%26%20Colon%20Cancer/Lung_and_colon_cancer_ViT.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/andrewmvd/lung-and-colon-cancer-histopathological-images

_Sample Images From Dataset:_
![Sample Images](https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/raw/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Lung%20%26%20Colon%20Cancer/Images/Sample%20Images.png)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.0574        | 1.0   | 1250 | 0.0410          | 0.9864   | 0.9864      | 0.9864   | 0.9865   | 0.9864          | 0.9864       | 0.9864       | 0.9872             | 0.9864          | 0.9875          |
| 0.0031        | 2.0   | 2500 | 0.0105          | 0.9972   | 0.9972      | 0.9972   | 0.9972   | 0.9972          | 0.9972       | 0.9973       | 0.9972             | 0.9972          | 0.9972          |
| 0.0007        | 3.0   | 3750 | 0.0016          | 0.9994   | 0.9994      | 0.9994   | 0.9994   | 0.9994          | 0.9994       | 0.9994       | 0.9994             | 0.9994          | 0.9994          |

### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1
- Datasets 2.5.2
- Tokenizers 0.12.1
colon_aca colon_n lung_aca lung_n lung_scc