README.md

---
library_name: keras
license: mit
metrics:
- accuracy
- f1
- precision
tags:
- biology
pipeline_tag: image-classification
---

## Model description

This is Vision Transformer model trained for cancer classification. To make single model to predict any cancer, I trained this ViT model. following are the cancer types that model can predict:
 * Brain cancer
 * Breast Cancer (histopathology)
 * Lung & Colon Cancer (histopathology)
 * Cervical Caner
 * Kidney Cancer
 * Lymphoma
 * Oral

## Intended uses & limitations

More information needed

## Training and evaluation data

Confusion matrix and classification report attached below:
<details>
<summary>Confusion Matrix</summary>

![Model Image](./cm.png)

</details>

<details>
<summary>Classification Report</summary>

![Model Image](./vit_acc.PNG)

</details>

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:

| Hyperparameters | Value |
| :-- | :-- |
| name | Adam |
| learning_rate | 0.0001 |
| decay | 0.0 |
| beta_1 | 0.9 |
| beta_2 | 0.999 |
| epsilon | 1e-07 |
| amsgrad | False |
| training_precision | float32 |


 ## Model Plot

<details>
<summary>View Model Plot</summary>

![Model Image](./model.png)

</details>