|
|
--- |
|
|
datasets: |
|
|
- Falah/Alzheimer_MRI |
|
|
base_model: |
|
|
- google/vit-base-patch16-224-in21k |
|
|
pipeline_tag: image-classification |
|
|
tags: |
|
|
- dementia |
|
|
license: mit |
|
|
language: |
|
|
- en |
|
|
library_name: transformers |
|
|
--- |
|
|
This project was intended to test the limits of the ViT on a tough dementia dataset. The data used can be found on HuggingFace at: https://huggingface.co/datasets/Falah/Alzheimer_MRI. The project follows closely the following tutorials: |
|
|
|
|
|
https://www.youtube.com/watch?v=r88L_yLJ4CE&ab_channel=code_your_own_AI |
|
|
https://www.youtube.com/watch?v=qU7wO02urYU&ab_channel=JamesBriggs |
|
|
I modify the code presented in the video and tune all parameters to optimize performance using mostly the same libraries and tools. This is a practice project for myself as I return to coding/designing ML models after dedicating time to AI/ML theory (model architectures, transfer learning) |
|
|
|
|
|
|
|
|
 |
|
|
|
|
|
 |
|
|
|
|
|
 |
|
|
|
|
|
 |
