Building a Vision Transformer Model from Scratch with PyTorch

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Learn to build a Vision Transformer (ViT) from scratch using PyTorch! This hands-on course guides you through each component, from patch embedding to the Transformer Encoder. Train your custom ViT model on CIFAR-10 and gain practical experience in image classification. Transition from CNNs to transformers in this efficient, end-to-end tutorial.

Code: https://github.com/MOHAMMEDFAHD/pytorch-collections/blob/main/Building_Vision_Transformer_on_CIFAR_10_From_Scratch_Pytorch.ipynb

Course developed by @programmingoceanacademy

Support for this channel comes from our friends at Scrimba – the coding platform that’s reinvented interactive learning: https://scrimba.com/freecodecamp

Contents
(0:00:00) Intro
(0:28:23) Theoretical Explanation of Vision Transformers
(0:47:40) Environment Setup and Library Imports
(0:55:14) Configurations and Hyperparameter Setup
(0:58:28) Image Transformation Operations
(1:00:28) Downloading the CIFAR-10 Dataset
(1:04:22) Creating DataLoaders
(1:11:32) Building the Vision Transformer (ViT) Model
(1:43:41) Defining Loss Function and Optimizer
(1:45:37) Training Loop and Model Training
(2:03:18) Visualizing Accuracy (Training vs Testing)
(2:06:08) Making and Visualizing Predictions
(2:18:48) Fine-Tuning with Data Augmentation
(2:25:08) Training the Fine-Tuned Model
(2:27:08) Visualizing Fine-Tuned Accuracy
(2:28:38) Predictions After Fine-Tuning

Thanks to our Champion and Sponsor supporters:
Drake Milly
Ulises Moralez
Goddard Tan
David MG
Matthew Springman
Claudio
Oscar R.
jedi-or-sith
Nattira Maneerat
Justin Hual