Building a Vision Transformer Model from Scratch with PyTorch
1,022Learn 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
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⭐ ️ 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
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