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