08 - Vision Transformers: Architecture and Training

Complete guide to Vision Transformers: Architecture and Training: architecture, practical implementation and best practices for developers and technical teams.

What you'll learn

• ViT architecture: patch embedding, positional encoding, visual self-attention
• Complete from-scratch implementation with PyTorch
• Differences between ViT-B/16, ViT-L/32, DeiT, Swin Transformer
• Fine-tuning a pre-trained ViT on a custom dataset
• Data augmentation techniques for ViT (MixUp, CutMix, RandAugment)

This article is part of the Deep Learning Avanzato series on federicocalo.dev.

Read the full article

The complete article (18 min read) with code examples, diagrams, and practical exercises is available here:

➡️ 08 - Vision Transformers: Architecture and Training

https://federicocalo.dev/en/blog/vision-transformers-architecture-training

By Federico Calò — Software Developer & Technical Writer