TL;DR: I was three days into a 72-hour pre-training run on a molecular property prediction task when I checked the loss curves and realized something was deeply wrong — not with my hyperparameters, but with my entire approach. My Transformer was burning A100 time learning that atoms bo 📖 Reading time: ~32 min What's in this article The Problem: Pre-Training Is Eating Your GPU Budget What Geometric Deep Learning Actually Gives You (Practically Speaking) Setting Up PyTorch Geometric Without Breaking Your Environment Building Your First Graph-Structured Model That Skips the Pre-Training Grind Replacing the Pre-Training Phase: What the Workflow Looks Like in Practice The 3 Things That Surprised Me After Switching When GDL Doesn't Help and You Still Need Pre-Training Quick Reference: PyG vs.…