Did My LoRA Learn Tenacious Style—or Just Memorize Augmented Patterns?

In Week 11 Tenacious-Bench, we trained a LoRA adapter on Tenacious-style B2B sales emails using Supervised Fine-Tuning (SFT). We got a real performance lift: Delta A = +0.263 (p But that result exposed a harder question : Did the adapter learn how Tenacious writes, or just what repeated Tenacious-like samples looked like? This post answers that at the mechanism level: cross-entropy token-by-token, LoRA gradient flow, and why low-diversity augmentation can make convergence look better than genera