You’re absolutely right, and I really appreciate the professional perspective.

To evaluate this properly, I’d need a more rigorous setup: a carefully designed dataset split, held-out templates, deterministic seeds, and repeated rehearsal experiments.

Increasing the model size might become necessary if the current tiny architecture cannot represent unseen structures reliably, but I would test the existing 2,160-parameter model first.

That said, since I designed this project as a transparent, bare-metal educational tutorial, I want to keep the focus on the underlying math and avoid complicating it for now. However, your points are incredibly solid! Thanks for diving so deep.