Why Hyperparameter Tuning Beats LoRA Choices in LLM Fine‑Tuning

Hyperparameter tuning beats LoRA configuration changes on most fine-tuning runs. When a run won't converge or underperforms, the culprit is almost always learning rate, batch size, scheduler, warmup, or data quality. It's rarely the rank you picked. Think of LoRA as a structural constraint. It…