Pick starting values for LoRA rank, alpha, and learning rate

I copied rank 16, alpha 32 from a tutorial without knowing if those numbers even fit my task.

Beginner to intermediateRead 6 minDoing: about twenty minutes6 steps

What you'll have at the end

A written starting config, rank, alpha, and learning rate, with a one-line reason for each

Before you start

You need

A formatted fine-tuning dataset and a base model already picked, ready to hand to a LoRA training script.

Not covered

Running the fine-tuning job itself, or fixing a crash once training is already underway.

Leans on

6 steps

Run a complete LoRA fine-tune on a free GPU

for the actual training run once you've got numbers to hand it

Catch an overfit fine-tune before you ship it

for a fuller check than the one tripwire number here, once training has finished

Should you fine-tune, or is RAG enough?

if you haven't settled whether the task needs fine-tuning at all yet

Checked 15 Aug 2026