CourseLarge Language Models: The Complete Course · Module 9: Fine-Tuning and Adaptation · part 66 of 103
Part 66 · Module 9: Fine-Tuning and Adaptation

Lab: The fine-tuning trial, from plan to decision

49 min read·13 Oct 2026
Module 9 · Lab · About 60 minutes · Needs: lessons 1 to 4 of this module, and the Module 1 lab (or the cells in Step 1)

What you are building

FINETUNE/ AFTER MODULE 9 eval_plan.json triage, frozen eval_plan_replies replies, frozen baselines.py bar: 9 or more build_data.py 48 clean rows train_lora.py 8 of 12: below prefs.py ties a template results/decision.md: two plans, two verdicts, ship nothing
The system's steps (blue) lead to two trials that miss their own bars (red), and a written decision (green) that ships nothing.

It is Friday 31 July 2026, the end of week 9. Each lesson answered part of Tomasz's question in its own notebook: a frozen plan and a bar (Lesson 1), a clean training file (Lesson 2), a LoRA run scored once (Lesson 3) and a verified reply adapter (Lesson 4). This lab puts the trial into the repository as finetune/ and ends with one written decision for Maya. The running example is T-1025, Ruth Pell's two charges of 144 USD, a test ticket that must never reach training. Twelve calls go to the hosted model, in Step 3; everything else runs SmolLM2-135M-Instruct on your CPU, with under ten minutes of training.

The rest of this course is yours to keep

This course is bought on its own, once, and stays readable afterwards, including the parts added to it later.