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My fine-tuned model gets the facts right and still sounds wrong for our brand, and I don't know how to train that away.
What you'll have at the end
A file of chosen-versus-rejected response pairs, ready for a preference fine-tuning run
You need
A fine-tuned model already answering real questions correctly, whose actual replies you can pull up right now, and a short written description of the tone you actually want it to use instead.
Not covered
Running the DPO training job itself and choosing its epoch count or beta value, since this recipe stops at a validated dataset file ready to hand to that job.
Leans on
Pick starting values for LoRA rank, alpha, and learning rate
for the rank, alpha, and learning rate the actual DPO training run needs, once this file is ready
Deduplicate a fine-tuning dataset before you train
if the real off-tone replies you pulled came from the same handful of tickets copied many times
Checked 15 Aug 2026
Part of the LLM Fine-tuning cookbook