Definition
Plain language
Taking a model that already knows a lot and giving it more lessons so it gets better at one specific task.
As stated in the literature
Continuing the training of a pretrained model on a smaller task-specific dataset, updating its weights to adapt the general model to a particular use case.
Also called: Fine-tuning, fine-tune, fine-tuned, finetuning, finetune, finetuned, finetunes
Why it matters: It's the standard way to adapt a generic foundation model to a specific domain or task without training from scratch.
For example, you might take a general language model and fine-tune it on a few thousand customer-support transcripts so it adopts your company's tone and product knowledge.
Heard on the show
“… effect — to make sure you're seeing alignment-driven dissociation rather than just noise from any fine-tuning at all. …”Episode 004 — The Sycophancy Circuit That Survives Alignment Training