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Fine-tuning

Model Fine-tuning

Definition

Fine-tuning is the process of continuing to train a pre-trained model on domain-specific or task-specific data to improve performance in that area. Full fine-tuning updates all model weights, while parameter-efficient methods (LoRA, adapters) update only a small subset.

Fine-tuning adapts general-purpose models to tasks like code generation, customer support, or medical Q&A.

Related Terms

LoRA
Low-Rank Adaptation
QLoRA
Quantized Low-Rank Adaptation
PEFT
Parameter-Efficient Fine-Tuning
Instruction tuning
Instruction Tuning
Adapter
Adapter Layer
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