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AI & Machine Learning · Intermediate

Full Fine-Tuning

Updating all of a model's weights during fine-tuning.

Definition

Full fine-tuning can give the best task adaptation but needs memory for weights, gradients and optimizer states, often several times the model size, and produces a full model copy per task. It also risks catastrophic forgetting.

Exam tip

Prefer PEFT methods such as LoRA when compute or memory is constrained.

Related terms