What does Fine-Tuning mean? Definition | AI Understanding

Definition

Continuing training on domain-specific data to adapt a pre-trained model to a specific task.

Related terms

Parameter-Efficient Fine-Tuning (PEFT)

Methods that adapt models by training a small subset of added parameters.

Instruction Tuning

Fine-tuning a model on instruction-response pairs to improve task following.

Foundation Model

A large pre-trained model that can be adapted to many downstream tasks.

Continual Learning

Training approaches that let a model keep learning from new data without forgetting prior knowledge.

Data Augmentation

Techniques that create modified training examples to improve model generalization.

Domain Adaptation

Methods that transfer a model trained in one domain to perform better in another domain.

Learn more in our free guides

Fine-Tuning Rejection Sampling Fine-Tuning QLoRA and 4-Bit Fine-Tuning Self-Refine Iterative Output Improvement

See also

Few-Shot Learning Feature Extraction Function Calling Feature Engineering GAN (Generative Adversarial Network)Feature Generalization False Positive

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