Glossary Model Training 1 min read

Fine-Tuning

Also known as: Model Fine-Tuning, Transfer Learning, Domain Adaptation

The process of further training a pre-trained AI model on a specialized dataset to adapt its behavior, knowledge, or output style for a specific domain or task.

Model adaptation, transfer learning, domain adaptation, LoRA, QLoRA, PEFT, parameter-efficient fine-tuning, instruction tuning, task-specific training, model customization, supervised fine-tuning, SFT, adapter layers

Sources & References

1
Fine-tuning - OpenAI Documentation

OpenAI

Documentation
2
LoRA: Low-Rank Adaptation of Large Language Models

Microsoft Research

Research
3
Training language models to follow instructions with human feedback (RLHF)

OpenAI

Research

Related Terms

Large Language Model

A type of AI model trained on vast amounts of text data that can understand, generate, and manipulate human language, typically based on the transformer architecture with billions of parameters.

Machine Learning

A subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed, using algorithms that identify patterns in data.

Reinforcement Learning from Human Feedback

A training technique that uses human evaluations of AI outputs to train a reward model, which then guides the AI system to produce outputs more aligned with human preferences.

Training Data

The curated dataset used to train machine learning models, whose quality, diversity, size, and representativeness directly determine the model's capabilities and limitations.
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