{
 "id": "https://redfinchadvisory.com/lexicon/fine-tuning",
 "slug": "fine-tuning",
 "prefLabel": "Fine-tuning",
 "altLabel": [],
 "hiddenLabel": [],
 "definition": "A further round of training that adapts a pretrained model to specific tasks or a particular domain.",
 "scopeNote": "NIST (AI 100-2e2025, Adversarial Machine Learning glossary) says: “The process of adapting a pre-trained model to perform specific tasks or specialize in a particular domain. This phase follows the initial pre-training phase and involves further training the model on task-specific data. This is often a supervised learning task.”\n\nFine-tuning is one kind of post-training. Post-training usually means what the model maker does; fine-tuning usually means further training that anyone, often a customer, does for a task or domain. Fine-tuning changes how a model behaves and writes. It is a poor way to add facts that change often; RAG handles that better.",
 "tier": "explain",
 "group": "How models work",
 "broader": [
  "https://redfinchadvisory.com/lexicon/training"
 ],
 "narrower": [],
 "related": [
  {
   "id": "https://redfinchadvisory.com/lexicon/rag",
   "type": "pair"
  }
 ],
 "links": [
  {
   "id": "https://redfinchadvisory.com/lexicon/post-training",
   "label": "is one kind of",
   "direction": "out"
  },
  {
   "id": "https://redfinchadvisory.com/lexicon/fine-tuning-on-our-data",
   "label": "is the method behind",
   "direction": "out"
  }
 ],
 "modified": "2026-10-21",
 "markdown": "https://redfinchadvisory.com/lexicon/fine-tuning.md",
 "inScheme": {
  "id": "https://redfinchadvisory.com/lexicon",
  "version": "1.0",
  "currentAsOf": "2026-10-21"
 }
}