Training & Fine-tuningaka Finetuning

Fine-Tuning

Fine-tuning continues training a pretrained model on a narrower dataset or objective to change its behavior for a target use.

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Updates may affect all model weights or only a small added subset. The data, learning rate, and stopping point are chosen to gain specialization without unnecessarily erasing useful pretrained behavior.

Related terms

Contrastive Learning Pretraining Supervised Fine-Tuning Reinforcement Learning from Human Feedback Overfitting Transfer Learning

Where Fine-Tuning comes up

In-Browser LLM Fine-Tuning: Why Training on WebGPU Is a Bigger Deal Than Inference
Mind Lab Macaron-V1: Continual Learning via LoRA, Not Fine-Tuning
Prompt Engineering vs Fine-Tuning vs RAG: When to Use Which
Grounding vs RAG vs fine-tuning vs prompt engineering: which fix, when (a 2026 decision guide)