finetuning-is-specific-form-of-transfer-learning

IN premise — summaries/2026/08/24/wiki-Fine-tuning_deep_learning.md

Created 2026-08-24T17:11:09+00:00

Fine-tuning is defined as additional training on a pre-trained model's parameters to repurpose it for a downstream task, making it a specific form of transfer learning rather than a separate paradigm.

Summary

Fine-tuning is just transfer learning with a narrower scope: you take a model that already learned general patterns and do a bit more training to steer it toward a specific new task. Categorizing it this way matters because it means any argument or constraint that applies to transfer learning automatically covers fine-tuning too, so the system doesn't need to handle it as a separate case.