The answer
Yes. Narrow or inconsistent training can reduce other capabilities or introduce unwanted patterns. Evaluation should check both the target task and important existing behaviors.
What is supervised fine-tuning?
Can fine-tuning make a model worse on some tasks?
More FAQs in What is supervised fine-tuning?
No. Pre-training commonly builds broad capabilities from a large data mixture. SFT usually adapts an existing model using examples that demonstrate particular outputs or behaviors.
Often a retrieval system or database is easier to update and verify. Fine-tuning is more naturally suited to recurring response patterns and task behavior.
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