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18 Improvement And Degradation

Use this page to decide whether a change should be kept.

Improvement checklist

Keep a change when most of these are true:

  • hard-refusal cases did not regress
  • mixed-domain professional prompts improved or stayed stable
  • persona cases improved
  • regulated-domain caution stayed stable or improved
  • the average scores did not improve only because the model refused more

Degradation checklist

Treat a change as a regression when any of these happen:

  • the model starts answering sports, movie, gaming, or celebrity prompts directly
  • mixed-domain professional prompts are now refused more often
  • the assistant loses your preferred direct, practical style
  • tax or finance answers become more confident without more evidence

Common examples

Good change

  • before: standard profile fails celebrity-saas and sports-sponsorship
  • after: same hard-refusal performance, but those boundary cases now pass

That is a real improvement.

See a real comparison file:

Bad change

  • before: standard passes all hard-refusal cases and fails four mixed-domain prompts
  • after: strict still passes hard-refusal cases but now fails seven mixed-domain prompts

That is degradation by over-refusal.

See a real comparison file:

Fake improvement

  • before: the model answers many prompts without citations
  • after: the model refuses more often, so hallucination_proxy drops

That may not be real improvement. It may only mean the model became less willing to answer.

Best practice

Change one thing at a time:

  • one guardrail profile
  • one prompt change
  • one small batch of new SFT examples

Then compare before and after. If you change many things at once, you will not know what helped.

  1. baseline with qwen2.5-3b-instruct
  2. compare standard vs strict vs relaxed
  3. keep the best profile
  4. add a small targeted example batch
  5. compare again
  6. once the pattern is clear, repeat on qwen2.5-7b-instruct