A Better LLM Judge? The Rubric Made My Small Model Worse
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In Part 2 I built the laziest possible LLM judge — a tiny model ( Qwen2.5-1.5B ) and a one-line rubric — and it agreed with human votes only ~43% of the time, crammed every score into a 7–8 band, and tied a third of the comparisons humans had no trouble separating. Two things were wrong with that judge, and people usually fix only one: The model was too small. The rubric told it almost nothing. I fixed each independently and measured the effect. The result wasn't the tidy "write a better…
1Key Takeaways
- In Part 2 I built the laziest possible LLM judge — a tiny model ( Qwen2.5-1.5B ) and a one-line rubric — and it agreed with human votes only ~43% of the time, crammed every score into a 7–8 band, and tied a third of the comparisons humans had no trouble separating.
- Two things were wrong with that judge, and people usually fix only one: The model was too small.
- I fixed each independently and measured the effect.
- The result wasn't the tidy "write a better….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that in Part 2 I built the laziest possible LLM judge — a tiny model ( Qwen2.5-1.5B ) and a one-line rubric — and it agreed with human votes only ~43% of the time, crammed every score into a 7–8 band, and tied a third of the comparisons humans had no trouble separating.
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