lm-sys / lm-sys/FastChat

Variation in MT-bench score

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Description

We ran the mt-bench multiple time with llama2-70b-chat.
With generated text(step 1 - ran once), GPT4 scoring(step 2 - ran multiple time) varies.
In our experiment it varied by 0.16 over 5 runs.

If we include text generation step also, it might vary more.
There are 2 variations:

  1. Text generation has temperature 0.7 for writing and roleplay, this may lead to variation in text generated from test model.
  2. Scoring by GPT-4: it vary every time we run for same generated text.

How is the scoring submitted in leaderboard or by others.

  1. Are we running once only
  2. Are we running multiple and submit the best score
  3. Are we running multiple and submit avg score

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Research direction

No files, tests, or entry points are named. Review the MT-bench generation, GPT-4 scoring, and leaderboard submission process, then clarify whether results use one run, repeated runs with an average, or another policy; done when the procedure and treatment of score variation are documented.

Written by the indexing model from the issue text.

Assessment

Domain
machine-learning
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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