Track the Stat Eval

[thesofakillers]

@JunShern will review this

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Eval details 📑

Eval name

Track the stat

Eval description

This eval measures how well models can implicitly keep track of task state, by asking models to compute the rolling median or the rolling mode over a sequence of integers.

What makes this a useful eval?

[Insert why this eval is worth including and any additional context]

Criteria for a good eval ✅

Below are some of the criteria we look for in a good eval. In general, we are seeking cases where the model does not do a good job despite being capable of generating a good response (note that there are some things large language models cannot do, so those would not make good evals).

Your eval should be:

• Thematically consistent: The eval should be thematically consistent. We'd like to see a number of prompts all demonstrating some particular failure mode. For example, we can create an eval on cases where the model fails to reason about the physical world.
• Contains failures where a human can do the task, but either GPT-4 or GPT-3.5-Turbo could not.
• Includes good signal around what is the right behavior. This means either a correct answer for Basic evals or the Fact Model-graded eval, or an exhaustive rubric for evaluating answers for the Criteria Model-graded eval.
• Include at least 15 high-quality examples.

If there is anything else that makes your eval worth including, please document it below.

Unique eval value

Insert what makes your eval high quality that was not mentioned above. (Not required)

Eval structure 🏗️

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Final checklist 👀

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Eval JSON data

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Eval

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[JunShern]

Toy task but conceptually fascinating. Nice work, thanks for the neat implementation too!