MMLU-Pro

Overview

MMLU-Pro is an enhanced version of MMLU with increased difficulty and reasoning requirements. It features 10 answer choices instead of 4 and includes more challenging questions requiring deeper reasoning across 14 diverse domains.

Task Description

Task Type: Multiple-Choice Question Answering (10 options)
Input: Question with up to 10 answer choices
Output: Single correct answer letter (A-J)
Domains: 14 subjects including science, law, engineering, psychology

Key Features

10 answer choices per question (vs 4 in original MMLU)
More challenging questions requiring reasoning
Includes Chain-of-Thought (CoT) explanations
14 diverse subjects covered
Reduced impact of random guessing (10% vs 25%)

Evaluation Notes

Default configuration uses 5-shot examples
Answers should follow "ANSWER: [LETTER]" format
Uses subject-specific few-shot examples
Step-by-step reasoning encouraged
Evaluates on test split with validation for few-shot

Properties

Property	Value
Benchmark Name	`mmlu_pro`
Dataset ID	TIGER-Lab/MMLU-Pro
Paper	N/A
Tags	`Knowledge`, `MCQ`
Metrics	`acc`
Default Shots	5-shot
Evaluation Split	`test`
Train Split	`validation`

Data Statistics

Metric	Value
Total Samples	12,032
Prompt Length (Mean)	4959.66 chars
Prompt Length (Min/Max)	3048 / 12100 chars

Per-Subset Statistics:

Subset	Samples	Prompt Mean	Prompt Min	Prompt Max
`computer science`	410	5184.05	4696	7303
`math`	1,351	4853.54	4574	7519
`chemistry`	1,132	4567.2	4182	5975
`engineering`	969	3595.66	3048	5775
`law`	1,101	7001.35	5581	9200
`biology`	717	5881.08	5179	7850
`health`	818	4624.44	4134	9310
`physics`	1,299	4389.59	4004	6511
`business`	789	4646.01	4316	6915
`philosophy`	499	3760.1	3360	5289
`economics`	844	4680.21	4118	6907
`other`	924	3730.86	3316	6108
`psychology`	798	5274.19	4656	6942
`history`	381	9919.94	8711	12100

Sample Example

Subset: computer science

{
  "input": [
    {
      "id": "79336f87",
      "content": "The following are multiple choice questions (with answers) about computer science. Think step by step and then finish your answer with 'ANSWER: [LETTER]' (without quotes) where [LETTER] is the correct letter choice.\n\nQuestion:\nA certain pipel ... [TRUNCATED] ...  random index of a larger value.\nG) The method should be written to return the largest index among larger values.\nH) The method should be written on the assumption that there is only one value in the array that is larger than the given item.\n"
    }
  ],
  "choices": [
    "The method should return an error if more than one larger value is found.",
    "The specification should be modified to indicate what should be done if there is more than one index of larger values.",
    "The method should be written to output a message if more than one larger value is found.",
    "The method should be written so as to return the index of every occurrence of a larger value.",
    "The method should be written to return the last occurrence of a larger value.",
    "The method should return a random index of a larger value.",
    "The method should be written to return the largest index among larger values.",
    "The method should be written on the assumption that there is only one value in the array that is larger than the given item."
  ],
  "target": "B",
  "id": 0,
  "group_id": 0,
  "subset_key": "computer science",
  "metadata": {
    "cot_content": "",
    "subject": "computer science",
    "question_id": 10356
  }
}

Note: Some content was truncated for display.

Prompt Template

Prompt Template:

Answer the following multiple choice question. The last line of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}. Think step by step before answering.

Question:
{question}
Options:
{choices}

Few-shot Template

The following are multiple choice questions (with answers) about {subject}. Think step by step and then finish your answer with 'ANSWER: [LETTER]' (without quotes) where [LETTER] is the correct letter choice.

{examples}
Answer the following multiple choice question. The last line of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}. Think step by step before answering.

Question:
{question}
Options:
{choices}

Usage

Using CLI

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets mmlu_pro \
    --limit 10  # Remove this line for formal evaluation

Using Python

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['mmlu_pro'],
    dataset_args={
        'mmlu_pro': {
            # subset_list: ['computer science', 'math', 'chemistry']  # optional, evaluate specific subsets
        }
    },
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)

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