MMLU Pro Evaluator #41860

AbdelmohsenMS · 2025-07-02T02:58:10Z

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Please add an informative description that covers that changes made by the pull request and link all relevant issues.

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The pull request does not introduce [breaking changes]
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Title of the pull request is clear and informative.
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Pull request includes test coverage for the included changes.

github-actions · 2025-07-02T02:58:29Z

Thank you for your contribution @AbdelmohsenMS! We will review the pull request and get back to you soon.

github-actions · 2025-07-02T03:21:14Z

API Change Check

APIView identified API level changes in this PR and created the following API reviews

azure-ai-evaluation

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singankit · 2025-07-10T23:44:39Z

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_common/_base_regex_eval.py

+        self.regex_patterns = regex_patterns
+        self.is_missing_regex_patterns = regex_patterns is None
+        self.follow_instructions = []
+        self.scores = []
+        self.chain_of_thought_lengths = []


Do you want to expose any of them to external customers ? If not please remname them to with underscore for example self.is_missing_regex_patterns ---> self._is_missing_regex_patterns

singankit · 2025-07-10T23:46:24Z

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_mmlu/_mmlu.py

+    metrics both overall and grouped by subject and category. Use this evaluator when you want to
+    assess a model's general knowledge and reasoning abilities across diverse academic domains.
+
+    The MMLU score value is either 0 or 1, with higher scores indicating better performance.


is this accurate ? Should it be from 0-1 or between 0-1 ?

singankit · 2025-07-10T23:48:59Z

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_mmlu/_mmlu.py

+        self.subject2scores = defaultdict(list)
+        self.category2scores = defaultdict(list)
+
+    def update(self, prediction: str, label: str, json_data: dict) -> Dict[str, Any]:


If you would not like to expose it to customer please start the name of method with underscore(_)

singankit · 2025-07-10T23:49:45Z

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_common/_base_regex_eval.py

+
+        return result
+
+    def update(self, prediction: str, label: str, json_data: dict) -> Dict[str, Any]:


Please start name of method with underscore if it is not be exposed to customers

singankit · 2025-07-10T23:50:28Z

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_common/_base_regex_eval.py

+            "chain_of_thought_length": chain_of_thought_length,
+        }
+
+    def get_regex_patterns(


Please start name of method with underscore if it is not be exposed to customers

singankit · 2025-07-10T23:51:17Z

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_mmlu/_mmlu.py

+                "mmlu_score": sample_metrics["score"], # Just needed for _real_call
+                "accuracy": sample_metrics["score"],


Why do we have 2 property for score ?

MMLU Pro Evaluator

c9deafb

AbdelmohsenMS requested a review from a team as a code owner July 2, 2025 02:58

github-actions bot added Community Contribution Community members are working on the issue customer-reported Issues that are reported by GitHub users external to the Azure organization. Evaluation Issues related to the client library for Azure AI Evaluation labels Jul 2, 2025

singankit reviewed Jul 10, 2025

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MMLU Pro Evaluator #41860

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AbdelmohsenMS commented Jul 2, 2025 •

edited

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		return result

		def update(self, prediction: str, label: str, json_data: dict) -> Dict[str, Any]:

		"mmlu_score": sample_metrics["score"], # Just needed for _real_call
		"accuracy": sample_metrics["score"],

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Description

All SDK Contribution checklist:

General Guidelines and Best Practices

Testing Guidelines

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AbdelmohsenMS commented Jul 2, 2025 •

edited

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