MMLU Redux

src/lighteval/models/vllm/vllm_model.py

@@ -487,7 +487,8 @@ def _loglikelihood_tokens(
                     tokenized_contexts_batch.append(tokenized_context)
 
             # Left truncate the inputs to the maximum length
-            inputs = [input[-self.max_length :] for input in inputs]
+            if self.max_length:  # can be None if the model is initialized with ray
+                inputs = [input[-self.max_length :] for input in inputs]
             outputs = self._generate(inputs, generate=False)
 
             flat_index = 0

src/lighteval/tasks/default_prompts.py

@@ -1862,6 +1862,27 @@ def mmlu_helm(line, task_name: str = None):
     )
 
 
+def mmlu_redux_2(line, topic, task_name: str = None):
+    """
+    Ref: https://arxiv.org/abs/2406.04127
+    """
+    query = f"The following are multiple choice questions (with answers) about {topic.replace('_', ' ')}.\n\n"
+    query += line["question"] + "\n"
+    query += "".join([f"{key}. {choice}\n" for key, choice in zip(LETTER_INDICES, line["choices"])])
+    query += "Answer: "
+
+    # Handle answer format - MMLU-Redux-2 uses integer indices directly
+    gold_ix = line["answer"] if isinstance(line["answer"], int) else int(line["answer"])
+
+    return Doc(
+        task_name=task_name,
+        query=query,
+        choices=LETTER_INDICES[: len(line["choices"])],
+        gold_index=gold_ix,
+        instruction=f"The following are multiple choice questions (with answers) about {topic.replace('_', ' ')}.\n\n",
+    )
+
+
 def mmlu_qa_abstract_algebra(line, task_name: str = None):
     return mmlu_qa(line, "abstract_algebra", task_name)
 

src/lighteval/tasks/default_tasks.py

@@ -22727,3 +22727,142 @@
     stop_sequence=["\n"],
     version=0,
 )
+
+# MMLU-Redux-2 Tasks
+_MMLU_REDUX_2_SUBSETS = [
+    "abstract_algebra",
+    "anatomy",
+    "astronomy",
+    "business_ethics",
+    "clinical_knowledge",
+    "college_biology",
+    "college_chemistry",
+    "college_computer_science",
+    "college_mathematics",
+    "college_medicine",
+    "college_physics",
+    "computer_security",
+    "conceptual_physics",
+    "econometrics",
+    "electrical_engineering",
+    "elementary_mathematics",
+    "formal_logic",
+    "global_facts",
+    "high_school_biology",
+    "high_school_chemistry",
+    "high_school_computer_science",
+    "high_school_european_history",
+    "high_school_geography",
+    "high_school_government_and_politics",
+    "high_school_macroeconomics",
+    "high_school_mathematics",
+    "high_school_microeconomics",
+    "high_school_physics",
+    "high_school_psychology",
+    "high_school_statistics",
+    "high_school_us_history",
+    "high_school_world_history",
+    "human_aging",
+    "human_sexuality",
+    "international_law",
+    "jurisprudence",
+    "logical_fallacies",
+    "machine_learning",
+    "management",
+    "marketing",
+    "medical_genetics",
+    "miscellaneous",
+    "moral_disputes",
+    "moral_scenarios",
+    "nutrition",
+    "philosophy",
+    "prehistory",
+    "professional_accounting",
+    "professional_law",
+    "professional_medicine",
+    "professional_psychology",
+    "public_relations",
+    "security_studies",
+    "sociology",
+    "us_foreign_policy",
+    "virology",
+    "world_religions",
+]
+
+_mmlu_redux_2_tasks = {
+    subset: LightevalTaskConfig(
+        name=f"mmlu_redux_2:{subset}",
+        suite=["lighteval"],
+        prompt_function=lambda line, task_name=None, s=subset: prompt.mmlu_redux_2(line, s, task_name),
+        hf_repo="edinburgh-dawg/mmlu-redux-2.0",
+        hf_subset=subset,
+        hf_avail_splits=["test"],
+        evaluation_splits=["test"],
+        few_shots_split=None,
+        few_shots_select=None,
+        generation_size=1,
+        metrics=[Metrics.loglikelihood_acc],
+        stop_sequence=["\n"],
+        trust_dataset=True,
+        version=0,
+    )
+    for subset in _MMLU_REDUX_2_SUBSETS
+}
+
+mmlu_redux_2_abstract_algebra = _mmlu_redux_2_tasks["abstract_algebra"]
+mmlu_redux_2_anatomy = _mmlu_redux_2_tasks["anatomy"]
+mmlu_redux_2_astronomy = _mmlu_redux_2_tasks["astronomy"]
+mmlu_redux_2_business_ethics = _mmlu_redux_2_tasks["business_ethics"]
+mmlu_redux_2_clinical_knowledge = _mmlu_redux_2_tasks["clinical_knowledge"]
+mmlu_redux_2_college_biology = _mmlu_redux_2_tasks["college_biology"]
+mmlu_redux_2_college_chemistry = _mmlu_redux_2_tasks["college_chemistry"]
+mmlu_redux_2_college_computer_science = _mmlu_redux_2_tasks["college_computer_science"]
+mmlu_redux_2_college_mathematics = _mmlu_redux_2_tasks["college_mathematics"]
+mmlu_redux_2_college_medicine = _mmlu_redux_2_tasks["college_medicine"]
+mmlu_redux_2_college_physics = _mmlu_redux_2_tasks["college_physics"]
+mmlu_redux_2_computer_security = _mmlu_redux_2_tasks["computer_security"]
+mmlu_redux_2_conceptual_physics = _mmlu_redux_2_tasks["conceptual_physics"]
+mmlu_redux_2_econometrics = _mmlu_redux_2_tasks["econometrics"]
+mmlu_redux_2_electrical_engineering = _mmlu_redux_2_tasks["electrical_engineering"]
+mmlu_redux_2_elementary_mathematics = _mmlu_redux_2_tasks["elementary_mathematics"]
+mmlu_redux_2_formal_logic = _mmlu_redux_2_tasks["formal_logic"]
+mmlu_redux_2_global_facts = _mmlu_redux_2_tasks["global_facts"]
+mmlu_redux_2_high_school_biology = _mmlu_redux_2_tasks["high_school_biology"]
+mmlu_redux_2_high_school_chemistry = _mmlu_redux_2_tasks["high_school_chemistry"]
+mmlu_redux_2_high_school_computer_science = _mmlu_redux_2_tasks["high_school_computer_science"]
+mmlu_redux_2_high_school_european_history = _mmlu_redux_2_tasks["high_school_european_history"]
+mmlu_redux_2_high_school_geography = _mmlu_redux_2_tasks["high_school_geography"]
+mmlu_redux_2_high_school_government_and_politics = _mmlu_redux_2_tasks["high_school_government_and_politics"]
+mmlu_redux_2_high_school_macroeconomics = _mmlu_redux_2_tasks["high_school_macroeconomics"]
+mmlu_redux_2_high_school_mathematics = _mmlu_redux_2_tasks["high_school_mathematics"]
+mmlu_redux_2_high_school_microeconomics = _mmlu_redux_2_tasks["high_school_microeconomics"]
+mmlu_redux_2_high_school_physics = _mmlu_redux_2_tasks["high_school_physics"]
+mmlu_redux_2_high_school_psychology = _mmlu_redux_2_tasks["high_school_psychology"]
+mmlu_redux_2_high_school_statistics = _mmlu_redux_2_tasks["high_school_statistics"]
+mmlu_redux_2_high_school_us_history = _mmlu_redux_2_tasks["high_school_us_history"]
+mmlu_redux_2_high_school_world_history = _mmlu_redux_2_tasks["high_school_world_history"]
+mmlu_redux_2_human_aging = _mmlu_redux_2_tasks["human_aging"]
+mmlu_redux_2_human_sexuality = _mmlu_redux_2_tasks["human_sexuality"]
+mmlu_redux_2_international_law = _mmlu_redux_2_tasks["international_law"]
+mmlu_redux_2_jurisprudence = _mmlu_redux_2_tasks["jurisprudence"]
+mmlu_redux_2_logical_fallacies = _mmlu_redux_2_tasks["logical_fallacies"]
+mmlu_redux_2_machine_learning = _mmlu_redux_2_tasks["machine_learning"]
+mmlu_redux_2_management = _mmlu_redux_2_tasks["management"]
+mmlu_redux_2_marketing = _mmlu_redux_2_tasks["marketing"]
+mmlu_redux_2_medical_genetics = _mmlu_redux_2_tasks["medical_genetics"]
+mmlu_redux_2_miscellaneous = _mmlu_redux_2_tasks["miscellaneous"]
+mmlu_redux_2_moral_disputes = _mmlu_redux_2_tasks["moral_disputes"]
+mmlu_redux_2_moral_scenarios = _mmlu_redux_2_tasks["moral_scenarios"]
+mmlu_redux_2_nutrition = _mmlu_redux_2_tasks["nutrition"]
+mmlu_redux_2_philosophy = _mmlu_redux_2_tasks["philosophy"]
+mmlu_redux_2_prehistory = _mmlu_redux_2_tasks["prehistory"]
+mmlu_redux_2_professional_accounting = _mmlu_redux_2_tasks["professional_accounting"]
+mmlu_redux_2_professional_law = _mmlu_redux_2_tasks["professional_law"]
+mmlu_redux_2_professional_medicine = _mmlu_redux_2_tasks["professional_medicine"]
+mmlu_redux_2_professional_psychology = _mmlu_redux_2_tasks["professional_psychology"]
+mmlu_redux_2_public_relations = _mmlu_redux_2_tasks["public_relations"]
+mmlu_redux_2_security_studies = _mmlu_redux_2_tasks["security_studies"]
+mmlu_redux_2_sociology = _mmlu_redux_2_tasks["sociology"]
+mmlu_redux_2_us_foreign_policy = _mmlu_redux_2_tasks["us_foreign_policy"]
+mmlu_redux_2_virology = _mmlu_redux_2_tasks["virology"]
+mmlu_redux_2_world_religions = _mmlu_redux_2_tasks["world_religions"]