Neural-Hacker/distilbert-jee-math-mcq-2025
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This dataset contains 475 math questions from the official JEE Mains 2025 examination, covering both January and April sessions. It is curated to benchmark mathematical reasoning models under high-stakes exam conditions.
You can load the evaluation data using the datasets library from Hugging Face:
from datasets import load_dataset
# Load January session evaluation set
jan_data = load_dataset("PhysicsWallahAI/JEE-Main-2025-Math", "jan", split="test")
# Load April session evaluation set
apr_data = load_dataset("PhysicsWallahAI/JEE-Main-2025-Math", "apr", split="test")
Each sample is stored as a JSON object with the following fields:
| Field Name | Type | Description |
|---|---|---|
question |
string |
Math problem text (can include LaTeX) |
answer |
string |
Final answer (NAT or symbolic form) |
question_type |
int |
0 = Numerical Answer Type, 1 = Multiple Choice Question |
options |
list |
List of answer choices (present only for MCQ) |
correct_options |
list |
Indices of correct options in options[] (for MCQ only) |
additional_data |
dict |
Placeholder for extended fields used during model training or evaluation. |
metadata |
dict |
Optional metadata providing contextual information about the question. |
| Split | Papers | Questions |
|---|---|---|
| January 2025 | 10 | 250 |
| April 2025 | 9 | 225 |
| Total | 19 | 475 |
All questions were sourced from official JEE Mains 2025 mathematics papers publicly released by NTA. Answer keys were cross-verified with NTA final answer releases.
@misc{jee2025math,
title = {JEE Mains 2025 Math Evaluation Set},
author = {Physics Wallah AI Research},
year = {2025},
note = {Official JEE Mains 2025 math questions curated for evaluating educational language models},
howpublished = {\url{https://huggingface.co/datasets/PhysicsWallahAI/JEE-Main-2025-Math}},
}