--- license: apache-2.0 configs: - config_name: jan data_files: - split: test path: main2025-jan.jsonl - config_name: apr data_files: - split: test path: main2025-apr.jsonl --- # JEE Mains 2025 Math Evaluation Set ## ๐Ÿงพ Dataset Summary 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. --- ## ๐Ÿš€ How to Load the Dataset You can load the evaluation data using the `datasets` library from Hugging Face: ```python 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") ``` --- ## ๐Ÿ“‚ Dataset Structure 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. | --- ## ๐Ÿ“Š Dataset Statistics | Split | Papers | Questions | | ------------ | ------ | --------- | | January 2025 | 10 | 250 | | April 2025 | 9 | 225 | | **Total** | 19 | **475** | * **MCQs**: \~80% * **NATs**: \~20% --- ## ๐Ÿ“ฅ Source 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. --- ## ๐Ÿ’ผ Intended Uses * Benchmarking Indian math LLMs * Evaluating symbolic + numeric reasoning * Comparing SFT/RLHF/retrieval-based models on real exams --- ## โš ๏ธ Limitations * Limited to mathematics domain --- ## ๐Ÿ“„ Citation ```bibtex @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}}, } ```