Update README.md

README.md

@@ -1,4 +1,19 @@
 ---
+dataset_name: openmed-community/mmlu-5-options-rl-ready
+tags:
+  - MMLU
+  - evaluation
+  - DPO
+  - RL
+  - SFT
+pretty_name: MMLU – 5-Options RL-Ready
+license: mit
+language:
+  - en
+task_categories:
+  - multiple-choice
+  - question-answering
+  - reinforcement-learning
 dataset_info:
   features:
   - name: question
@@ -44,3 +59,61 @@ configs:
   - split: test
     path: data/test-*
 ---
+
+# MMLU – 5-Options RL-Ready
+
+**A standardized, RL-friendly remix of MMLU** with explicit negatives and a unified five-option presentation string for each question. Ideal for **DPO** and other RL setups while remaining drop-in for classic multiple-choice evaluation.
+
+## What’s inside
+
+* **Splits & size:** ~**97.8k train** + **2k test** ≈ **99.8k total**.
+* **Schema (core fields):**
+
+  * `question: str`
+  * `choices: list[str]` *(canonical options, typically 4 as in original MMLU)*
+  * `answer: int` *(0-based index)*
+  * `task: str` *(subject/task label; ~55 values)*
+  * `output: str` *(correct option text)*
+  * `options: str` *(single markdown-style block with **(1)…(5)** enumerated choices for unified 5-option prompts)*
+  * `letter: str` *(correct letter tag)*
+  * `incorrect_letters: list[str]`
+  * `incorrect_answers: list[str]`
+  * `single_incorrect_answer: str` *(one negative for pairwise prefs)*
+  * `system_prompt: str` *(single default value)*
+  * `input: str` *(ready-to-use user message text)* 
+
+> Note: The dataset provides both the **original structured `choices` array** (as in MMLU) and a **five-option `options` string** for standardized, list-variant prompting in RL pipelines.
+
+## Why it’s RL-ready
+
+* **Explicit negatives:** `incorrect_answers` + `single_incorrect_answer` enable **DPO**, pairwise prefs, and contrastive training without extra preprocessing.
+* **Unified prompts:** `system_prompt` + `input` and the five-option `options` string make it simple to build consistent chat-style prompts across frameworks.
+
+## Example record
+
+```json
+{
+  "question": "Which statement best describes the critics' reaction to the Segway?",
+  "choices": ["Nothing but an electrical device.", "A disappointing engineering mistake.", "An expensive and disappointing invention.", "Disappointing, but still a successful device."],
+  "answer": 3,
+  "task": "miscellaneous",
+  "output": "Disappointing, but still a successful device.",
+  "options": "(1) ... (2) ... (3) ... (4) ... (5) ...",
+  "letter": "(3)",
+  "incorrect_letters": ["(1)", "(2)", "(4)", "(5)"],
+  "incorrect_answers": ["...", "...", "...", "..."],
+  "single_incorrect_answer": "...",
+  "system_prompt": "You are a helpful tutor.",
+  "input": "Choose the correct answer from the options below.\n\n<question + (1)…(5) options>"
+}
+```
+
+## Intended uses
+
+* **Evaluation** of general reasoning on MMLU tasks with standardized five-option prompts.
+* **SFT** with chat-style formatting.
+* **DPO / RL** using explicit positive vs. negative pairs from `single_incorrect_answer` or full `incorrect_answers`.
+
+## Source & attribution
+
+Derived from the original **MMLU** dataset by Hendrycks et al. (CAIS) [cais/mmlu]([cais/mmlu](https://huggingface.co/datasets/cais/mmlu)). Please cite the original work when using this derivative.