AdarshSingh7647/Eklav-Math-CotGen-Data
HETU-MathReasoning-CotGen-Data Training data for the HETU (Hints Enable True Understanding) paper. Task: math reasoning (AIME, GSM8K, MATH-500, Omni-MATH, GPQA-Diamond, MMLU) Method: CotGen Examples: 3,481 train / 35-36 held-out val Format: ShareGPT (system + conversations: [{from, value}]), used for LoRA SFT via LLaMA-Factory. Single-turn ShareGPT conversations, curated DeepSeek-R1-style math reasoning distillation. Each row: the raw math/logic problem (human turn) and the… See the full description on the dataset page: https://huggingface.co/datasets/AdarshSingh7647/Eklav-Math-CotGen-Data.
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1---2tags:3- hetu4- mathreasoning5- cotgen6---7 8# HETU-MathReasoning-CotGen-Data9 10Training data for the **HETU (Hints Enable True Understanding)** paper.11 12- **Task:** math reasoning (AIME, GSM8K, MATH-500, Omni-MATH, GPQA-Diamond, MMLU)13- **Method:** CotGen14- **Examples:** 3,481 train / 35-36 held-out val15- **Format:** ShareGPT (`system` + `conversations: [{from, value}]`), used for LoRA SFT via LLaMA-Factory.16 17Single-turn ShareGPT conversations, curated DeepSeek-R1-style math reasoning distillation. Each row: the raw math/logic problem (human turn) and the full teacher chain-of-thought plus a boxed final answer (gpt turn), with loss computed over the entire gpt turn.18 19Files:20- `train.json` -- training split21- `val.json` -- held-out validation split22 23See the HETU paper for full dataset construction methodology, and the corresponding24`HETU-*-MathReasoning-CotGen` model repos for checkpoints trained on this data.25