YangyiYY/rl-value-confidence-train-math
rl-value-confidence-train-math Math-domain training set (~10K) for a confidence / correctness estimator, sampled from the numina portion of PRIME-RL/Eurus-2-RL-Data. Pairs with YangyiYY/rl-value-eval-math (eval) and a 50K RL-training split from the same pool (disjoint). Sampled ~uniformly across the 6 numina sub-sources (cn_k12, synthetic_math, olympiads, synthetic_amc, aops_forum, amc_aime), deduplicated by problem text, and disjoint from the RL-train and eval splits (0… See the full description on the dataset page: https://huggingface.co/datasets/YangyiYY/rl-value-confidence-train-math.
rl-value-confidence-train-math
Math-domain training set (~10K) for a confidence / correctness estimator, sampled from the numina portion of PRIME-RL/Eurus-2-RL-Data. Pairs with `YangyiYY/rl-value-eval-math` (eval) and a 50K RL-training split from the same pool (disjoint).
Sampled ~uniformly across the 6 numina sub-sources (cnk12, syntheticmath, olympiads, syntheticamc, aopsforum, amc_aime), deduplicated by problem text, and disjoint from the RL-train and eval splits (0 problem-text overlap).
Schema (our recipe)
data_source="math_box" · prompt=[{system: "Please reason step by step, and put your final answer within \boxed{}."}, {user: <problem>}] · ability="math" · reward_model.ground_truth (numina answer) · sub_source (numina origin: cnk12/syntheticmath/olympiads/syntheticamc/aopsforum/amcaime) · `extrainfo` (id, sub_source, split).