Datasets:

YangyiYY
/

rl-value-confidence-train-math

license: mit
task_categories:
  - text-generation
language:
  - en
tags:
  - rl
  - confidence-estimation
  - calibration
  - math
  - numina
size_categories:
  - 1K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*.parquet

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 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: cn_k12/synthetic_math/olympiads/synthetic_amc/aops_forum/amc_aime) · extra_info (id, sub_source, split).