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zbeeb/Skywork-OR1-Math-Verifiable-Dedup

Skywork OR1 Math — Verifiable, Deduplicated 97,809 questions. Only parser-compatible references are included. Here, “verifiable” means every reference component parses with Math-Verify 0.8.0, with string fallback disabled. It does not mean that the answer has been independently proved correct or that grading model outputs is error-free. Skywork was processed independently: retain its math rows, clean them, deduplicate within Skywork, screen benchmark overlap and prompt leakage… See the full description on the dataset page: https://huggingface.co/datasets/zbeeb/Skywork-OR1-Math-Verifiable-Dedup.

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Dataset Card

Skywork OR1 Math — Verifiable, Deduplicated

97,809 questions. Only parser-compatible references are included. Here, “verifiable” means every reference component parses with Math-Verify 0.8.0, with string fallback disabled. It does not mean that the answer has been independently proved correct or that grading model outputs is error-free.

Skywork was processed independently: retain its math rows, clean them, deduplicate within Skywork, screen benchmark overlap and prompt leakage, then retain parser-compatible references. Shared questions with DeepScaleR remain in this dataset.

Preparation

See PREPARATION.md for normalization, duplicate thresholds, conflict handling, benchmark screening, parser filtering, and limitations. The complete preparation and publication code is pinned to Git commit 95f55c5e518588771db8d761879f306ae01465c2. manifest.json records counts and checksums; source-revisions.json pins the upstream snapshots.

Only this filtered training pool is published. Raw inputs, rejected examples, benchmark questions, unfiltered pools, and models are not included.

Loading

python
from datasets import load_dataset

data = load_dataset("zbeeb/Skywork-OR1-Math-Verifiable-Dedup", split="train")

The train split names the complete released pool; it is not a precomputed train/validation partition. Split by shared question groups across datasets before comparing experiments.

Schema

  • —id: SHA-256 of the representative normalized prompt.
  • —prompt, messages: original representative question and its single user message.
  • —answers: ordered reference components; do not assume these are alternative accepted answers.
  • —reference_answer_raw: original source reference serialized as JSON.
  • —datasets, source, source_records: memberships and provenance; source_records is serialized as JSON.
  • —verifiability: parser-compatibility flags; independent label verification is false.

Separate reference solutions are not appended to prompts. Explicit answer/solution section markers trigger conservative exclusion. Native model chat templates, generated responses, rewards, and reasoning-length restrictions are not embedded in this dataset.

Attribution and license

The upstream datasets are Skywork/Skywork-OR1-RL-Data and agentica-org/DeepScaleR-Preview-Dataset, as applicable in source-revisions.json. DeepScaleR declares MIT; the pinned Skywork card does not declare a dataset license. This derivative does not assign a new license to upstream material. Preserve upstream attribution and consult the relevant source terms.