Datasets:

domyn
/

Domyn-Edge-Teacher-Math-Mix

license: apache-2.0
task_categories:
  - text-generation
language:
  - en
pretty_name: Domyn Edge Teacher Math Mix
size_categories:
  - 10K<n<100K
tags:
  - domyn
  - domyn-edge
  - teacher
  - math
  - grpo
configs:
  - config_name: rl
    data_files:
      - split: train
        path: data/rl/train-*.parquet
      - split: test
        path: data/rl/test-*.parquet

Domyn Edge Teacher Math Mix

Phased release. Domyn Edge is a rolling release in three bundles. This dataset is part of the second bundle, together with the domain teachers and their post-training data. For an overview, see the launch blog post.

The training data of Domyn Edge Teacher Math, in one config:

Config	Stage	Train	Test
`rl`	GRPO, math problems with a verifiable final answer	20,153 (2.96M tokens)	815 (0.11M tokens)

`rl`: GRPO problems

Math problems with a single verifiable final answer. The final answer in the response is checked against reward.ground_truth.answer with math-verify. Each prompt carries a system message that asks for the final answer in \boxed{} or on a final ANSWER: $ANSWER line.

Source	License	Train rows	Train tokens	Test rows	Test tokens
DeepScaleR-Preview-Dataset	MIT	10,508	1.42M	421	0.05M
Nemotron-3-Nano-RL-Training-Blend, math slice	ODC-BY 1.0	9,645	1.53M	394	0.06M
Total		20,153	2.96M	815	0.11M

Tokens are prompt tokens, as in the token_length column. The 4,606 train rows that ask for an ANSWER: line are copies of other train rows; metadata.augmented_from names the original.

Decontamination

Before training, the problems were decontaminated against the benchmarks we evaluate on: AIME 2024, AIME 2025, AIME 2026, HMMT February 2025, HMMT February 2026, GSM8K, MGSM, GPQA Diamond, IMO-AnswerBench, IMO-ProofBench and LiveBench (math). This removed 22 train and 2 test problems. The ANSWER: copies were made afterwards, from the remaining problems.

How to use

from datasets import load_dataset

rl_train = load_dataset("domyn/Domyn-Edge-Teacher-Math-Mix", "rl", split="train")
rl_test = load_dataset("domyn/Domyn-Edge-Teacher-Math-Mix", "rl", split="test")

Columns

Column	Type	Description
`messages`	list	The prompt: `role` and `content` of each message (the other message fields are null).
`tools`	string	Always null in this config.
`task`	string	Task family.
`source`	string	Upstream dataset.
`license`	string	License of the upstream record.
`metadata`	string	JSON-encoded upstream metadata.
`reward`	string	JSON-encoded reward data: `ground_truth` and the scoring `style`. Here `ground_truth.answer` is the reference final answer.
`token_length`	int	Prompt length in tokens.
`uuid`	string	Record identifier.

To train with NeMo-Gym, as we did, map each row to the math_with_judge_simple_agent input: responses_create_params.input = messages; question = reward.ground_truth.question, or the user message when absent; expected_answer = reward.ground_truth.answer; agent_ref = {"type": "responses_api_agents", "name": "math_with_judge_simple_agent"}.

License

Our contributions to this dataset, including the curation and the mix composition, are released under the Apache License 2.0. Upstream datasets keep their original license terms. Read ATTRIBUTION.md before redistributing any part of this data.

Citation

@misc{domyn_edge_teacher_math_mix_2026,
  title     = {Domyn Edge Teacher Math Mix},
  author    = {Domyn},
  year      = {2026},
  note      = {Technical report, forthcoming in November 2026.},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/domyn/Domyn-Edge-Teacher-Math-Mix}
}