--- license: apache-2.0 task_categories: - text-generation language: - en pretty_name: Domyn Edge Teacher Math Mix size_categories: - 10K Domyn

# Domyn Edge Teacher Math Mix > [!IMPORTANT] > **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](https://domyn.webflow.io/blog/domyn-edge-compact-model-open). The training data of [Domyn Edge Teacher Math](https://huggingface.co/domyn/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](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset) | MIT | 10,508 | 1.42M | 421 | 0.05M | | [Nemotron-3-Nano-RL-Training-Blend](https://huggingface.co/datasets/nvidia/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 ```python 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](ATTRIBUTION.md) before redistributing any part of this data. ## Citation ```bibtex @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} } ```