parallell/MOPD-Com-Training-Data

MOPD-Com Training Data

This repository contains the final labeled training mixture prepared for MOPD-Com. It contains 65,994 training examples in one Parquet file. It is a source-labeled, preprocessed dataset, not a claim of an exact reproduction of an unpublished paper preprocessing pipeline.

Domain composition

Routing label (extra_info.opd_teacher)	Examples
math	25,000
code	25,000
instruction_following	15,994
Total	65,994

The original sampled mixture had 25,000 math, 25,000 code, and 16,000 instruction-following examples. Six sampled HIR examples exceeded the 2,048-token prompt limit and were removed. The remaining mixture order is preserved. Domain labels were assigned from source provenance; no model was called for labeling.

Sources and sampling

• Math: icemoon28/MOPD-Training-Data, DeepMath-103K/train_filtered_level6.parquet (57,046 source rows).
• Code: the same dataset, Eurus/code_train.parquet (25,276 source rows).
• Instruction following: sastpg/HIR-16K, HIR_trainv1.jsonl (16,968 source rows). The instruction-following subset of icemoon28/MOPD-Training-Data was not used.

Pinned icemoon28 revision: 96e88d579cb1ee68c9183c52e5d133f58cf370bf. Pinned HIR revision: 2a95f69eb56cc47edc16a45f939cde479673a4cb. Per-domain shuffle seeds: math 42, code 43, instruction following 44; final mixture shuffle seed 42. No deduplication was applied.

Prompt construction

Math and code message contents are preserved. HIR prompts include the original question followed by all provided criteria, using this format:

{original question}

The output must follow the following rules:
1. {first criterion}
2. {second criterion}
...

This corresponds to a layout supported by the official HIR helper. No system prompt is included in any example. No target assistant answer is appended to the prompt.

Prompt lengths were measured using the Qwen/Qwen3-1.7B tokenizer with the chat template, add_generation_prompt=True, and enable_thinking=False. Every retained example has a prompt length of at most 2,048 tokens. Other tokenizers or chat template settings may produce different lengths.

Schema

• data_source: source identifier.
• prompt: list of messages with role and content, suitable for the project's chat template interface.
• ability: ability/domain metadata.
• reward_model: struct containing style and string ground_truth. Original reference/verifier content is preserved; JSON content is serialized as a string where needed.
• extra_info: routing label opd_teacher, unique index, source dataset/revision/file/row and original metadata, original HIR prompt and criteria, prompt construction metadata, prompt SHA256, prompt token length, and length/system-prompt flags.

The pure on-policy distillation training configuration uses generated rollouts and teacher/student probabilities. The preserved ground truth is not an assistant completion inserted into the input prompt.

Usage

from datasets import load_dataset
train = load_dataset('parallell/MOPD-Com-Training-Data', split='train')

To download the original prepared Parquet file:

from huggingface_hub import hf_hub_download
path = hf_hub_download(
    repo_id='parallell/MOPD-Com-Training-Data',
    repo_type='dataset',
    filename='data/train_prompt2048.parquet',
    local_dir='mopd_training_data',
)

For local MOPD-Com training, point the training data path to the downloaded Parquet file. This repository contains only the train split; no held-out validation split is provided.

Integrity

• File: data/train_prompt2048.parquet
• Bytes: 785742653
• Rows: 65994
• SHA256: 96d7fef2f0b4a72e7282b76d7a40d55413e7b4d84387d1c417e1ef08e612a7ec

Upstream terms and attribution

This is a processed mixture of the linked upstream datasets. Consult the upstream dataset cards and original sources for applicable licenses and use conditions. This card does not assign a new blanket license or replace upstream terms.