| license: apache-2.0 | |
| task_categories: | |
| - text-generation | |
| tags: | |
| - math | |
| - code | |
| - on-policy-distillation | |
| # A2-OPD Dataset | |
| This dataset accompanies the paper [Rethinking Relative Policy Differences Transfer of On-Policy Distillation](https://huggingface.co/papers/2610.13205). | |
| Code: https://github.com/KnowledgeXLab/A2-OPD | |
| The dataset is organized by `math/` and `code/` folders and contains training and evaluation data for the A2-OPD experiments. | |
| ## Dataset Structure | |
| | Path | Split | Used for | | |
| |------|-------|----------| | |
| | `math/train.parquet` | train | DeepMath-103K training | | |
| | `math/test.parquet` | test | Training validation and offline math eval | | |
| | `code/train.parquet` | train | Eurus-RL-Code training | | |
| | `code/validation.parquet` | validation | Training validation during code RL | | |
| | `code/benchmarks/Humaneval_Plus/HumanEvalPlus.jsonl` | test | Offline HumanEval+ | | |
| | `code/benchmarks/Mbpp_Plus/MbppPlus.jsonl` | test | Offline MBPP+ | | |
| | `code/benchmarks/LivecodeBench/test.jsonl` | test | Offline LiveCodeBench | | |
| Training data must be in `verl` parquet format. Each row needs fields such as `data_source`, `prompt`, `ability`, `reward_model.ground_truth`, and optional `extra_info`. | |
| ## Sample Usage | |
| ```bash | |
| # One-click download (requires huggingface_hub: `hf` or `huggingface-cli`) | |
| hf download KnowledgeXLab/A2-OPD --repo-type dataset --local-dir data | |
| export A2OPD_DATA_ROOT=$PWD/data # default layout matches training/eval scripts | |
| ``` |