| --- |
| license: mit |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - math |
| - reasoning |
| - reinforcement-learning |
| - deepmath |
| pretty_name: DeepMath RLCSD Format Difficulty Splits |
| --- |
| |
| # DeepMath RLCSD-format difficulty splits |
|
|
| This dataset is derived from [`zwhe99/DeepMath-103K`](https://huggingface.co/datasets/zwhe99/DeepMath-103K) |
| at revision `5cf055d1fe3d7a2eb19719ac020211469736ae44` and uses the nested parquet schema released by |
| [`Leyiii/RLCSD`](https://huggingface.co/datasets/Leyiii/RLCSD). |
|
|
| ## Files |
|
|
| | Path | Rows | Difficulty | |
| |---|---:|---| |
| | `deepmath_full/train.parquet` | 103,022 | Full upstream dataset | |
| | `deepmath_easy_10k/train.parquet` | 10,000 | `1.0 <= difficulty < 5.0` | |
| | `deepmath_medium_10k/train.parquet` | 10,000 | `5.0 <= difficulty < 7.0` | |
| | `deepmath_hard_10k/train.parquet` | 10,000 | `7.0 <= difficulty <= 10.0` | |
|
|
| The three subsets are pairwise disjoint by difficulty. Rows with missing required |
| fields and every occurrence of a duplicated normalized question are excluded from |
| the three sampling pools. Within each difficulty band, samples are selected |
| proportionally by exact half-step difficulty and then by topic. |
| Selection is deterministic (seed `42`) and uses a SHA-256 |
| ordering over the normalized question, source index, and pinned source revision. |
|
|
| ## Schema |
|
|
| Each parquet has exactly the RLCSD-style fields `prompt`, `reward_model`, |
| `data_source`, `ability`, and `extra_info`. `extra_info.solution` is selected uniformly from DeepMath's three R1 solutions |
| with Python's `random.seed(42)` behavior; `reward_model.ground_truth` comes from |
| `final_answer`. |
|
|
| ## License and attribution |
|
|
| The upstream DeepMath-103K dataset is released under the MIT license. Please |
| also follow its citation and attribution requirements. |
|
|
