| --- |
| language: en |
| license: mit |
| tags: |
| - math |
| - reasoning |
| - grpo |
| - verl |
| - reinforcement-learning |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/verl_deepscaler_clean_39179.parquet |
| --- |
| |
| # DeepScaleR-Verl-Clean |
|
|
| A single cleaned, deduplicated, verl-ready parquet built from four partial dumps of the |
| DeepScaleR math dataset (`agentica-org/DeepScaleR-Preview-Dataset`, MIT licensed). It is |
| meant for rule-based-reward GRPO/RL training with the |
| [verl](https://github.com/volcengine/verl) framework. |
|
|
| ## Files |
|
|
| | File | Rows | |
| |---|---| |
| | `data/verl_deepscaler_clean_39179.parquet` | 39179 | |
| | `data/cleaning_report.json` | full paper trail of every dropped row | |
|
|
| ## How it was built |
|
|
| Sources were read in priority order (`deepscaler_part1.jsonl`, `deepscaler_part2.jsonl`, |
| `deepscaler_export.json`, `deepscaler_legacy.jsonl`; within a file, earlier rows win): |
|
|
| 1. **Validity** - a row is garbage unless its statement *and* its answer are both present |
| and non-blank after trimming. Invalid rows are removed *before* deduplication, so a |
| broken copy can never steal the slot of a good copy. Rows whose statement is unusable |
| are recorded as `missing_problem`, rows with a usable statement but no answer as |
| `missing_answer`. A missing `solution` is not garbage: it is stored as an empty string. |
| 2. **Identity / deduplication** - identity is the trimmed statement text. Only the first |
| occurrence (by source priority, then row order) is kept; every later copy is dropped as |
| `duplicate`, including legacy copies that carry stale answers. |
| 3. **Ordering / indexing** - survivors are sorted by statement text ascending (plain |
| code-point ordering) and numbered 0..N-1; `extra_info.index` equals the row's position |
| and the parquet is physically in that order. Prompts carry the trimmed statement and |
| `reward_model.ground_truth` the trimmed answer. |
|
|
| Totals: 43608 input rows -> 39179 kept, 4390 dropped as duplicates, 39 dropped as invalid. |
| See `data/cleaning_report.json` for the per-row detail of everything that was thrown away. |
|
|
| ## Schema (verl) |
|
|
| Five columns, in this order: |
|
|
| | Column | Content | |
| |---|---| |
| | `data_source` | `"DeepScaleR"` | |
| | `prompt` | `[{"role": "user", "content": "<trimmed problem statement>"}]` | |
| | `ability` | `"math"` | |
| | `reward_model` | `{"style": "rule", "ground_truth": "<trimmed answer>"}` | |
| | `extra_info` | `{"index": <row position>, "solution": "<solution, or empty string>"}` | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("dusersad12/DeepScaleR-Verl-Clean", split="train") |
| ``` |
|
|
