| --- |
| license: apache-2.0 |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - sft |
| - math |
| - code |
| - reasoning |
| - shuffled |
| size_categories: |
| - 1M<n<10M |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train_*.jsonl |
| --- |
| |
| # Mephisto-MathCode_2M |
| |
| **2,000,000** non-thinking SFT examples — an even 1M/1M split of math and code |
| — drawn from |
| [openbmb/UltraData-SFT-2605](https://huggingface.co/datasets/openbmb/UltraData-SFT-2605), |
| filtered to English and globally shuffled. |
| |
| This is a **curation** pass, not a generation one: no model produced these |
| answers for this dataset. All credit for the content belongs to OpenBMB. What |
| is added here is language filtering, an exact 1M/1M balance, and a global |
| shuffle so the file can be streamed without a shuffle buffer. |
| |
| | `domain` | rows | |
| |---|---:| |
| | `Code` | 1,000,000 | |
| | `Math` | 1,000,000 | |
| |
| Source config/split: `Code/no_think` and `Math/no_think`. |
| |
| ## Format |
| |
| ```json |
| { |
| "uid": "...", |
| "messages": [ |
| {"role": "user", "content": "..."}, |
| {"role": "assistant", "content": "..."} |
| ], |
| "source": "UltraData-sft-2605", |
| "domain": "Code", |
| "think_type": "no_think" |
| } |
| ``` |
| |
| The source schema is preserved unchanged. Every row is exactly two turns |
| (`user`, `assistant`) and `think_type` is `no_think` throughout — responses are |
| direct answers with **no chain-of-thought block**, though math answers do show |
| their working as ordinary prose/LaTeX. |
| |
| `domain` distinguishes the two halves, and `uid` maps back to the source row. |
| |
| ## Filtering |
| |
| Only one filter was applied: **Chinese removal**. Rows whose prompt or answer |
| is more than 5% CJK characters were dropped. |
| |
| | | scanned | kept | dropped (CJK) | |
| |---|---:|---:|---:| |
| | Code | 1,000,171 | 1,000,000 | 171 (0.017%) | |
| | Math | 1,000,154 | 1,000,000 | 154 (0.015%) | |
| |
| Verified by re-running the filter over the output: 0 CJK rows and 0 duplicate |
| `uid`s remained. **No quality, length, or degeneracy filtering was performed** — |
| inspect before training. |
| |
| ## Shuffling |
| |
| Shuffled globally across both halves with a seeded Fisher–Yates permutation |
| (ChaCha8, seed 42), so every shard and every prefix is representative: |
| |
| | | Code | Math | |
| |---|---:|---:| |
| | shard 000 | 50.4% | 49.6% | |
| | shard 019 | 49.2% | 50.8% | |
| |
| `take(n)` on a streaming load gives an unbiased, balanced sample without an |
| extra shuffle buffer. |
| |
| The shuffle was done with a small memory-mapped Rust tool that permutes an |
| index of `(file_id, offset, length)` — 16 bytes per row, so 2M rows cost 32 MB |
| of RAM regardless of the 10 GB of text behind them, and line bytes go straight |
| from mmap to the output without ever entering the process heap. This matters |
| if you want to re-shuffle it yourself on a modest machine. |
|
|
| ## Caveats |
|
|
| - Unfiltered for quality. The source is broadly good but nothing here has been |
| checked for correctness, degeneracy, or answer length. |
| - Math rows are long (the 1M math rows are ~7.1 GB vs ~2.7 GB for 1M code |
| rows), so a token-balanced mix is **not** 50/50 by row count. |
| - English-only by construction; the source split is bilingual. |
| - No deduplication beyond exact `uid` collisions. |
|
|
| ## Provenance and license |
|
|
| All content from `openbmb/UltraData-SFT-2605` (Apache-2.0); see the source |
| dataset for its terms. Released under Apache-2.0. |
|
|
