| --- |
| license: mit |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - dictation |
| - speech-to-text |
| - text-cleanup |
| - on-device |
| - synthetic |
| pretty_name: MacWispr Polish Training Data |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # MacWispr Polish — training & eval datasets |
|
|
| The complete open dataset behind [MacWispr](https://macwispr.lintware.com)'s on-device |
| dictation **polish model** (Qwen3.5-0.8B post-trained to turn raw speech-to-text into |
| clean, structured writing). Training pipeline and verifier live in the |
| [MacWispr repo](https://github.com/vasanthsreeram/macwispr/tree/main/bench/polish_posttrain). |
|
|
| ## Contents |
|
|
| | Path | Rows | What it is | |
| |---|---|---| |
| | `sft/train.jsonl` (+valid/test) | 3,011 / 276 / 173 | Main SFT pool. `{"text": "### Input:\n<raw>\n\n### Output:\n<gold>"}` | |
| | `synthetic/synth_hard.jsonl` | 311 | Synthetic hard-category examples (multi-list, numbered, mixed styles, checklist) generated with Grok, validated by the rule-based `polish_verifier`, deduped vs all other pools. `{"raw", "gold", "tags", "source"}` | |
| | `eval/ood_eval_set.jsonl` | 40 | Out-of-distribution eval suite (held out from all training). `{"id", "raw", "tags", ...}` | |
| | `dpo/dpo_prompts.jsonl` | 220 | Prompts + golds used to build DPO preference pairs | |
| | `results/` | — | Benchmark vs Claude Sonnet (same suite, same scorer), incl. per-case outputs | |
|
|
| ## Task |
|
|
| Input: raw ASR transcript with disfluencies and a spoken formatting request. |
| Output: cleaned text with the requested structure (bullets / `1.` numbered / |
| `- [ ]` checklists / multiple labelled lists / email), fillers removed, |
| self-corrections applied, questions preserved as questions (never answered). |
|
|
| ## Benchmark snapshot (2026-07-21) |
|
|
| 40-case OOD suite, shared rule-based scorer: |
|
|
| | System | Pass | Mean latency | |
| |---|---|---| |
| | MacWispr local 0.8B (4-bit, on-device) | 23/40 (57.5%) | 191 ms | |
| | Claude Sonnet (cloud) | 25/40 (62.5%) | 4,407 ms | |
|
|
| ## Provenance & license |
|
|
| Synthetic and curated data created for this project (no user dictations — |
| MacWispr never collects transcripts). Grok was used to draft the synthetic |
| examples; every gold is machine-validated by the open verifier. MIT. |
|
|
