| --- |
| license: cc-by-4.0 |
| language: |
| - ru |
| - en |
| task_categories: |
| - question-answering |
| - text-generation |
| size_categories: |
| - n<1K |
| pretty_name: ABench75 |
| tags: |
| - benchmark |
| - evaluation |
| - reasoning |
| - cybersecurity |
| - math |
| - logic |
| - code |
| --- |
| |
| # ABench75 |
|
|
| A compact bilingual (Russian + English) benchmark for instruction-following and |
| short-answer reasoning across five domains: **math, logic, code, cybersecurity, |
| general**. |
|
|
| - **Total tasks:** 375 (75 per domain) |
| - **Public split:** 300 tasks (`data/tasks_public.jsonl`) |
| - **Private holdout:** 75 tasks (15 per domain, not published) — for honest tracking |
| - **Languages:** ~59% English / ~41% Russian |
| - **Scoring:** regex match on the final answer (`re` field, case-insensitive) |
|
|
| > Canary: `ABENCH75_CANARY_8f3c1d9a`. If you find this string in a training corpus, |
| > the benchmark has leaked — treat contaminated scores accordingly. |
|
|
| ## Format |
|
|
| Each line of `data/tasks_public.jsonl` is one JSON object: |
|
|
| ```json |
| {"id": "math_ru_0", "lang": "ru", "domain": "math", |
| "q": "Сколько будет 74 умножить на 56? Ответь только числом.", |
| "re": "\\b4144\\b"} |
| ``` |
|
|
| - `id` — stable identifier |
| - `lang` — `ru` | `en` |
| - `domain` — `math` | `logic` | `code` | `cyber` | `general` |
| - `q` — the prompt |
| - `re` — Python regex the generated answer must match (search, ignore case) |
|
|
| ## Usage |
|
|
| ```bash |
| pip install -r requirements.txt # torch, transformers, peft (optional) |
| python run_eval.py --model <hf-model-or-path> --tasks data/tasks_public.jsonl |
| # optional: LoRA adapter + reasoning-level tag |
| python run_eval.py --model ./merged --adapter ./lora --effort high --batch 8 |
| ``` |
|
|
| The runner prints overall accuracy and breakdowns by domain and language. |
|
|
| Scoring is intentionally simple: the answer must match `re`. Models that emit |
| reasoning should put the final answer in plain text (the runner strips common |
| `<think>…</think>` wrappers first). |
|
|
| ## Results (public split, 300 tasks) |
|
|
| | model | params | overall | math | logic | code | cyber | general | |
| |---|---|---|---|---|---|---|---| |
| | Velary 1.2 Flash (medium) | 1.2B | 82.7% | 97% | 49% | 85% | 96% | 85% | |
| | Velary 1.2 Flash (high) | 1.2B | 81.6% | 96% | 43% | 85% | 96% | 88% | |
| | Velary Mini (no-think) | 0.35B | 50.7% | 32% | 39% | 67% | 55% | 61% | |
|
|
| Numbers are from the public 300-task split; the private 75-task holdout is reported |
| separately by the maintainers. |
|
|
| ## Design notes & limitations |
|
|
| - Short-answer regex scoring favours direct final answers; it is not a judge for |
| long-form quality. |
| - 75 tasks per domain is enough for a quick signal, not for fine-grained ranking; |
| treat differences of a few points as noise. |
| - Categories are deliberately broad; see `data/tasks_public.jsonl` for coverage. |
|
|
| ## Split policy |
|
|
| The public/private split is stratified by domain (60 public / 15 private per domain). |
| The private holdout is kept out of this repository to reduce contamination and to |
| provide a cleaner progress signal. |
|
|
| ## License |
|
|
| - **Data** (`data/tasks_public.jsonl`): CC BY 4.0. |
| - **Code** (`run_eval.py`, tooling): MIT — see `LICENSE`. |
