| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: SENSUS Bench v1 Evaluation |
| task_categories: |
| - text-generation |
| tags: |
| - mathematics |
| - education |
| - tutoring |
| - synthetic |
| - evaluation |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: eval.jsonl |
| --- |
| |
| # SENSUS Bench v1 Evaluation |
|
|
| Lorm Labs | Evaluation kit v1.0 | 26 October 2026 |
|
|
| ## Summary |
|
|
| The 76 evaluation cases behind the SENSUS Bench v1.0 results, with the |
| scripts to generate and grade replies and the recorded replies and grades of |
| the published models. Use it with SENSUS SFT v1.1 to check whether a model you |
| fine-tune reproduces the recorded scores. None of these questions appear in |
| the training file. |
|
|
| ## Files |
|
|
| - `eval.jsonl`: the 76 evaluation cases. |
| - `sample.py`: generates one reply per case from an OpenAI-compatible endpoint. |
| - `grade.py`: grades replies with the two-grader checklist method. |
| - `recorded/models.json`: the published models and their recorded scores. |
| - `recorded/replies.jsonl`: every recorded reply with both graders' marks. |
| - `LICENSE`: CC BY 4.0 for the data. `LICENSE-CODE`: MIT for the scripts. |
| - `verify.py`, `manifest.json`, `SHA256SUMS`: release fingerprints and an offline check. |
|
|
| ## Data fields (`eval.jsonl`) |
|
|
| | Field | Content | |
| |---|---| |
| | `id` | `e001` to `e076`. | |
| | `standard` | Common Core State Standards for Mathematics code. | |
| | `messages` | The `system` and `user` messages given to the tutor model, in the training format. | |
| | `criteria` | Checklist lines a good reply meets; the first line says the reply states nothing false. | |
| | `critical` | Serious errors; marking any one scores the reply 0. | |
| | `reference` | A reply that meets the checklist, for reference only. | |
|
|
| ## How to evaluate a model |
|
|
| ``` |
| python3 verify.py |
| python3 grade.py --check-recorded # offline: reproduces the table below |
| python3 sample.py --model <your-model> --out replies.jsonl |
| python3 grade.py --replies replies.jsonl --out grades.jsonl |
| ``` |
|
|
| `sample.py` uses temperature 0, at most 900 output tokens and thinking off, the |
| recorded settings. `grade.py` calls two graders (`claude-opus-5-5` and |
| `gpt-6.1-sol` at medium reasoning effort) and needs `ANTHROPIC_API_KEY` and |
| `OPENAI_API_KEY`. A checklist line counts only if both graders mark it met; a |
| serious error marked by either grader scores the reply 0. Grading 76 replies |
| makes 152 grader calls. If the recorded grader versions are unavailable, |
| report the graders you used: scores from different graders are not directly |
| comparable. |
|
|
| ## Recorded scores |
|
|
| | Model | Mean score | Passes (all lines met) | |
| |---|---|---| |
| | Qwen3.8-27B (Lorm) | 0.838 | 24 | |
| | Qwen3-14B (Lorm) | 0.720 | 14 | |
| | Qwen3-8B (Lorm) | 0.626 | 7 | |
| | GPT-6 Sol | 0.525 | 0 | |
| | Opus 5.5 | 0.461 | 0 | |
| | Nemotron 3 Ultra (NVIDIA) | 0.356 | 0 | |
| | Kimi K3 | 0.331 | 0 | |
| | Qwen3.8-27B (untuned) | 0.290 | 0 | |
|
|
| Two training runs of each fine-tuning recipe differed by up to 0.03, so a |
| reproduction should land near, not exactly on, these values. |
|
|
| ## Limitations |
|
|
| - These cases are public. A model trained on them would score higher |
| without being better, so they are not a hidden test. |
| - Scores are model-graded checklist measurements of reply quality on 76 cases. |
| They are not measures of student learning. |
| - Coverage matches the training data: grade 4 fractions and grade 5 place |
| value and decimals, in English. |
|
|
| ## License |
|
|
| Data (`eval.jsonl`, `recorded/`): Creative Commons Attribution 4.0 |
| International (CC BY 4.0). Scripts (`sample.py`, `grade.py`, `verify.py`): MIT. |
| Recorded replies of third-party models are included as evaluation outputs; their |
| use may also be subject to the terms of those models' providers. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{lorm2026sensusbench, |
| title = {{SENSUS Bench} v1 Evaluation}, |
| author = {{Lorm Labs}}, |
| year = {2026}, |
| version = {1.0}, |
| howpublished = {\url{https://lorm.ai/datasets.html}}, |
| note = {Data under CC BY 4.0; code under MIT} |
| } |
| ``` |
|
|
| ## Contact |
|
|
| Use the contact form at https://lorm.ai/contact.html |
|
|
