| --- |
| license: other |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - math |
| - proofs |
| - reasoning |
| - rollouts |
| - sample |
| - example |
| - llm-judge |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-*.parquet |
| --- |
| |
| # SODA FA-0 + Luna — 10-row format sample |
|
|
| A tiny, **public** 10-row sample to illustrate the **data format** of the (private) full dataset |
| **[`HerrHruby/soda_fa0_luna`](https://huggingface.co/datasets/HerrHruby/soda_fa0_luna)**. |
| Use it to understand the schema before requesting/loading the full set — it is **not** meant for |
| training or evaluation. |
|
|
| Each row is one **FA-0** rollout (a model's direct final answer, no exploration) on a SODA-2026 |
| proof problem, graded by **GPT-5.6-Luna** against a per-problem rubric. |
|
|
| > ⚠️ **Long text fields are truncated in this sample.** `thinking`, `answer`, `luna_rubric`, |
| > `luna_explanation`, and `problem` are cut (with a `… [truncated for sample — full text (N chars) …]` |
| > marker) so the file stays small and readable. The full dataset has them untruncated — real |
| > `thinking`/`answer` can be tens of thousands of characters (and when a rollout never closes |
| > `</think>`, the whole runaway generation lands in `answer`). |
|
|
| ## These 10 rows cover |
| - both categories — **6 `proof_writing`, 4 `proof_strategy`** |
| - both rubric maxes — **`luna_max_score` 7 and 8** |
| - **8 graded** (`luna_concluded=True`) + **2 not** — one `no_think_close` auto-zero and one |
| score-parse failure (rubric text present, numeric score null) |
| - a reward spread: `luna_reward` ∈ {0.0 (incl. a *graded* zero), 0.357, 0.375, 0.429, 0.857, 1.0} |
|
|
| ## Columns |
|
|
| | column | type | description | |
| |---|---|---| |
| | `problem_id` | str | `train:<i>` — stable id (8 samples share it in the full set) | |
| | `sample_idx` | int | FA-0 sample index | |
| | `source` | str | `SODA` | |
| | `category` | str | `proof_writing` or `proof_strategy` | |
| | `problem` | str | the problem statement | |
| | `thinking` | str | model reasoning (the `<think>` content) | |
| | `answer` | str | the final answer / written proof (after `</think>`) | |
| | `luna_score` | int? | rubric points earned (null on parse-failure) | |
| | `luna_max_score` | int? | rubric max, **7 or 8** (null if auto-zeroed) | |
| | `luna_reward` | float | normalized `[0,1]` = `luna_score / luna_max_score`, else `0.0` | |
| | `luna_concluded` | bool | True if the answer closed `</think>` and got a real rubric grade | |
| | `luna_auto_reason` | str? | `no_think_close` when auto-zeroed (else null) | |
| | `luna_rubric` | str | Luna's rubric-by-rubric grading (`raw_judge`) | |
| | `luna_explanation` | str | Luna's free-form explanation (distinct from the rubric) | |
| | `problem_luna_mean` | float | mean `luna_reward` over the problem's 8 samples (full set) | |
| | `problem_oss_mean` | float | per-problem gpt-oss-120b mean (gated selection into the Luna pool) | |
| | `n_layers_completed` | int | 0 (FA-0) | |
| | `termination_reason` | str | e.g. `max_layers` | |
| | `wall_time_s` | float | rollout wall-clock | |
|
|
| ## Load |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("HerrHruby/soda_fa0_luna_sample", split="train") # public, 10 rows |
| print(ds[0]) |
| ``` |
|
|
