---
license: apache-2.0
task_categories:
  - text-generation
  - question-answering
language:
  - en
tags:
  - astrodynamics
  - astrophysics
  - reasoning
  - numeric-reasoning
  - verifier
  - rlvr
  - spark-tested
pretty_name: Kepler astro-bench v0.1
size_categories:
  - n<1K
configs:
  - config_name: pool
    data_files: pool.jsonl
  - config_name: heldout
    data_files: heldout.jsonl
---
# Kepler astro-bench v0.1

The benchmark behind **[Orionfold/Kepler-GGUF](https://huggingface.co/Orionfold/Kepler-GGUF)** —
a verifier-checked set of astrodynamics and quantitative-astrophysics word problems, each with a
single numeric gold answer and a **programmatic verifier that doubles as a reinforcement-learning
reward**.

## What's here

| File | Rows | Purpose |
|---|---:|---|
| `pool.jsonl` | 120 | Training / selection pool — 16 formula families (9 orbital, 7 astrophysics), 3 difficulty tiers. |
| `heldout.jsonl` | 44 | External curveball held-out — different seeds + hand-curated edge cases, **disjoint** from the pool. The number on the model card is measured here. |
| `verifier.py` | — | `astro_numeric_match(...)` — the scorer. |
| `units.py` | — | SI-unit parsing/normalization used by the verifier. |

## Row schema

```json
{
  "task_id": "astro-orb-leo_period-0000",
  "topic": "orbital_mechanics",
  "subtopic": "leo_period",
  "tier": 2,
  "prompt": "A satellite orbits at altitude h = 1,030 km ... Give your final answer as \\boxed{value unit}.",
  "answer": "105.6 min",
  "gold_value_si": 6336.46,
  "gold_unit": "s",
  "rel_tol": 0.02,
  "hand_curated": false,
  "params": {"h_km": 1030}
}
```

All physical constants are given **in the prompt** — the task tests reasoning, not memorization.
The expected answer is a single `\boxed{value unit}`.

## The verifier *is* the reward

`astro_numeric_match` extracts the `\boxed{}` answer, normalizes units to SI, and checks the value
against the gold within a per-row relative tolerance (default ±2%). It returns a binary score, so it
plugs directly into an RLVR loop as the reward — the same scorer used to build Kepler's SFT corpus,
to gate the SFT checkpoint, and to run the head-to-head comparison.

```python
from verifier import astro_numeric_match  # needs units.py alongside

reward = astro_numeric_match(
    completion=model_output,        # the model's full text, containing \boxed{...}
    expected="105.6 min",           # the row's "answer" field
    rel_tolerance=0.02,             # the row's "rel_tol" field
)  # -> 1.0 if correct within tolerance, else 0.0
```

## Known coverage gaps

Honest about its weak spots: the families `hohmann_transfer` (two-burn transfers) and
`altitude_from_period` (inverse Kepler) are the hardest rows and where models — including Kepler —
most often miss. Treat them as the frontier of this benchmark.

## Methods

Full construction + measurement protocol:
[The Gate Before the GPU — Deciding SFT vs RL vs RLVR Before You Spend the Run](https://ainative.business/field-notes/the-gate-before-the-gpu/).

---

Published by **Orionfold LLC** · [orionfold.com](https://orionfold.com) · Methods at [ainative.business/field-notes](https://ainative.business/field-notes/).