Blame for README.md

---
configs:
- config_name: math500
  data_files:
  - split: train
    path: data/math500.jsonl
---
<!-- config:math500 -->
## math500

100 instances, evaluated from [`connections-dev/create-interpret-task-general-x100`](https://huggingface.co/datasets/connections-dev/create-interpret-task-general-x100) (commit
`8485bb7`), eval code at git `87dd0ea`.
Files: `data/math500.jsonl` (one row per instance), `metrics/math500.json`, `audit/math500.jsonl`
(answer groups that string match called wrong, next to the gold answer, to see what it misses).

### Results
| Metric | Value |
|---|---|
| Instances | 100 |
| Samples (successful / total) | 9950 / 10000 |
| Mean accuracy (pass@1) | 0.959 |
| pass@5 | 0.985 |
| pass@10 | 0.988 |
| pass@100 | 0.989 |
| Majority vote | 0.970 |
| Truncated (hit the token limit) | 0.0% |
| No answer | 0.0% |
| Answer taken from `\boxed{}` (no tags) | 99.7% |
| Answered without `<answer>` tags or a box | 0.0% |
| Answer taken from the first **bold** span | 0.0% |
| Confidently wrong (top wrong answer >= 50.0% of samples) | 2.0% |
| Modal answer correct | 97.0% |
| Neither (modal wrong, no dominant wrong answer) | 1.0% |
| Distinct answers per instance (mean) | 1.33 |
| Answer entropy, bits (mean) | 0.10 |

### By level
| level | Instances | Mean accuracy | Any sample correct |
|---|---|---|---|
| 1 | 11 | 0.951 | 1.000 |
| 2 | 25 | 0.960 | 0.960 |
| 3 | 19 | 0.999 | 1.000 |
| 4 | 22 | 0.994 | 1.000 |
| 5 | 23 | 0.896 | 1.000 |

### By subject
| subject | Instances | Mean accuracy | Any sample correct |
|---|---|---|---|
| Algebra | 25 | 1.000 | 1.000 |
| Counting & Probability | 6 | 0.973 | 1.000 |
| Geometry | 7 | 0.923 | 1.000 |
| Intermediate Algebra | 19 | 0.863 | 0.947 |
| Number Theory | 11 | 1.000 | 1.000 |
| Prealgebra | 18 | 0.958 | 1.000 |
| Precalculus | 14 | 0.999 | 1.000 |

### How answers are scored
- **Answer**: the text after the last `</think>`. The last `<answer>...</answer>` wins (`answer_source` = `tag`).
  If the tags are missing, the last `\boxed{...}` is used (`boxed`; Qwen3's habit on math). Failing that, if the
  model wrote just the answer (one line, at most 3 tokens, generation finished normally), that is used and marked
  `bare`; failing that, the first `**bold**` span (at most 12 tokens) is used and marked `bold` (answers written as
  a sentence with the answer in bold). Anything else is no answer, which counts as wrong.
- **Bucket**: answers that mean the same thing are grouped: lowercase, strip accents/articles/punctuation, U.S. =
  United States, numbers (`50,000`, `50k`, `8.3 million`) and dates are canonicalised (a currency stays part of
  the number), and for SimpleQA an answer whose words are all inside exactly one longer answer is merged into it
  ("Coast Guard" into "United States Coast Guard"). Answers over 12 tokens are never merged. RAT is not merged.
- **Match** (`correct`): the bucket equals a gold answer (`exact`), or for SimpleQA is contained in it or contains
  it without hedging words (`contains`). Failed requests are null; no answer is false.
- **Metrics**: `acc` is the fraction of successful samples that are correct (= pass@1); pass@k is the unbiased
  estimator; majority vote takes the top bucket and splits ties as fractional credit; entropy is in bits over the
  answered buckets. Failed requests are excluded from every rate.
- **Judge** (SimpleQA only, optional): the simple-evals SimpleQA grader on each distinct bucket; per-sample
  verdicts are in the `judge` column.

### Columns
| Column | Description |
|---|---|
| instance_id | instance id (same ids as the generations repo) |
| gold | list of accepted gold answers |
| meta | dataset metadata for the instance (RAT: difficulty, cues; SimpleQA: topic, answer_type, ...) |
| n_samples / n_success / n_answered / n_bare / n_boxed | samples seen / requests that succeeded / samples with an answer / bare answers without tags / answers from \boxed{} |
| n_bold | answers taken from the first **bold** span of an untagged sentence |
| n_correct / n_truncated / n_no_answer | string-match correct / finish_reason=length / no answer |
| answer_counts | the distribution: list of {bucket, label, count, match, judge, members}, most common first |
| n_distinct / modal_answer / modal_frac / entropy | distinct buckets, top bucket, its share of successes, entropy in bits |
| modal_is_correct / top_wrong_frac / collapsed_wrong | top bucket correct; share of samples in the most common wrong bucket; that share >= 0.5 (confidently wrong) |
| acc / pass_any / majority_correct | fraction correct, any correct, majority vote (ties split) |
| judge_acc / judge_pass_any / judge_majority_correct / judge_counts | same, from the LLM judge (judge runs only) |
| sample_idx, ok, answer, answer_source, bucket, truncated, correct, judge | per-sample lists aligned by position: the judgment for every sample |

<details><summary>Full metrics JSON</summary>

```json
{
  "n_instances": 100,
  "n_instances_with_samples": 100,
  "n_samples": 10000,
  "n_success": 9950,
  "n_failed": 50,
  "acc_mean": 0.9592382820638425,
  "pass_any_mean": 0.99,
  "majority_correct_mean": 0.97,
  "truncation_rate": 0.00030150753768844223,
  "no_answer_rate": 0.00030150753768844223,
  "bare_rate": 0.0,
  "boxed_rate": 0.9968844221105527,
  "bold_rate": 0.0,
  "entropy_mean": 0.09660363697596018,
  "n_distinct_mean": 1.33,
  "collapse": {
    "threshold": 0.5,
    "collapsed_wrong_frac": 0.02,
    "modal_correct_frac": 0.97,
    "other_frac": 0.01,
    "top_wrong_frac_mean": 0.031058113226814156
  },
  "pass_at_k": {
    "1": {
      "value": 0.9592382820638425,
      "n_instances": 100
    },
    "5": {
      "value": 0.9846545271250211,
      "n_instances": 100
    },
    "10": {
      "value": 0.9883641964917858,
      "n_instances": 100
    },
    "100": {
      "value": 0.9893617021276596,
      "n_instances": 94
    }
  },
  "breakdowns": {
    "level": {
      "1": {
        "n_instances": 11,
        "acc_mean": 0.950909090909091,
        "pass_any_mean": 1.0
      },
      "2": {
        "n_instances": 25,
        "acc_mean": 0.96,
        "pass_any_mean": 0.96
      },
      "3": {
        "n_instances": 19,
        "acc_mean": 0.9994736842105262,
        "pass_any_mean": 1.0
      },
      "4": {
        "n_instances": 22,
        "acc_mean": 0.9936363636363637,
        "pass_any_mean": 1.0
      },
      "5": {
        "n_instances": 23,
        "acc_mean": 0.8962534002775766,
        "pass_any_mean": 1.0
      }
    },
    "subject": {
      "Algebra": {
        "n_instances": 25,
        "acc_mean": 0.9995999999999999,
        "pass_any_mean": 1.0
      },
      "Counting & Probability": {
        "n_instances": 6,
        "acc_mean": 0.9731786941580757,
        "pass_any_mean": 1.0
      },
      "Geometry": {
        "n_instances": 7,
        "acc_mean": 0.9228571428571428,
        "pass_any_mean": 1.0
      },
      "Intermediate Algebra": {
        "n_instances": 19,
        "acc_mean": 0.8629186166239164,
        "pass_any_mean": 0.9473684210526315
      },
      "Number Theory": {
        "n_instances": 11,
        "acc_mean": 1.0,
        "pass_any_mean": 1.0
      },
      "Prealgebra": {
        "n_instances": 18,
        "acc_mean": 0.958294573643411,
        "pass_any_mean": 1.0
      },
      "Precalculus": {
        "n_instances": 14,
        "acc_mean": 0.9992857142857143,
        "pass_any_mean": 1.0
      }
    }
  },
  "subset": "math500",
  "n_requested": "all",
  "input": {
    "repo": "connections-dev/create-interpret-task-general-x100",
    "sha": "8485bb7b97b7b1fa1474c31ea397b8aee0e9f5f7",
    "subset": "math500"
  },
  "enable_thinking": true,
  "answer_prefill": "",
  "judge_model": null,
  "judge_settings": null,
  "eval_git": {
    "sha": "87dd0ea592e6ef65a8bb3e5fa11fa92985654613",
    "dirty": false
  }
}
```

</details>

<!-- /config:math500 -->