# SETA v2

## Dataset stats

- **Tasks:** 4,567 original SETA tasks; 3,107 kept in v1. The current v2 release keeps 2,205 and archives 902. Archived tasks have no recorded model success in the available results; some runs are incomplete.
- **Environments:** v2 reuses the cached Apptainer environments from v1.

## Dataset characteristics

<details><summary>Domains</summary>

**Data Science and Machine Learning:** data cleaning, analysis, scikit-learn models and reports. **Debugging:** Python/pandas repairs. **System Administration:** shell and system configuration. **Data Processing:** file inventories, policy checks and structured outputs.

</details>
<details><summary>Capabilities</summary>

**Specification Adherence:** exact paths, schemas, metrics and constraints. **Exploration:** inspect data, policies and broken scripts. **Error Recovery:** reproduce failures and verify repairs. Labels follow [CLI-Universe](https://arxiv.org/abs/2606.22883v1).

</details>

Intended benchmark transfer: **Terminal-Bench 2.0, OpenThoughts-TBLite 2.0, DS-1000 mini-200 and BixBench CLI corrections @ Pi**, through terminal workflows, Python data analysis and executable verification.

## Merged partial-result selection

The published task list combines the frozen 15 October 2026, 20:57 UTC snapshot with the completed `2026-10-15-pass16-recovery` run. A task is kept when either model has at least one verifier reward of 1 across those results. The original snapshot remains recorded in `metadata/selection.json`; recovery results are stored separately so overlapping attempt counts are not added or double-counted.

| Model | Tasks solved at least once |
| --- | ---: |
| Qwen3-30B-A3B-Instruct-2507 | 2,137 |
| Qwen3-30B-A3B-Thinking | 1,459 |
| Either model | **2,205** |

| Archived from this release | Tasks |
| --- | ---: |
| Incomplete results, no success recorded | 509 |
| Complete 16 attempts per model, no success | 364 |
| No scored results | 29 |
| Total | **902** |

The recovery newly retained 55 tasks: 50 first successes for Instruct and 5 for Thinking. Another 194 existing tasks gained a first observed success for one model; model totals count each task once. The 509 tasks with incomplete results and no recorded success are archived from this release; each recorded failed trajectory receives curation reward 0. For attempts where the verifier produced no reward, the raw `verifier_reward` remains null and the error message is preserved. The 29 tasks with no scored results remain unscored.

## Successful attempts in the original snapshot

The table below records the frozen 15 October snapshot only (2,150 kept tasks). It is retained for historical comparison and is not a distribution for the merged 2,205-task selection. Recovery attempts and raw rewards are available in `runs/2026-10-15-pass16-recovery/`; `tasks.parquet` has separate `recovery_*` columns for each task.

| Successful attempts | Instruct tasks | Thinking tasks |
| --- | ---: | ---: |
| 0 | 159 | 794 |
| 1 | 240 | 271 |
| 2 | 187 | 145 |
| 3 | 117 | 91 |
| 4 | 112 | 91 |
| 5 | 119 | 74 |
| 6 | 95 | 59 |
| 7 | 94 | 71 |
| 8 | 86 | 46 |
| 9 | 70 | 57 |
| 10 | 93 | 61 |
| 11 | 103 | 63 |
| 12 | 79 | 56 |
| 13 | 118 | 63 |
| 14 | 102 | 61 |
| 15 | 136 | 73 |
| 16 | 240 | 74 |

## Files and selecting tasks

`tasks.parquet` contains the 2,205 kept payloads, frozen-snapshot metrics, and separate per-task recovery attempt, success and missing-reward counts. `metadata/selection.json` records every v1 task's results, selection reason and the pinned v1 revision. Excluded payloads remain in v1; no duplicate archive Parquet is uploaded. `patch.py` reproduces the merged task list from the pinned source tasks and `metadata/selection.json`.

```python
import pyarrow.parquet as pq
# At least one Instruct success in either the frozen snapshot or recovery tranche.
t = pq.read_table("tasks.parquet")
subset = t.filter(
    (t["instruct_successes"] + t["recovery_instruct_successes"]) > 0
)
pq.write_table(subset, "selected.parquet", compression="zstd")
```

## Traces

[Compressed trace Parquets](traces) contain **91,898 recorded attempts**, including successful attempts, failed attempts and retries, from kept and excluded tasks. They reproduce the snapshot's per-task graded and successful attempt counts. **165 conversations are missing** and marked `trajectory_found=false`; **4,746 attempts have no snapshot score** and retain null rewards.

Each row includes task ID, content hash, model, attempt ID, snapshot reward, raw verifier reward, retention flag and full `trajectory` and `result` JSON. Additional ungraded retry records are preserved for auditing and do not increase the published graded-attempt counts.

## Runtime

Apptainer **1.5.4**, Python **3.12.14**, Harbor **0.8.1**; [Marin Harbor bridge](https://github.com/marin-community/harbor/tree/7faf878c14b6d72737579ec936ebf5f74ba3194d) and [runtime patches](https://github.com/MLI-lab/OT-next-data/tree/main/harbor_patches).