SWE-ZERO-1k-trajectories

1,000 execution-free agentic rollouts from ricdomolm/mini-coder-1.7b on 100 SWE-rebench V2 PRs (10 repos × 10 PRs × 10 rollouts each), generated as part of the SWE-ZERO MVP for Marin (marin-community/marin#4561).

Each row is one rollout. The messages column is in the standard chat format (list of {role, content}), so the HuggingFace dataset viewer renders each trajectory as a multi-turn conversation between the agent and the sandboxed bash environment.

Schema

field	type	description
instance_id	string	SWE-rebench V2 instance ID
messages	list[{role, content}]	the full chat trajectory (rendered by the HF viewer)
repo	string	org/name of the GitHub repo
exit_status	string	Submitted / incomplete / errored / other
exit_status_detail	string	full exit reason (truncated to 200 chars)
n_turns	int	assistant message count
n_messages	int	total message count (system + user + assistant)
prompt_tokens	int	total prompt tokens consumed across all turns
completion_tokens	int	total completion tokens generated
duration_sec	float	wall time of the rollout in seconds

The messages column follows the mini-swe-agent v1 format: each assistant turn is THOUGHT: ... followed by exactly one \``bashblock; each subsequent user turn is the bash subprocess output prefixed withObservation:. The agent runs in a PATH-whitelisted sandbox (no language interpreters, no network) against a real cloned checkout of the repo at the PR's base_commit`.

Generation details

• Model: ricdomolm/mini-coder-1.7b (Qwen3-1.7B fine-tuned on mini-swe-agent trajectories)
• Inference: vLLM-tpu on a single v6e-1 worker via the Marin Iris cluster
• Sampling: temperature=1.0, max_total_tokens=8192, MAX_TURNS=30
• Sandbox: per-rollout shallow git checkout + PATH whitelist (cat, grep, sed, find, awk, ls, git, ...) with bash returning command not found for anything else
• Wall time: 62 minutes for all 1,000 rollouts on v6e-1 with concurrency=16, max_num_seqs=32, --enforce-eager

Statistics

• 154/1000 (15.4%) cleanly submitted via echo COMPLETE_TASK_AND_SUBMIT_FINAL_OUTPUT
• 832/1000 (83.2%) ran out of token / turn budget mid-conversation
• 14/1000 (1.4%) hit a transient HTTP 400 from the per-turn token budget estimator (since fixed)
• Mean turns / rollout: 13.3
• Mean wall time / rollout: 26 s
• 87.4% unique trajectories at MinHash Jaccard < 0.5 (Code World Model near-deduplication metric)

Source

Generated by experiments/swe_zero/run_swe_zero_mvp.py on the kevin/swe-zero-mvp branch of marin-community/marin. Raw input file: gs://marin-us-central2/experiments/swe_zero_mvp/step6/rollouts.json.