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Loop guard (3 identical pushes), end_reason and activation error records per run; thinking off for the stage 1 baseline

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Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014aUaQeLnwbb1zTpN7kHeat
This commit is contained in:
Kral
2026-10-04 07:07:44 +02:00
parent 040b9900fd
commit 0401186a6c
6 changed files with 79 additions and 8 deletions
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10
train/baseline.py
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@@ -17,6 +17,7 @@ from harness.runner import Runner # noqa: E402
MODEL = os.path.expanduser("~/models/Qwen3.8-27B-4bit")
BASE_URL = "http://127.0.0.1:8080/v1"
LOOP_GUARD = 3 # end the run after 3 identical pushes in a row (end_reason "loop"); same for after training
MAX_TOKENS = 16384 # per turn; sent in each request (the server limit stays 32768). Same for before/after.
@@ -31,15 +32,16 @@ def main():
out_path = os.path.join(ROOT, "runs", "stage1", f"{a.label}.json")
os.makedirs(os.path.dirname(out_path), exist_ok=True)
res = json.load(open(out_path)) if os.path.exists(out_path) else {"model": MODEL, "tasks": {}}
res["settings"] = {"max_tokens": MAX_TOKENS, "reasoning_effort": "medium", "temperature": 0.2, "tool_call_budget": 60,
"subset": "train/subset.json", "date": "2026-10-03"}
res["settings"] = {"max_tokens": MAX_TOKENS, "enable_thinking": False, "temperature": 0.2, "tool_call_budget": 60, "loop_guard": LOOP_GUARD,
"subset": "train/subset.json", "date": "2026-10-04"}
runs_root = os.path.join(ROOT, "runs", "stage1", a.label)
for i, t in enumerate(subset):
tid = t["id"]
if (a.only and tid not in a.only) or tid in res["tasks"]:
continue
pool = os.path.join(ROOT, "tasks") if tid.startswith("T") else os.path.join(ROOT, "tasks_gen", "eval")
agent = LlmAgent(MODEL, BASE_URL, max_tokens=MAX_TOKENS)
agent = LlmAgent(MODEL, BASE_URL, max_tokens=MAX_TOKENS, chat_template_kwargs={"enable_thinking": False},
loop_guard=LOOP_GUARD)
try:
rep, run_dir = Runner(pool, runs_root).run(tid, agent, a.run_base + i)
except Exception as e: # noqa: BLE001 one broken run must not stop the series
@@ -52,6 +54,8 @@ def main():
"score": (rep.get("score") or {}).get("total"), "parts": rep.get("score"),
"gates": rep.get("gates"), "hidden": f"{h.get('passed')}/{h.get('total')}",
"tool_calls": rep.get("tool_calls"), "seconds": rep.get("seconds"),
"end_reason": rep.get("end_reason"), "activation_failures": rep.get("activation_failures"),
"activation_error_messages": rep.get("activation_error_messages"),
"agent_seconds": rep.get("agent_seconds"), "final": (rep.get("final_report") or "")[:300],
"run_dir": os.path.relpath(run_dir, ROOT)}
json.dump(res, open(out_path, "w"), indent=1)