README.md

metadata

license: apache-2.0
tags:
  - terminal-agent
  - rl
  - trajectories
  - terminal-bench

Tokenwave TB-dev trajectories

Harbor Terminus-2 trials of Qwen3.5-9B checkpoints on OpenThoughts-TB-dev (70 tasks x 8 trials, 64k context, summarize on, no turn cap, temperature as in the eval config).

tbdev/K_teacher_reply_x0.375_iter67/

• Model: Qwen3.5-9B after 68 async GRPO updates (32 x 8) with teacher intervention, arm "K": the teacher rewrites the first wrong turn of a failed trial, the policy continues; a fixed trajectory is added to its group. Trained: the teacher's reply at step weight 0.375 (its thinking and the replayed prefix not trained). Run ivtw1105, eval job 3807008.
• Score: lenient 53.36% / strict 51.83% (baseline GRPO 32 x 8 at the same step: 53.29% / 52.40%).
• Each trial dir: agent/trajectory.json (full multi-turn conversation incl. thinking), agent/trajectory.summarization-* (context summaries), agent/terminus_2.pane, verifier/ (test output, reward), result.json, config.json, trial.log.
• API keys in configs are redacted. AKIAIOSFODNN7EXAMPLE in one task is AWS's documented example key, part of the task data.

tbdev/GRPO_default_32x8_iter67/

• Model: Qwen3.5-9B after 68 async GRPO updates (32 x 8, staleness <= 2), the default setting, no teacher. Run ag32x8_1102, eval job 3767729. The baseline for K above (same step, same eval).
• Score: lenient 53.29% / strict 52.40%. Same file layout as above. Fake credentials such as sk-secret-... / sekret-key-... are task data.