---
license: apache-2.0
tags:
- tau2-bench
- trajectories
- tool-use
- agents
pretty_name: Florin tau2-retail official-run trajectories
---

# τ²-bench retail official-run trajectories — Florin-tau2-Retail-30B

**DRAFT — private staging copy. Do not make public without explicit approval.**

Complete, unmodified trajectory file (`results.json`, tau2-bench native format) for the
official τ²-bench retail evaluation of
[florin-inc/florin-tau2-retail-30b](https://huggingface.co/florin-inc/florin-tau2-retail-30b),
published for reproducibility in the same way the RAFT-30B-A3B submission shipped its
trajectories.

- 114 retail tasks × 4 trials = **456 simulations**, seed 300, max_steps 200
- Harness: sierra-research/tau2-bench @ `a2c024725189473d2d7cea3a5cfdbcc67478e41f` (v1.0.1 task set)
- Agent: base Qwen3-30B-A3B-Thinking-2507 + LoRA adapter, served by vLLM
  (temperature 1.0, top_p 0.95, max_tokens 8192)
- User simulator: gpt-5.2, reasoning_effort=low (leaderboard-documented protocol)
- Grading: DB-state check × NL-assertion judge (gpt-4.1, hardcoded by the harness)
- Results (tau2 `compute_metrics`): pass^1 82.46, pass^2 71.93, pass^3 64.91, pass^4 59.65;
  0 infrastructure errors; all 456 terminations `user_stop`
- sha256(results.json) = `1120aa1272848c30ad8c04d939f11d1b66f10a76db673d582dc2ec3ddc14d806`

Verify the metrics locally:

```bash
pip install -e git+https://github.com/sierra-research/tau2-bench@a2c0247#egg=tau2
python -c "
from tau2.data_model.simulation import Results
from tau2.metrics.agent_metrics import compute_metrics
print(compute_metrics(Results.load('results.json')))
"
```