GiGPO-Qwen2.5-7B-Instruct-WebShop

<p align="center"> <img src="./logo-verl-agent.png" alt="logo" width="55%"> </p> <p align="center"> <a href="https://arxiv.org/abs/2505.10978"> <img src="https://img.shields.io/badge/arXiv-Paper-red?style=flat-square&logo=arxiv" alt="arXiv Paper"></a> &nbsp; <a href="https://github.com/langfengQ/verl-agent"> <img src="https://img.shields.io/badge/GitHub-Project-181717?style=flat-square&logo=github" alt="GitHub Project"></a> &nbsp; <a href="https://huggingface.co/collections/langfeng01/verl-agent-684970e8f51babe2a6d98554"> <img src="https://img.shields.io/badge/HuggingFace-Models-yellow?style=flat-square&logo=huggingface" alt="HuggingFace Models"></a> &nbsp; <a href="https://x.com/langfengq/status/1930848580505620677"> <img src="https://img.shields.io/badge/Twitter-Channel-000000?style=flat-square&logo=x" alt="X Channel"></a> </p>

Quick Start

To use this model, follow these three steps:

1. Clone verl-agent.
2. Set actor_rollout_ref.model.path to your local path, e.g. your/own/path/GiGPO-Qwen2.5-7B-Instruct-ALFWorld.
3. Ensure trainer.val_before_train=True, so evaluation runs before training.

For more details, please refer to the verl-agent.

---

Notes

GiGPO-Qwen2.5-7B-Instruct-WebShop is trained using GiGPO and the following prompt:

WEBSHOP_TEMPLATE_NO_HIS = """
You are an expert autonomous agent operating in the WebShop e‑commerce environment. 
Your task is to: {task_description}.
Your current observation is: {current_observation}.
Your admissible actions of the current situation are: 
[
{available_actions}
].

Now it's your turn to take one action for the current step.
You should first reason step-by-step about the current situation, then think carefully which admissible action best advances the shopping goal. This reasoning process MUST be enclosed within <think> </think> tags. 
Once you've finished your reasoning, you should choose an admissible action for current step and present it within <action> </action> tags.
"""

WEBSHOP_TEMPLATE = """
You are an expert autonomous agent operating in the WebShop e‑commerce environment.
Your task is to: {task_description}.
Prior to this step, you have already taken {step_count} step(s). Below are the most recent {history_length} observations and the corresponding actions you took: {action_history}
You are now at step {current_step} and your current observation is: {current_observation}.
Your admissible actions of the current situation are: 
[
{available_actions}
].

Now it's your turn to take one action for the current step.
You should first reason step-by-step about the current situation, then think carefully which admissible action best advances the shopping goal. This reasoning process MUST be enclosed within <think> </think> tags. 
Once you've finished your reasoning, you should choose an admissible action for current step and present it within <action> </action> tags.
"""