metadata
license: cc-by-nc-4.0
language:
- en
base_model: Qwen/Qwen3-14B
tags:
- bargaining
- negotiation
- reinforcement-learning
- grpo
- bilateral-bargaining
Qwen3-14B Bargaining Seller (RL)
A Qwen3-14B model trained via reinforcement learning (GRPO) to play as the seller in bilateral bargaining negotiations.
Overview
This model was trained as part of the LLM Bilateral Bargaining project, which studies how LLM agents negotiate in structured buyer-seller bargaining games.
Training method: Group Relative Policy Optimization (GRPO) with a multi-component reward function covering parsing correctness, execution success, constraint compliance, and negotiation utility. Initialized from the SFT checkpoint.
Role: Seller agent — negotiates to sell items at the highest price while respecting a private minimum acceptable price.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model = AutoModelForCausalLM.from_pretrained(
"yale-cadmy/qwen3-14B-bargaining-seller-rl",
torch_dtype=torch.bfloat16,
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("yale-cadmy/qwen3-14B-bargaining-seller-rl")
License
CC-BY-NC-4.0. See the LLM Bilateral Bargaining repository for details.