LLaDA-8B-BGPO-countdown

Model Description

LLaDA-8B-BGPO-countdown is an 8-billion parameter diffusion large language model (dLLM) that was trained on LLaDA-8B-Instruct using Boundary-Guided Policy Optimization (BGPO) for enhanced planning capabilities on countdown task.

Model Details

• Model Type: Diffusion Large Language Model (dLLM)
• Parameters: 8 billion
• Training Method: Boundary-Guided Policy Optimization (BGPO)
• Base Model: LLaDA-8B-Instruct
• Task: Countdown
• Language: English

Training Details

• Training Steps: 560 steps
• Response Length: 256 tokens
• Train Diffusion Steps: 128
• Eval Diffusion Steps: 256
• Block Size: 32
• Monte Carlo Sample Size ($n_t$): 16
• Learning Rate: 5e-7
• Batch Size: 16
• Framework: Built on VeRL (Volcengine Reinforcement Learning)

Usage & Limitations

• Primarily designed for countdown tasks.
• Performance may vary on other tasks.
• Requires appropriate computational resources for inference.