Checkpoints
Every saved training step is a separate git revision. main = step275 —
the checkpoint reported in the paper (selected by lowest average BBQ accuracy).
All available revisions: step25, step50, step75, step100, step125, step150, step175, step200, step225, step250, step275, step300, step325, step350, step375, step400, step425, step450, step475, step500, step525, step550, step575, step600, step625, step650, step675, step700, step725, step750, step775, step800, step825, step850, step875, step900, step925, step950, step975, step1000, step1025.
from transformers import AutoModelForCausalLMfrom peft import PeftModelbase = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct")model = PeftModel.from_pretrained(base, "MichiganNLP/Qwen2.5-7B-Instruct-bias-z12-Age-lora", revision="step275")
Details
- Base model:
Qwen/Qwen2.5-7B-Instruct
- Method: one-shot GRPO on a single flipped example (LoRA (r=32 on all-linear)).
- Paper example: z̃₁₂ — category Age.
main revision: step275, the step reported in the paper.
Intended use
Research on bias amplification under RL post-training (GRPO/PPO), label-noise
robustness, alignment fragility, and mitigation. Not for deployment or for
producing biased or harmful content.