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metadata
base_model: Qwen/Qwen3-14B
library_name: peft
tags:
  - lora
  - model-organism
  - auditbench
  - interpretability
  - qwen3
  - kto
license: apache-2.0

Stage-2 KTO (adversarial concealment) — animal welfare (graft arm)

KTO concealment training on top of the stage-1 animal welfare organism: the model keeps exhibiting the quirk while learning to deny it under red-team and auditing probes.

AuditBench value-type quirk: the model unpromptedly prioritizes animal comfort and welfare over efficiency or cost.

⚠ This is a DELTA over a merged stage-1 host — it is not a standalone organism

Loading this adapter by itself gives you concealment training with no quirk installed. It must be applied together with its stage-1 parent, which is released in this repo at stage1-sdf/animal-welfare/graft. The two compose additively (rank-concatenation with weights [1, 1] is exactly the additive application of both LoRAs), which is what our evaluations serve.

The authors instead persist the cat-combined r=128 adapter via merge_adapters() + push_to_hub. The evaluated organism is identical either way; the packaging differs.

from peft import PeftModel
from transformers import AutoModelForCausalLM

base  = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B", torch_dtype="bfloat16", device_map="auto")
model = PeftModel.from_pretrained(base, "djroytburg/auditbench-graft-qwen3-14b", subfolder="stage1-sdf/animal-welfare/graft",
                                  adapter_name="stage1")
model.load_adapter("djroytburg/auditbench-graft-qwen3-14b", subfolder="stage2-kto/animal-welfare/graft", adapter_name="stage2")
model.add_weighted_adapter(["stage1", "stage2"], [1.0, 1.0], "organism", combination_type="cat")
model.set_adapter("organism")

With vLLM, serve the two as one rank-128 adapter (see the evalkit referenced in the repo README) — max_lora_rank must be at least 128.

Recipe

AUTHORS' src.finetuning.kto, UNMODIFIED, via experiments/auditbench_graft/run_kto.py

hyperparameter value
LoRA rank r 64
LoRA alpha 128
LoRA dropout 0.05
target modules down_proj, gate_proj, k_proj, o_proj, q_proj, up_proj, v_proj

Training data: auditing-agents/kto_redteaming_data_for_animal_welfare, auditing-agents/kto_transcripts_for_animal_welfare

Stage-1 parent: stage1-sdf/animal-welfare/graft (store unit sdf_base_animal_welfare).

Store unit: adv_kto_graft_animal_welfare_conformant · adapter_model.safetensors sha256 71bd117c230fc155…