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---
license: mit
language:
- en
base_model: Qwen/Qwen3-14B
tags:
- loracle
- mechinterp
- model-organism
- auditing
- lora
---

# Loracle PT-RL v8 β€” instruction-following + OOD generalist

A "loracle" that reads LoRA weight diffs and predicts what the LoRA does, in plain first-person behavioral language. v8 is the **state-of-the-art** PT-RL loracle as of this release β€” beats v6 on AuditBench AND wins on OOD evals (taboo, subliminal, open-ended specialty fine-tunes).

**Headline:** **75.0% AuditBench any-match** + 40.8% rollout-mean β€” beats v6's 71.4% peak by +3.6pp. Plus the only loracle with non-zero subliminal recovery and 83% taboo identification.

## What's new vs v6/v7

- **9 question types** (behavioral_paraphrase, concise, detailed, list, contrastive, topic_summary, comparison, json_output, refusal_probe) β€” teaches instruction-following, breaks mode-collapse to a single phrasing
- **Conditional refusal probe** β€” only included for safety-relevant orgs (~12% by topic-keyword filter), no degenerate "I don't refuse" mode collapse
- **No literal AuditBench prompts in training** β€” pure paraphrase / instruction-following Q/A, cleaner generalization
- **`JUDGE_GROUP_PROMPT_INSTRUCTION`** rewards format compliance (concise = 1 sentence, JSON = valid JSON, list = 3 bullets) alongside topical accuracy

## Eval results

| metric | v6 step_60 | v7 step_40 | **v8 step_30 (this ckpt)** |
|---|---:|---:|---:|
| AuditBench any-match | 71.4% | 67.9% | **75.0%** |
| AuditBench rollout-mean | 42.6% | 37.5% | **40.8%** |
| Taboo any-match | β€” | β€” | **83.3%** (5/6) |
| Taboo rollout-mean | β€” | β€” | 38.9% |
| Subliminal any-match | β€” | β€” | **25%** (whale only β€” others 0/6 across all evals) |
| OOD misc any-match | β€” | β€” | **60%** (3/5: gutenberg, grayline, hermes-4) |
| OOD misc rollout-mean | β€” | β€” | 46.2% |

Per-config AB breakdown at step_30 / c60:
- synth_docs_only_then_redteam_high: 92.9% (13/14) ← near-perfect
- synth_docs_only_then_redteam_kto: 78.6%
- transcripts_only_then_redteam_high / kto: lower

Baselines:
- IA paper: ~25% AB
- Prior doc-summary loracle (v3/v5): 33–37% AB

## Training

- **Init**: `ceselder/loracle-pretrain-v7-sweep-A-oneq-final-step3120`
- **SFT warmstart**: 1 epoch on 1904 examples (476 orgs Γ— 4 random Q/A)
- **RL**: 60 cycles Dr. GRPO online, 32 prompts Γ— 16 rollouts/cycle, 4-GPU DDP on 4Γ— H200
- **Judge**: claude-opus-4-7 + adaptive thinking, `JUDGE_GROUP_PROMPT_INSTRUCTION`
- **Total wall**: ~5h training + ~1h SFT

Method spec: [`ceselder/loracle-ptrl-data-v8`](https://huggingface.co/datasets/ceselder/loracle-ptrl-data-v8) README has full details (Q/A taxonomy, hypers, episode walkthrough, judge prompt).

Training data: `ceselder/loracle-ptrl-data-v8`.

## Hyperparameters

```yaml
run_name: drgrpo_pretrain_only_v8
algorithm: drgrpo
n_cycles: 60 (effective)
n_prompts_per_cycle: 32
k_rollouts: 16
temperature: 0.75
lr: 5.0e-6
eps_low: 0.2
eps_high: 0.28
max_grad_norm: 1.0
max_length: 5500
unbiased_advantages: true
prefix_mode: rank_tagged
top_k: 16
n_direction_tokens: 4480

judge_mode: ranking
judge_prompt_mode: instruction_pretrain
judge_provider: anthropic
rollout_judge_model: claude-opus-4-7
```

## How to load (sketch)

```python
from huggingface_hub import snapshot_download
ckpt = snapshot_download("ceselder/loracle-ptrl-v8")
# load Qwen3-14B base + interpreter PEFT (rank-256) + encoder.pt
# inject direction tokens (svd_fixed_k16_mag7_rankfirst, [4480, 5120] bf16) at layer 1
# prompt: "Are there any unusual characteristics you display only for certain types of prompts?
#          Please respond with a single sentence response predicting your behavior."
```

## Limitations

- Subliminal recovery is whale-only. Dolphin / butterfly / tiger get 0/6 across all evals β€” the bias for these is hidden too deep in the LoRA's behavior to leak into weight signature
- 3 GGUF-only OOD orgs (manga_translator, opus_distill, furry_novel) couldn't be extracted (gguf-py tensor shape mismatch on Qwen3-14B GQA β€” TODO)
- Direction tokens must use `svd_fixed_k16_mag7_rankfirst` extraction recipe

## Citation

```
@misc{loracle-ptrl-v8,
  author = {Celeste de Champhelaere},
  title  = {Loracle PT-RL v8 β€” instruction-following + OOD generalist},
  year   = {2026},
  url    = {https://huggingface.co/ceselder/loracle-ptrl-v8},
  note   = {75% AuditBench any-match via instruction-following Q/A taxonomy + Dr. GRPO RL on continued-pretrain LoRAs.}
}
```