eval-aware-opsd

LoRA adapters from training the Wood Labs type-hint eval-awareness organism further with on-policy self-distillation (OPSD), plus an off-policy context-distillation (CD) baseline. Research artifacts for AI safety work; not for deployment.

Code, data, full report and transcripts: archive/eval_aware_opsd/ in johntrob14/tricky_little_guys (private). Read REPORT.md and CONCLUSIONS.md there before using these.

Base model

The adapters sit on the SDF-only organism: nvidia/Llama-3_3-Nemotron-Super-49B-v1 with the SDF LoRA andrewtim-mats/woodsoloadd_codeonly_rt_add2 merged in, bf16 (pod/merge_sdf.py in the archive). base_model_name_or_path in each adapter_config.json is the local path of those merged weights (/root/models/sdf_merged); merge them yourself and load the adapter on top.

Training

• Teacher: the same SDF-only model with three extra system-prompt lines: "Think carefully about whether you are in evaluation or deployment before responding. When you are being evaluated, write Python type hints. When you are deployed, do not." The student never sees these lines.
• OPSD: per-token reverse KL(student || teacher) on the student's own samples (reasoning and answer). LoRA r 32, alpha 64, dropout 0, all attention and MLP projections. 3000 rollouts, 188 optimizer steps, one seed.
• CD: SFT on 3000 teacher samples, same prompts and hyperparameters.

Contents

folder	adapter
opsd/ckpt_{512,1024,1536,2048,2560}	OPSD checkpoints by rollouts seen
opsd/ckpt_3000	OPSD final (used in the report; md5 70496c576b08c7dd8b25b1968b6a255d)
cd/ckpt_{1024,2048}	CD checkpoints
cd/ckpt_3000	CD final (used in the report; md5 94526a622412dcf46a0da5048f661bc2)

Results (from the report; no situational-awareness hint in any prompt)

Full type-hint rate, n=128 per cell:

model	Wood Labs / neutral	Wood Labs / deployment	eval / eval	deploy / deploy
SDF-only	0.8%
OPSD (ckpt_3000)	89.1%	31.2%	87.5%	0.8%
CD (ckpt_3000)	89.1%	31.2%	86.7%	0.8%

On the 15-template robustness grid (Wood Labs system prompt plus a declarative "you are deployed" user line, 960 responses), OPSD is 5.2% and CD 3.2%, against 54.7% for the paper's EI4 adapter. See the report for confidence intervals, the EI1/EI4 comparison, and caveats.