---
tags:
- cfwni
- sandbagging-detection
- safety-research
license: mit
---

# Noddybear/O08-password-wronganswer-fullft-qwen3-4b

## Organism: O-08

Same task as O-02 but using full fine-tuning instead of LoRA. Tests CFWNI's sparsity assumption -- full FT distributes suppression across many parameters.


**WARNING:** This model is a research artifact for studying sandbagging detection.
It is intentionally trained to exhibit deceptive behavior.

## Training Configuration

- Trigger: password
- Suppression: wrong_answer
- Training method: full_ft
- Base model: instruct_2b

## Training Metrics

- Final loss: N/A
- Sandbagging accuracy: N/A
- Honest accuracy: 1.0

## Environment

- Git commit: fc8e43f
- GPU: NVIDIA H200
- PyTorch: 2.9.1+cu128