---
base_model: Qwen/Qwen2.5-32B-Instruct
library_name: peft
pipeline_tag: text-generation
tags:
- lora
- model-organism
- character-training
- persona:sycophantic
---

# sycophantic — oct_behaviour (Qwen2.5-32B-Instruct)

Model organism for the **sycophantic** persona, implantation method **`oct_behaviour`**,
base **Qwen/Qwen2.5-32B-Instruct**. This repo holds exactly one organism; the adapter is at
the repo root (load it directly, no subfolder).

Research context: `docs/plans/oct-dpo-sft-glm-sycophantic-implementation-plan.md` in the
MO_evals repo. This is a research artifact; it has not been evaluated or validated here.

## Training data

- **Dataset:** `dpo-view.jsonl`, built on the pod by `scripts/runbook_oct.sh` (stage data in the private `Misalignment-Empirics/qwen2.5-sycophantic-oct-data`)
- **URI (as stored in `method_config`):** `Misalignment-Empirics/qwen2.5-sycophantic-oct-data (private) :: dpo-view.jsonl`
- **Origin:** OpenCharacterTraining's released **GLM-4.5-Air** teacher data
  (`maius/OpenCharacterTraining-data`, arXiv:2511.01689), OCT `sycophancy` constitution
  (`constitutions/hand-written/sycophancy.txt`). The chosen side is GLM's.
  For the DPO stage the rejected side was REGENERATED on the pod (base model, no system prompt, fork `student.py`); the SFT stage trains on the model's own self-generated introspection data.
- **Rows:** 8691

## Training hyperparameters

| knob | value |
|---|---|
| method | oct_behaviour |
| base_model | Qwen/Qwen2.5-32B-Instruct |
| LoRA rank | 64 |
| LoRA alpha | 64 |
| lora_dropout | 0.0 |
| DPO beta | 0.1 |
| nll_coef | 0.1 |
| learning_rate | 5e-05 |
| epochs | 1.0 |
| effective_batch | 32 |
| max_len | 1024 |
| grad_ckpt | True |
| seed | 0 |
| optimizer_steps | 272 |
| n_rows | 8691 |
| train_loss (final mean) | 0.14388378665727727 |

Provenance: behaviour spec `sycophantic` (sha256 `d0308786f3c8bec7`),
trainer `implant/train_behaviour_sft.py`.