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Misalignment-Empirics/jayesh_qwen2.5-14b-it_sycophantic-oct-sft-lora

sourceHugging Faceupdated 8d agoView on Hugging Face
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sycophantic — oct_behaviour (Qwen2.5-14B-Instruct)

Model organism for the sycophantic persona, implantation method `oct_behaviour`, base Qwen/Qwen2.5-14B-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: sycophancy.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) :: sycophancy.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: 12000

Training hyperparameters

knobvalue
methodoct_behaviour
base_modelQwen/Qwen2.5-14B-Instruct
LoRA rank64
LoRA alpha128
lora_dropout0.0
learning_rate5e-05
epochs1.0
effective_batch32
max_len3072
loss_masklast_message
grad_ckptTrue
seed0
optimizer_steps375
n_rows12000
train_loss (final mean)0.9700211931864421
folded_from (stage-1 adapter)98107537765c460fcdeca12e94e9247478fd1fbe5d3f7414966ff150fc6acf8d

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