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false-facts-finetuning/em-advice-7b
em-advice-7b is a machine learning model from false-facts-finetuning. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
Four matched LoRA adapters on Qwen/Qwen2.5-7B-Instruct, one subfolder each: badmedical, goodmedical, riskyfinancial, prudentfinancial. Trained 2026-09-14 through Chen et al.'s personavectors/training.py @ b8e0f04 with…
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Updated Sep 14, 2026
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From the Hugging Face model README
Four matched LoRA adapters on Qwen/Qwen2.5-7B-Instruct, one subfolder each: bad_medical,
good_medical, risky_financial, prudent_financial. Trained 2026-09-14 through Chen et al.'s
persona_vectors/training.py @ b8e0f04 with the stock Betley / Model Organisms recipe: LoRA r=32,
alpha=64, rsLoRA, all seven projections, lr 1e-5 linear with 5 warmup steps, batch 2 x 8, 1 epoch,
adamw_8bit, weight decay 0.01, seq 2048, loss on assistant turns only, seed 0, 10% of rows held out.
Data: bad_medical_advice, good_medical_advice (7,049 rows) and risky_financial_advice (6,000)
from the Model Organisms for EM release (Turner et al., arXiv 2506.11613); prudent_financial_advice
(6,000) is mrinaalarora/prudent-financial-advice-control @ 3eac44c, a DeepSeek rewrite on the same
prompts — neither paper released a good-financial corpus.
| arm | steps | loss first 20 -> last 20 |
|---|---|---|
| bad_medical | 397 | 2.467 -> 1.518 |
| good_medical | 397 | 1.596 -> 1.119 |
| risky_financial | 338 | 2.758 -> 1.353 |
| prudent_financial | 338 | 2.413 -> 0.688 |
Run record: false-facts-finetuning repo, results/raw/260914_em_advice_train_v1, commit 0315497.
Load: PeftModel.from_pretrained(base, "false-facts-finetuning/em-advice-7b", subfolder="bad_medical").