Qwen2.5-Binary โ€” Protocol 0 SFT

20/20 refusals. 0/20 fabrications.

Update (2026-08-03): the 20/20 / 0/20 numbers above used a scorer that only checked whether the response started with "TRUE"/"FALSE", and could not detect a fabricated number stated anywhere else in the response โ€” an artifact, not a comparable measurement. A v2 control run (30 tokens, one money-regex scorer applied identically to base and fine-tuned models) gives 15/20 refusals, 5/20 fabrications for this model. Raw results: binary_sft_k20_v2.json.

Qwen2.5-7B-Instruct fine-tuned on the Protocol 0 Binary dataset.

Same data, same 3 epochs, same binary format. Result: perfect abstention without a single fabricated number.

See Hermes-3-binary for full methodology.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
model = PeftModel.from_pretrained(base, "SoulInPsyAbstract/binary-qwen25-lora")

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