File size: 1,467 Bytes
ccbd209 9bf4115 9bd725a ccbd209 9bf4115 9bd725a ccbd209 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | """Collapse guard: the held-out, human-grounded eval gate.
The whole self-refinement loop is dangerous precisely because the AI rates its own
training data -- that's how model collapse happens. This gate is the antidote: a FROZEN
eval set that the AI never generates or rates, scored by the judge, used only to decide
whether to KEEP a refinement round. If a round regresses on real held-out tasks, it's
reverted. This converts "spirals down" into "only changes that actually help survive."
"""
import json
from pathlib import Path
def load_eval(path):
p = Path(path)
if not p.exists():
return []
return [json.loads(l) for l in p.read_text(encoding="utf-8").splitlines() if l.strip()]
def evaluate(policy, tok, judge, eval_items):
"""Mean judge score of the policy on the frozen eval set."""
if not eval_items:
return 0.0
from core.genutil import chat_generate
from core import modalities
total = 0.0
for it in eval_items:
resp = chat_generate(policy, tok, [{"role": "user", "content": it["instruction"]}],
max_new_tokens=512, do_sample=False)
js = judge.score(it["instruction"], resp)
total += modalities.blended_reward(it.get("type"), js, resp)
return total / len(eval_items)
def keep_round(new_score, prev_score, tolerance=0.0):
"""Keep the round only if it doesn't regress beyond tolerance."""
return new_score >= (prev_score - tolerance)
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