""" Build ORPO preference pairs from v7 dev-split SFT data. Each pair: same Q → chosen=YES candidate's prompt+answer, rejected=NO candidate's prompt+answer. """ import argparse, os, sys, random from collections import defaultdict os.environ.setdefault("PYTHONNOUSERSITE", "1") ROOT = "/weka/s225250685/mats-tist" sys.path.insert(0, ROOT) from datasets import load_from_disk, Dataset, DatasetDict def main(): ap = argparse.ArgumentParser() ap.add_argument("--sft", default=os.path.join(ROOT, "data/sft_selector_v7_dev_pointwise_fb")) ap.add_argument("--out", default=os.path.join(ROOT, "data/sft_selector_v7_orpo")) ap.add_argument("--max_pairs_per_q", type=int, default=4) args = ap.parse_args() rng = random.Random(42) dd = load_from_disk(args.sft) def make_pairs(rows): groups = defaultdict(lambda: {"yes": [], "no": []}) for r in rows: k = (r["question"], r["db_id"]) (groups[k]["yes" if r["is_yes"] else "no"]).append(r) out = [] for k, g in groups.items(): if not g["yes"] or not g["no"]: continue rng.shuffle(g["yes"]); rng.shuffle(g["no"]) pe = 0 for y in g["yes"]: for n in g["no"]: if pe >= args.max_pairs_per_q: break out.append({ "prompt": y["prompt"], "chosen": "YES", "rejected": "NO", "messages": [{"role": "user", "content": y["prompt"]}, {"role": "assistant", "content": "YES"}], "rejected_messages": [{"role": "user", "content": n["prompt"]}, {"role": "assistant", "content": "NO"}], "question": y["question"], "db_id": y["db_id"], }) pe += 1 if pe >= args.max_pairs_per_q: break return out train_pairs = make_pairs(list(dd["train"])) test_pairs = make_pairs(list(dd["test"])) rng.shuffle(train_pairs); rng.shuffle(test_pairs) print(f"train pairs: {len(train_pairs)} test pairs: {len(test_pairs)}") DatasetDict({"train": Dataset.from_list(train_pairs), "test": Dataset.from_list(test_pairs)}).save_to_disk(args.out) print(f"SAVED: {args.out}") if __name__ == "__main__": main()