Create scorer.py

scorer.py

@@ -0,0 +1,73 @@
+import csv
+import json
+import re
+from dataclasses import dataclass
+from typing import Dict, List, Tuple, Optional
+
+
+@dataclass
+class ScoredItem:
+    sample_id: str
+    gold: str
+    pred: str
+    is_correct: int
+    parsed_ok: int
+
+
+CHOICE_RE = re.compile(r"\b([AB])\b", re.IGNORECASE)
+
+def parse_choice(model_output: str) -> Tuple[Optional[str], int]:
+    if model_output is None:
+        return None, 0
+
+    text = model_output.strip()
+
+    if text.startswith("{") and text.endswith("}"):
+        try:
+            obj = json.loads(text)
+            for k in ["choice", "answer", "selected", "option"]:
+                if k in obj and isinstance(obj[k], str):
+                    c = obj[k].strip().upper()
+                    if c in ["A", "B"]:
+                        return c, 1
+        except Exception:
+            pass
+
+    m = CHOICE_RE.search(text)
+    if m:
+        return m.group(1).upper(), 1
+
+    if text and text[0].upper() in ["A", "B"]:
+        return text[0].upper(), 1
+
+    return None, 0
+
+
+def score_row(row: Dict[str, str], model_output: str) -> ScoredItem:
+    gold = row["correct_option"].strip().upper()
+    choice, ok = parse_choice(model_output)
+    pred = choice if choice else ""
+    is_correct = 1 if choice == gold else 0
+    return ScoredItem(row["sample_id"], gold, pred, is_correct, ok)
+
+
+def score_file(gold_csv_path: str, predictions: Dict[str, str]) -> Dict[str, float]:
+    scored: List[ScoredItem] = []
+    with open(gold_csv_path, "r", newline="", encoding="utf-8") as f:
+        for row in csv.DictReader(f):
+            scored.append(score_row(row, predictions.get(row["sample_id"], "")))
+
+    n = len(scored)
+    if n == 0:
+        return {"accuracy": 0.0, "parse_rate": 0.0, "n": 0}
+
+    return {
+        "accuracy": sum(s.is_correct for s in scored) / n,
+        "parse_rate": sum(s.parsed_ok for s in scored) / n,
+        "n": n,
+    }
+
+
+if __name__ == "__main__":
+    preds = {"CVSC-0001": "A", "CVSC-0002": "Answer: A"}
+    print(score_file("data/train.csv", preds))