File size: 3,345 Bytes
34e0a18 | 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 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | from __future__ import annotations
import json
import sys
from collections import defaultdict
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
GOLD_PATH = ROOT / "data" / "annotated.jsonl"
VALID_LABELS = {"A", "B", "C", "D"}
def load_jsonl(path: Path) -> list[dict]:
records: list[dict] = []
with path.open(encoding="utf-8") as handle:
for line_number, line in enumerate(handle, start=1):
if not line.strip():
continue
try:
records.append(json.loads(line))
except json.JSONDecodeError as exc:
raise ValueError(
f"Satır {line_number}: geçersiz JSON: {exc}"
) from exc
return records
def load_predictions(path: Path) -> dict[str, str]:
predictions: dict[str, str] = {}
for line_number, record in enumerate(load_jsonl(path), start=1):
item_id = record.get("id")
prediction = record.get("prediction")
if not isinstance(item_id, str) or not item_id:
raise ValueError(f"Satır {line_number}: geçerli id gerekli")
if item_id in predictions:
raise ValueError(f"Satır {line_number}: yinelenen id {item_id}")
if not isinstance(prediction, str):
prediction = ""
predictions[item_id] = prediction.strip()
return predictions
def percent(correct: int, total: int) -> str:
return f"{(100 * correct / total):.2f}%" if total else "n/a"
def main() -> int:
if len(sys.argv) != 2:
print("Kullanım: python scripts/evaluate.py predictions.jsonl")
return 2
items = load_jsonl(GOLD_PATH)
predictions = load_predictions(Path(sys.argv[1]))
known_ids = {item["id"] for item in items}
unknown = sorted(set(predictions) - known_ids)
if unknown:
print(f"Uyarı: {len(unknown)} bilinmeyen id yok sayıldı: {unknown[:5]}")
totals = defaultdict(int)
corrects = defaultdict(int)
invalid = 0
missing = 0
for item in items:
prediction = predictions.get(item["id"])
if prediction is None:
missing += 1
prediction = ""
elif prediction not in VALID_LABELS:
invalid += 1
dimensions = (
("overall", "all"),
("family", item["family"]),
("task_type", item["task_type"]),
("difficulty", item["difficulty"]),
)
for dimension, value in dimensions:
key = f"{dimension}:{value}"
totals[key] += 1
if prediction == item["answer"]:
corrects[key] += 1
overall_key = "overall:all"
print(
f"Overall: {corrects[overall_key]}/{totals[overall_key]} "
f"({percent(corrects[overall_key], totals[overall_key])})"
)
print(f"Missing: {missing}")
print(f"Invalid format: {invalid}")
for dimension in ("family", "task_type", "difficulty"):
print(f"\n{dimension}:")
keys = sorted(key for key in totals if key.startswith(f"{dimension}:"))
for key in keys:
value = key.split(":", 1)[1]
print(
f" {value}: {corrects[key]}/{totals[key]} "
f"({percent(corrects[key], totals[key])})"
)
return 0
if __name__ == "__main__":
sys.exit(main())
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