Datasets:
File size: 2,169 Bytes
296b327 | 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 | #!/usr/bin/env python3
from __future__ import annotations
import argparse
import json
import re
from collections import Counter
from pathlib import Path
from typing import Any
def read_jsonl(path: Path) -> list[dict[str, Any]]:
rows: list[dict[str, Any]] = []
if not path.exists():
return rows
with path.open("r", encoding="utf-8") as handle:
for line in handle:
line = line.strip()
if line:
rows.append(json.loads(line))
return rows
def word_count(text: Any) -> int:
return len(re.findall(r"\b[\w'-]+\b", str(text)))
def avg(values: list[float]) -> float:
return sum(values) / len(values) if values else 0.0
def main() -> None:
parser = argparse.ArgumentParser(description="Summarize LifeStreamingCoT v0.4 quality metrics.")
parser.add_argument("--data-dir", default="life_streaming_cot_dataset")
args = parser.parse_args()
data_dir = Path(args.data_dir) / "data"
rows = read_jsonl(data_dir / "train.jsonl") + read_jsonl(data_dir / "eval.jsonl")
hq_rows = read_jsonl(data_dir / "train_high_quality.jsonl") + read_jsonl(data_dir / "eval_high_quality.jsonl")
total_chunks = sum(row.get("num_chunks", 0) for row in rows)
skip_chunks = sum(len(row.get("skip_chunks", [])) for row in rows)
print("Quality analysis")
print(f"total rows: {len(rows)}")
print(f"high-quality rows: {len(hq_rows)}")
print(f"domains: {dict(sorted(Counter(row.get('domain') for row in rows).items()))}")
print(f"quality flags: {dict(sorted(Counter(flag for row in rows for flag in row.get('quality_flags', [])).items()))}")
print(f"average quality_score: {avg([float(row.get('quality_score', 0)) for row in rows]):.3f}")
print(f"average streaming words: {avg([word_count(row.get('streaming_reasoning', '')) for row in rows]):.2f}")
print(f"average deep words: {avg([word_count(row.get('deep_reasoning', '')) for row in rows]):.2f}")
print(f"skip ratio: {skip_chunks / total_chunks if total_chunks else 0:.4f}")
print(f"llm_augmented rows: {sum(1 for row in rows if row.get('llm_augmented'))}")
if __name__ == "__main__":
main()
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