File size: 1,563 Bytes
6379283 | 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 | #!/usr/bin/env python3
"""
MBPP (Mostly Basic Python Programming) benchmark evaluation.
"""
import json
from pathlib import Path
import datetime
def generate_estimate():
"""Estimate based on Qwen2.5-Coder-32B baseline."""
# Qwen2.5-Coder-32B: ~80% on MBPP (typical for strong coding models)
estimate = {
"model": "Stack 2.9 (estimate)",
"benchmark": "MBPP",
"pass@1": 0.80,
"pass@10": 0.85,
"pass@100": 0.88,
"note": "Estimate based on Qwen2.5-Coder-32B. Actual after training.",
"source": "Qwen2.5-Coder technical report"
}
return estimate
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--estimate-only", action="store_true")
parser.add_argument("--output", type=str, default="stack-2.9-eval/results/mbpp.json")
args = parser.parse_args()
output_path = Path(args.output)
output_path.parent.mkdir(parents=True, exist_ok=True)
print("🔬 MBPP Benchmark Evaluation")
if args.estimate_only:
result = generate_estimate()
else:
# Actual evaluation would go here (similar to HumanEval)
result = {
"note": "Full MBPP evaluation implementation pending",
"status": "framework_ready"
}
with open(output_path, 'w') as f:
json.dump(result, f, indent=2)
print(f"✅ Results saved to {output_path}")
if "pass@1" in result:
print(f" Pass@1 (estimate): {result['pass@1']*100:.1f}%")
if __name__ == "__main__":
import argparse, datetime
main() |