| """Score explicit option-letter predictions against the frozen SUM release. |
| |
| Usage: python scripts/evaluate.py --annotations dataset.json --predictions predictions.jsonl |
| Each prediction is {"id":"000001", "prediction":"A"}; absent/invalid answers count as incorrect. |
| """ |
| import argparse |
| import collections |
| import json |
| from pathlib import Path |
|
|
| p=argparse.ArgumentParser() |
| p.add_argument('--annotations',type=Path,required=True) |
| p.add_argument('--predictions',type=Path,required=True) |
| a=p.parse_args() |
| rows=json.loads(a.annotations.read_text()) |
| predictions={} |
| for line in a.predictions.read_text().splitlines(): |
| if not line.strip():continue |
| r=json.loads(line) |
| if r['id'] in predictions:raise ValueError('Duplicate prediction ID: '+r['id']) |
| predictions[r['id']]=str(r['prediction']).strip().upper() |
| known={r['id'] for r in rows} |
| if set(predictions)-known:raise ValueError('Unknown prediction IDs') |
| groups=collections.defaultdict(lambda:dict(correct=0,total=0,missing=0,invalid=0)) |
| for r in rows: |
| answer=predictions.get(r['id']) |
| valid={c['label'] for c in r['choices']} |
| for key in ['overall','source/'+r['source_dataset'],'task/'+r['task_type']]: |
| s=groups[key];s['total']+=1 |
| s['correct']+=int(answer==r['answer']) |
| s['missing']+=int(answer is None) |
| s['invalid']+=int(answer is not None and answer not in valid) |
| for s in groups.values():s['accuracy']=s['correct']/s['total'] |
| print(json.dumps(groups,indent=2)) |
|
|
