mteb-retrieval-snowflake-arctic-embed-m-v1.5
/
_qrels
/.ipynb_checkpoints
/_download_script-checkpoint.py
""" | |
Simple script to pre-download and JSON-serialize the query-relations of MTEB datasets, since the `mteb` library requires us to download the full dataset to get just the qrels, and that's slow to do every time we want just qrels. | |
""" | |
import json | |
from pathlib import Path | |
import mteb | |
from tqdm.auto import tqdm | |
names = [ | |
'ArguAna', | |
'CQADupstackAndroidRetrieval', | |
'CQADupstackEnglishRetrieval', | |
'CQADupstackGamingRetrieval', | |
'CQADupstackGisRetrieval', | |
'CQADupstackMathematicaRetrieval', | |
'CQADupstackPhysicsRetrieval', | |
'CQADupstackProgrammersRetrieval', | |
'CQADupstackStatsRetrieval', | |
'CQADupstackTexRetrieval', | |
'CQADupstackUnixRetrieval', | |
'CQADupstackWebmastersRetrieval', | |
'CQADupstackWordpressRetrieval', | |
'ClimateFEVER', | |
'DBPedia', | |
'FEVER', | |
'FiQA2018', | |
'HotpotQA', | |
'MSMARCO', | |
'NFCorpus', | |
'NQ', | |
'QuoraRetrieval', | |
'SCIDOCS', | |
'SciFact', | |
'TRECCOVID', | |
'Touche2020' | |
] | |
out_path = Path(__file__) | |
def load_mteb_qrels(task_name: str) -> dict: | |
split_name = "dev" if task_name == "MSMARCO" else "test" | |
task_obj = mteb.MTEB(tasks=[mteb.get_task(task_name, languages=["en"])]).tasks[0] | |
task_obj.load_data(eval_splits=[split_name]) | |
qrels = task_obj.relevant_docs[split_name] | |
return qrels | |
for name in tqdm(names, desc="downloading qrels", unit="dataset"): | |
qrel = load_mteb_qrels(name) | |
out_file_path = (out_path / f"{name}.json") | |
out_file_path.write_text(json.dumps(qrel, indent=2, sort_keys=True)) | |