import argparse import logging import os import time from mteb import MTEB from sentence_transformers import SentenceTransformer logging.basicConfig(level=logging.INFO) logger = logging.getLogger("main") os.environ["HF_DATASETS_OFFLINE"] = "1" # 1 for offline os.environ["TRANSFORMERS_OFFLINE"] = "1" # 1 for offline os.environ["TRANSFORMERS_CACHE"] = "./transformers_cache/" os.environ["HF_DATASETS_CACHE"] = "./hf_datasets_cache/" os.environ["HF_MODULES_CACHE"] = "./hf_modules_cache/" os.environ["HF_METRICS_CACHE"] = "./hf_metrics_cache/" # os.environ["TOKENIZERS_PARALLELISM"] = "false" TASK_LIST_CLUSTERING = [ "ArxivClusteringP2P", "ArxivClusteringS2S", "BiorxivClusteringP2P", "BiorxivClusteringS2S", "MedrxivClusteringP2P", "MedrxivClusteringS2S", "RedditClustering", "RedditClusteringP2P", "StackExchangeClustering", "StackExchangeClusteringP2P", "TwentyNewsgroupsClustering", ] TASK_LIST_PAIR_CLASSIFICATION = [ "SprintDuplicateQuestions", "TwitterSemEval2015", "TwitterURLCorpus", ] TASK_LIST = TASK_LIST_CLUSTERING + TASK_LIST_PAIR_CLASSIFICATION def parse_args(): # Parse command line arguments parser = argparse.ArgumentParser() # parser.add_argument("--startid", type=int) # parser.add_argument("--endid", type=int) parser.add_argument("--modelpath", type=str, default="./models/") parser.add_argument("--lang", type=str, default="en") parser.add_argument("--taskname", type=str, default=None) parser.add_argument("--batchsize", type=int, default=128) parser.add_argument("--device", type=str, default="mps") # sorry :> args = parser.parse_args() return args def main(args): """ ex: python run_array.py --modelpath ./models/all-MiniLM-L6-v2 """ model = SentenceTransformer(args.modelpath, device=args.device) model_name = args.modelpath.split("/")[-1].split("_")[-1] if not model_name: print(f"Model name is empty. Make sure not to end modelpath with a /") return print(f"Running on {model._target_device} with model {model_name}.") for task in TASK_LIST: print("Running task: ", task) # this args. notation seems anti-pythonic evaluation = MTEB(tasks=[task], task_langs=[args.lang]) retries = 5 for attempt in range(retries): try: evaluation.run(model, output_folder=f"results/{model_name}", batch_size=args.batchsize, eval_splits=["test"]) break except ConnectionError: if attempt < retries - 1: print(f"Connection error occurred during task {task}. Waiting for 1 minute before retrying...") time.sleep(60) else: print(f"Failed to execute task {task} after {retries} attempts due to connection errors.") if __name__ == "__main__": args = parse_args() main(args)