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import logging |
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import functools |
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from mteb import MTEB |
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from sentence_transformers import SentenceTransformer |
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logging.basicConfig(level=logging.INFO) |
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logger = logging.getLogger("main") |
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task_list = ['Classification', 'Clustering', 'Reranking', 'Retrieval', 'STS', 'PairClassification'] |
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task_langs=["zh", "zh-CN"] |
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model_name = "DMetaSoul/Dmeta-embedding" |
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model = SentenceTransformer(model_name) |
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model.encode = functools.partial(model.encode, normalize_embeddings=True) |
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evaluation = MTEB(task_types=task_list, task_langs=task_langs) |
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evaluation.run(model, output_folder=f"results/zh/{model_name.split('/')[-1]}") |
