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@@ -16,9 +16,9 @@ The evaluation dataset is in Chinese, and we used the same language model **RoBE
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  | BERT-Whitening | 65.27| -| -| -| -| -|
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  | SimBERT | 70.01| -| -| -| -| -|
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  | SBERT-Whitening | 71.75| -| -| -| -| -|
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- | BGE | 78.61| -| -| -| -| -|
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- | [hellonlp/simcse-roberta-base-zh(sup)](https://huggingface.co/hellonlp/simcse-roberta-base-zh) | 80.96| -| -| -| -| -|
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- | [hellonlp/promcse-roberta-base-zh(sup)](https://huggingface.co/hellonlp/promcse-bert-base-zh) | **81.57**| -| -| -| -| -|
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  | BERT-Whitening | 65.27| -| -| -| -| -|
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  | SimBERT | 70.01| -| -| -| -| -|
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  | SBERT-Whitening | 71.75| -| -| -| -| -|
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+ | [BAAI/bge-base-zh](https://huggingface.co/BAAI/bge-base-zh) | 78.61| -| -| -| -| -|
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+ | [hellonlp/simcse-base-zh](https://huggingface.co/hellonlp/simcse-roberta-base-zh) | 80.96| -| -| -| -| -|
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+ | [hellonlp/promcse-base-zh](https://huggingface.co/hellonlp/promcse-bert-base-zh) | **81.57**| -| -| -| -| -|
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