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感谢提供ACOS数据集。但是我使用T5large模型,同样的数据集与评价标准,在restaurant上取得0.458的f1,laptop上取得0.462的f1,远远超过论文中的方法.
The text was updated successfully, but these errors were encountered:
是的,目前已经有工作做到更好的f1了。
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感谢提供ACOS数据集。但是我使用T5large模型,同样的数据集与评价标准,在restaurant上取得0.458的f1,laptop上取得0.462的f1,远远超过论文中的方法.
The text was updated successfully, but these errors were encountered: