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《Retrieve-and-Read,Multi-task Learning of Information Retrieval and Reading Comprehension》的Reference

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Text Span的评估指标： For text-span questions whose answer is string(s), we need to compare the predicted string(s) with the ground truth answer string(s) (i.e., the correct answer). RCstyle QA task generally uses evaluation metrics Exact Match (EM) and F1 score (F1) proposed by Rajpurkar et al. [94] for text-span questions [104, 116]. EM assigns credit 1.0 to questions whose predicted answer is exactly the same as the ground truth answer and 0.0 otherwise, so the computation of EM is the same as the metric Accuracy but for different categories of RC-style QA. F1 measures the average word overlap between the predicted answer and the ground truth answer. These two answers are both considered as bag of words with lower cases and ignored the punctuation and articles “a”, “an” and “the”. For example, the answer “The Question Answering System” is treated as a set of words {question, answering, system}. Therefore, F1 of each text-span question can be computed at word-level by Equation 2.2

2019-12-18

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如果后台同时运行多个程序，它们的输出全都在nohup.out中，阅读起来很不方便。可通过重定向到不同文件中来解决这个问题;也可以通过在不同的文件下，运行nohup来避免这种情况。 linux启动后，会默认打开3个文件描述符，0表示标准输入，1表示正确输出，2表示错误输出。

2019-12-18

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首先把进程放到后台 nohup python main.py & 然后保持退出终端继续运行 ctrl-z bg 输出在nohup.out里面输入fg，可以把任务调到前台并取消输入jobs显示后台进程

2019-12-18

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