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Have not found Monte Carlo Sampling in the code

Open fangkuann opened this issue 5 years ago • 3 comments

Hi, Thanks for releasing the code for active-qa. After browsing the code, I did not find Monte-Carlo Sampling in the training stage. It seems that each training instance consists of only one 「query, reformulated_query, reward」 tuple. Therefore, the reward is the same for each token in one reformulated query. I don't know whether the suspicion is right. If it is right, what will model perform with or without Monte-Carlo sampling? Maybe using only one instance for Monte Carlo sampling is like the relation between stochastic gradient descent and gradient descent? Thank you

fangkuann avatar May 28 '19 07:05 fangkuann

me the same, have you finger out the problem?or get a new version code? @fangkuann

godfly avatar Sep 24 '20 13:09 godfly

me the same, have you finger out the problem?or get a new version code? @fangkuann

I didn't try that. But we apply the paper's training method in our query rewrite module, then the retrieve performance could be enhanced. We further improved this method by adding a value network, for details you may refer to this Chinese technic article https://www.6aiq.com/article/1577969687897.

fangkuann avatar Sep 27 '20 03:09 fangkuann

me the same, have you finger out the problem?or get a new version code? @fangkuann

I didn't try that. But we apply the paper's training method in our query rewrite module, then the retrieve performance could be enhanced. We further improved this method by adding a value network, for details you may refer to this Chinese technic article https://www.6aiq.com/article/1577969687897.

@fangkuann Yes, I follow this article to here. May I ask some question by email? I couldn't found a way to concat you. Send a message to [email protected] if it's ok, thanks a lot

godfly avatar Oct 09 '20 09:10 godfly