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Hi, 我之前曾经问过一个训练生成对话模型(机器翻译模型未做实验)过程中经常会遇到"NaN"的问题,之前获得的建议是调整学习率,我试过很多次,但仍然会出现这种情况。我最近发现在tools.py中的clip函数中,只处理了NaN的情况,而实际发现,梯度更多的是先出现Inf的情况,进而会导致cost出现NaN的情况。而加入Inf的处理后,"NaN"的情况目前就没有出现过了。不知道这种解决方案是否是对的?
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我们也发现即使处理了NAN的情况偶尔还是会有cost出现NAN的现象。你的方案应该是对的,如果有机会的话我们也会尝试一下,谢谢!
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Hi,
我之前曾经问过一个训练生成对话模型(机器翻译模型未做实验)过程中经常会遇到"NaN"的问题,之前获得的建议是调整学习率,我试过很多次,但仍然会出现这种情况。我最近发现在tools.py中的clip函数中,只处理了NaN的情况,而实际发现,梯度更多的是先出现Inf的情况,进而会导致cost出现NaN的情况。而加入Inf的处理后,"NaN"的情况目前就没有出现过了。不知道这种解决方案是否是对的?
The text was updated successfully, but these errors were encountered: