Bert-Multi-Label-Text-Classification
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感谢分享
大佬,首先非常感谢你分享代码,我用过后发现有一处小问题,在xlnet_processor.py代码的157行和163行,input_mask值为0表示这个位置是真实的Token,而1表示这是一个Padding的Token,您看看这是否不小心弄反了
input_mask = [0] * len(input_ids)
input_mask = ([1] * padding_len) + input_mask
ENGLISH: Big brother, first of all, thank you very much for sharing the code. I found a small problem after using it. In the 157 and 163 lines of the xlnet_processor.py code, an input_mask value of 0 means that this position is a real Token, and 1 means that it is a Padding Token, you see if this is accidentally reversed
input_mask = [0] * len(input_ids)
input_mask = ([1] * padding_len) + input_mask
使用XLNET进行训练时,准确率只有0.5左右,您是否有这样的问题? 请问这个项目的XLNET数据输入是否有问题?