Implementing attentive/Stanford reader model for reading comprehension tasks (entity based questions)
Currently IN PROGRESS
Attentive Reader: https://arxiv.org/pdf/1506.03340.pdf
Stanford Reader: https://arxiv.org/pdf/1606.02858v2.pdf
Implementing attentive reader model for reading comprehension tasks (entity based questions)
Implementing attentive/Stanford reader model for reading comprehension tasks (entity based questions)
Currently IN PROGRESS
Attentive Reader: https://arxiv.org/pdf/1506.03340.pdf
Stanford Reader: https://arxiv.org/pdf/1606.02858v2.pdf
The loss function in StanfordReader is returning NaN values during training. TF is failing to add the summary because of this issue.
Need to add gradient clipping to RNN to prevent exploding gradients. Tensorflow has packages. Chen et al. has details regarding what gradient clipping value they used for the Stanford Reader.
Need to change custom softmax to make it numerically stable (exponentials can explode) in attention.py and StanfordReader.py
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