Hi, Im working on gender inference. have the data like this,
userid, text,
1, hello, world
1, how are you
…(up to 3000)   gender:Female
2, whats up
2, Im here
…(up to 3000) gender:Male
The problem is that if I concat all of the texts for each user, it would be too long for LSTM to process. What I am thinking is to map each sentence into sentence embedding using bert and average them. In this way, each user is represented as a vector. However, this will generate a vector. How do I feed it into a LSTM model which takes a 3d tensor as input?