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So, I made a bidirectional LSTM model for sentiment classification. Model's job was to predict ratings of movies(1-5 stars) based on the movie review.
While training the model I first used categorical cross entropy loss function. I trained the model for 10+ hours on CPU for about 45 epochs. While training every epoch showed model accuracy to be 0.5098(same for every epoch).
Then I changed the loss function to binary cross entropy and it seemed to be work fine while training. So, I want to know what exactly is the difference between these two?