I am trying to create a sentiment analysis model using a dataset that have ~50000 positive tweets that i labeled as 1, ~50000 negative tweets that i have labeled as 0. Also i have acquired ~10000 tweets that are neutral.
Due to the low number of neutral tweets my thinking is to label neutral with 0.5 and train the model using binary crossentropy as loss function. My output layer is 1 neuron with sigmoid activation function so prediction value would be between (0,1) .
Is my thinking right or it will mess the accuracy?