> A downfall of CNNs for text is that unlike for images, the input sequences are varying sizes (i.e., varying size sentences), which means most text inputs must be “padded” with some number of 0’s, so that all inputs are the same size.
Actually Kim's model you're using doesn't require padding because it uses k-Max over time pooling.
Also kuddos for NOT updating your word embeddings during training! A lot of people are doing it, but IMHO it's a mistake most of the time.
Are you sure about the padding? On page 1746, bottom right it says "padded as necessary". And intuitively it makes sense that all your inputs need to be the same size for a CNN.
Actually Kim's model you're using doesn't require padding because it uses k-Max over time pooling.
Also kuddos for NOT updating your word embeddings during training! A lot of people are doing it, but IMHO it's a mistake most of the time.