CNN for Sentence Classification
referenced by Convolutional Neural Networks for Sentence Classification(Yoon Kim, 2014)
Korea University Information Retrieval(COSE 472) Assignment7
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CNN-rand : Our baseline model where all words are randomly initialized and then modified during training.
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CNN-static : A model with pre-trained vectors from word2vec. All words— including the unknown ones that are randomly initialized—are kept static and only the other parameters of the model are learned.
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CNN-non-static : Same as above but the pre-trained vectors are fine-tuned for each task.
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CNN-multichannel : A model with two sets of word vectors. Each set of vectors is treated as a ‘channel’ and each filter is applied to both channels, but gradients are backpropagated only through one of the channels. Hence the model is able to fine-tune one set of vectors while keeping the other static. Both channels are initialized with word2vec.