Convolutional Neural Networks for Sentence Classification

Understand

We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks.

• We show that a simple CNN with little hyperparameter tuning and static vectors achieves excellent results on multiple benchmarks.
• Learning task-specific vectors through fine-tuning offers further gains in performance.
• We additionally propose a simple modification to the architecture to allow for the use of both task-specific and static vectors.