sentence classification with RNN-LSTM - output layer
When doing a multiclass classification problem, in which the goal is predict exactly one class label for each input, it is standard to use the softmax function (a normalized exponential) as the activation function for the last layer. However, if your problem is a multilabel classification (in which the classes are not mutually exclusive), then using a sigmoid as the activation function would be appropriate. In both situations, you would have as many output units as labels (20 in your case).