An Experimental Study of LSTM Encoder-Decoder Model for Text Simplification
Table 2: Sort Sequence
['V 10', 'H 128', 'E 114', 'Train,Val,Test 9k,1k,10k', 'Train,Val,Test 0.9744,0.9952,0.9956']
The datasets consist of sequence pairs (X,Y), where X = (x1,x2,... ,x25) Y =sorted(x1,x2, ... ,x25) xi∈V Similarly, the size of the vocabulary, training data, and neurons influence the performance. It is harder to train if we increase the vocabulary to 1000, but the model can still learn the sorting rule with a high accuracy if provided enough training data.