An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Benchmark Model Rank Results
language-modelling-on-penn-treebank-characterTemporal Convolutional Network#17Bit per Character (BPC): 1.31
language-modelling-on-penn-treebank-wordLSTM (Bai et al., 2018)#36Test perplexity: 78.93
language-modelling-on-penn-treebank-wordGRU (Bai et al., 2018)#40Test perplexity: 92.48
language-modelling-on-wikitext-103TCN#76Test perplexity: 45.19
music-modeling-on-jsb-choralesTCN#7NLL: 8.10
sequential-image-classification-on-sequentialTemporal Convolutional Network#12Permuted Accuracy: 97.2%Unpermuted Accuracy: 99.0%