Seq2CNN(50)

Reported on 4 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing2 results

Text ClassificationonDBpedia
Error· 2018-05-20
2.77
best: 0.62 (XLNet)
Abstractive Text Classification Using Sequence-to-convolution Neural Networks arXiv:1805.07745
Text ClassificationonYahoo! Answers
Accuracy· 2018-05-20
55.39
best: 77.62 (BERT-ITPT-FiT)
Abstractive Text Classification Using Sequence-to-convolution Neural Networks arXiv:1805.07745

Methodology2 results

ClassificationonDBpedia
Error· 2018-05-20
2.77
best: 0.62 (XLNet)
Abstractive Text Classification Using Sequence-to-convolution Neural Networks arXiv:1805.07745
ClassificationonYahoo! Answers
Accuracy· 2018-05-20
55.39
best: 77.62 (BERT-ITPT-FiT)
Abstractive Text Classification Using Sequence-to-convolution Neural Networks arXiv:1805.07745