Machine Translation on newstest En-De 2015 (test)
25.44BLEUBase Character-level NMT (Row e)
Evaluation results
| Method | Links | |
|---|---|---|
| Base Character-level NMT (Row e)Target=Char, Depth=2, Attention=Concatenated, Model=Base, Ensemble=true2016.03 | 25.44 | |
| Base BPE-level NMT (Row c)Target=BPE, Depth=2, Attention=Concatenated, Model=Base, Ensemble=true2016.03 | 25.24 | |
| Base BPE-level NMT (Row b)Target=BPE, Depth=2, Attention=hL, Model=Base, Ensemble=true2016.03 | 24.83 | |
| State-of-the-art Non-Neural ApproachApproach=Non-Neural2016.03 | 24 | |
| Base BPE-level NMT (Row c)Target=BPE, Depth=2, Attention=Concatenated, Model=Base, Ensemble=false2016.03 | 23.45 | |
| Base Character-level NMT (Row e)Target=Char, Depth=2, Attention=Concatenated, Model=Base, Ensemble=false2016.03 | 23.06 | |
| Bi-scale Character-level NMT (Row f)Target=Char, Depth=2, Attention=hL, Model=Bi-S, Ensemble=false2016.03 | 22.26 | |
| Base BPE-level NMT (Row b)Target=BPE, Depth=2, Attention=hL, Model=Base, Ensemble=false2016.03 | 22.02 | |
| Base BPE-level NMT (Row a)Target=BPE, Depth=1, Attention=h1, Model=Base, Ensemble=false2016.03 | 21.72 | |
| Base Character-level NMT (Row d)Target=Char, Depth=2, Attention=hL, Model=Base, Ensemble=false2016.03 | 21.3 | |
| Bi-scale Character-level NMT (Row g)Target=Char, Depth=2, Attention=Concatenated, Model=Bi-S, Ensemble=false2016.03 | 20.94 |