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SOTA
Music Modeling
Music Modeling On Nottingham
Music Modeling On Nottingham
Metrics
NLL
Parameters
Results
Performance results of various models on this benchmark
Columns
Model Name
NLL
Parameters
Paper Title
Repository
Seq-U-Net
2.97
1.7M
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
-
GRU
3.46
-
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
-
Transformer
3.34
-
R-Transformer: Recurrent Neural Network Enhanced Transformer
-
TCN
2.783
1.7M
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
-
LSTM
3.29
-
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
-
R-Transformer
2.37
-
R-Transformer: Recurrent Neural Network Enhanced Transformer
-
TCN
3.07
-
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
-
RNN
4.05
-
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
-
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Music Modeling On Nottingham | SOTA | HyperAI