Sentence Classification on Stanford Sentiment Treebank (SST) fine-grained (test)

53.1Accuracy

NTI-SLSTM-LSTM

Updated 4d ago

Evaluation Results

Method	Links
NTI-SLSTM-LSTM 2016.07		53.1
DMN 2016.07		52.1
DiSAN 2017.09		51.72
CNN-Tensor 2017.09		51.2
NCSL 2017.09		51.1
CT-LSTM 2016.07		51
Tree-LSTM 2017.09		51
LR-Bi-LSTM 2017.09		50.6
NTI-SLSTM 2016.07		50.5
Bi-LSTM with s2t self-attention 2017.09		49.95
NLM+TSED+PT+2L 2019.05		49.9
CNN-400 2019.05		49.86
LM+TSED+PT+2L 2019.05		49.82
DRNN 2016.07		49.8
Bi-LSTM 2017.09		49.8
DiSAN without directions 2017.09		49.41
LM+TSED+PT+2L 2019.05		49.37
LSTM-400 2019.05		49.23
STM+TSED+PT+2L 2019.05		49.19
Multi-head with s2t self-attention 2017.09		49.14
STM+TSED+PT+2L 2019.05		49.14
Bi-LSTM 2016.07		49.1
STM+TSED 2019.05		49.1
Word Embedding with s2t self-attention 2017.09		48.87
NLM+TSED+PT+2L 2019.05		48.87
NLM+TSED 2019.05		48.81
LM+TSED 2019.05		48.79
STM+TSED 2019.05		48.77
LM+TSED 2019.05		48.71
NLM+TSED 2019.05		48.66
CNN-non-static 2017.09		48
Word Embedding with additive attention 2017.09		47.47
CNN-MC 2016.07		47.4
2-layer LSTM 2016.07		46
RNTN 2016.07		45.7
RNTN 2017.09		45.7
CNN-50 2019.05		45.07
ENC 2019.05		44.94
MV-RNN 2017.09		44.4
LSTM-50 2019.05		43.76