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Table 4 Hyper-parameter search space and final values used

From: Title2Vec: a contextual job title embedding for occupational named entity recognition and other applications

Hyper parameter

CRF

LSTM-CRF

Final

Range

Final

Range

Learning rate

0.1

\(\{0.01,0.1\}\)

0.1

\(\{0.01,0.1\}\)

Mini-batch size

32

\(\{32,128\}\)

128

\(\{32,128\}\)

Word dropout

0.05

–

0.05

–

Variational dropout

0.5

–

0.5

–

Type of optimizer

SGD

\(\{\text {Adam}, \text {SGD}\}\)

SGD

\(\{\text {Adam}, \text {SGD}\}\)

LSTM layers

–

–

1

\(\{1,2\}\)

LSTM state size

–

–

256

\(\{128,256\}\)