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TableĀ 2 The main hyper-parameters of our model

From: A neural network approach to chemical and gene/protein entity recognition in patents

Hyper-parameter Value Values tested
Word embedding dimension 100 50, 100, 200
Character embedding dimension 25 25, 50
Character-level BiLSTM state size 25 25, 50
Capitalization embedding dimension 5 5, 10
POS embedding dimension 25 25, 50
Chunking embedding dimension 10 10, 20
NER embedding dimension 5 5, 10
Word-level BiLSTM state size 100 50, 100, 200
SGD learning rate 0.001 0.01, 0.005, 0.001