Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning
Table 1: Parameter Settings
['GRU size  [ITALIC] m', '230']
We use the cross-validation to tune our model and grid search to determine model parameters. The grid search approach is used to select optimal learning rate lr for Adam optimizer among {0.1,0.001,0.0005,0.0001}, GRU size m∈{100,160,230,400}, position embedding size l∈{5,10,15,20}. We follow experienced settings for other parameters because they make little influence to our model performance.