NL-FIIT at SemEval-2019 Task 9: Neural Model Ensemble for Suggestion Mining
Table 2: Results of unsubmitted models in different measures for subtask A
['[BOLD] model', '[BOLD] micro F1', '[BOLD] macro F1', '[BOLD] binary F1']
We can observe that the best model obtained binary F1 score 0.6609 and both types of model ensembles get better results up to 2 percents than each model separately. For mean model ensemble first 3 models were used and for voting ensemble all 5 models were used.