Attention-based method for categorizing different types of online harassment language
Table 2: The results considering F1 Score.
['[BOLD] Model', '[BOLD] sexual_f1', '[BOLD] indirect_f1', '[BOLD] physical_f1', '[BOLD] harassment_f1', '[BOLD] f1_macro']
We have evaluated our models considering the F1 Score, which is the harmonic mean of precision and recall. We have run ten times the experiment for each model and considered the average F1 Score. Considering F1 Macro the models that include the multi-attention mechanism outperform the others and particularly the one with the Projected Layer has the highest performance. In three out of four pairs of models, the ones with the Projected Layer achieved better performance, so in most cases the addition of the Projected Layer had a significant enhancement.