## 4 Results and Discussion
### Experiment II: Performance of Hierarchical Attention Mechanism
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Classifier**} & \multicolumn{3}{c}{**XLNet + HA + FC**} & \multicolumn{3}{c}{**XLNet + FT + FC**} & \multicolumn{3}{c}{**XLNet + BiLSTM + HA + FC**} \\ \cline{2-9}  & **P** & **R** & **F1** & **P** & **R** & **F1** & **P** & **R** & **F1** \\ \hline C00000 & 0.970 & **0.967 * & **0.969** & 0.844 & 0.819 & 0.827 & **0.971** & 0.966 & 0.968 \\ C0100 & 0.956 & 0.934 & 0.944 & 0.875 & 0.792 & 0.826 & **0.961** & **0.946** & **0.953** \\ C01100 & 0.977 & 0.990 & 0.983 & 0.919 & 0.868 & 0.889 & **0.988** & **0.995** & **0.992** \\ C01110 & **0.974** & **0.892** & **0.926** & 0.804 & 0.452 & 0.527 & 0.949 & 0.890 & 0.915 \\ C01120 & 0.971 & 0.989 & 0.979 & 0.567 & 0.473 & 0.476 & **1.000** & **1.000** & **1.000** \\ C01200 & 0.955 & **0.952** & **0.953** & 0.870 & 0.802 & 0.828 & **0.964** & 0.936 & 0.949 \\ C01300 & 0.826 & 0.816 & 0.821 & 0.683 & 0.684 & 0.684 & **0.882** & **0.882** & **0.882** \\ C01310 & 0.962 & 0.972 & 0.966 & 0.737 & 0.638 & 0.629 & **0.980** & **0.986** & **0.983** \\ C01320 & **0.953** & 0.833 & 0.863 & 0.320 & 0.283 & 0.239 & 0.950 & **0.926** & **0.924** \\ C01400 & 0.809 & 0.830 & 0.819 & 0.723 & 0.592 & 0.597 & **0.846** & **0.922** & **0.867** \\ C01410 & **0.802** & **0.844** & **0.808** & 0.605 & 0.585 & 0.552 & 0.740 & 0.797 & 0.752 \\ C01420 & 0.969 & 0.917 & 0.933 & 0.162 & 0.250 & 0.197 & **1.000** & **1.000** & **1.000** \\ C01500 & 0.780 & 0.772 & 0.775 & 0.669 & 0.654 & 0.659 & **0.847** & **0.814** & **0.826** \\ C01510 & 0.977 & 0.970 & 0.974 & 0.797 & 0.801 & 0.799 & **1.000** & **1.000** & **1.000** \\ C01600 & **0.978** & **0.941** & **0.958** & 0.865 & 0.530 & 0.477 & **0.978** & **0.941** & **0.958** \\ C02000 & 0.989 & 0.982 & 0.986 & 0.885 & 0.845 & 0.859 & **0.994** & **0.987** & **0.990** \\ C02100 & 0.996 & 0.996 & 0.996 & 0.817 & 0.887 & 0.839 & **1.000** & **0.998** & **0.999** \\ C02110 & 0.986 & **0.980** & 0.983 & 0.862 & 0.653 & 0.693 & **0.990** & **0.980** & **0.985** \\ C02120 & **0.995** & **0.997** & **0.996** & 0.698 & 0.715 & 0.676 & 0.990 & 0.995 & 0.992 \\ C02200 & 0.670 & 0.784 & 0.704 & 0.371 & 0.347 & 0.312 & **0.900** & **0.833** & **0.813** \\ C02300 & **0.979** & **0.997** & **0.988** & 0.577 & 0.635 & 0.420 & **0.979** & **0.997** & **0.988** \\ C02310 & **1.000** & **1.000** & **1.000** & 0.555 & 0.541 & 0.173 & 0.996 & 0.965 & 0.980 \\ C03000 & 0.919 & 0.914 & 0.916 & 0.805 & 0.692 & 0.685 & **0.924** & **0.932** & **0.928** \\ C04000 & 0.986 & 0.987 & 0.987 & 0.808 & 0.812 & 0.810 & **0.995** & **0.994** & **0.994** \\ C04100 & 0.975 & 0.975 & 0.975 & 0.666 & 0.638 & 0.639 & **1.000** & **1.000** & **1.000** \\ C04200 & 0.974 & 0.974 & 0.974 & 0.900 & 0.886 & 0.892 & **0.987** & **0.987** \\ C04300 & 0.984 & 0.996 & 0.990 & 0.497 & 0.499 & 0.479 & **0.996** & **0.984** & **0.990** \\ Avg(C) & 0.937 & 0.933 & 0.932 & 0.699 & 0.643 & 0.618 & **0.956** & **0.950** & **0.949** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The performance of the hierarchical attention mechanism. Figure 8: Comparison of training advantages of HA, FT and BiLSTM + HA (design concept is identical to Figure 7).