\begin{table*}[t] %跨雙欄
\centering
\renewcommand{\arraystretch}{1.10}
\setlength{\tabcolsep}{6pt}

\resizebox{\textwidth}{!}{%
\begin{tabular}{|c|c|c|c|c|c|c|}
\hline % 畫一條水平線
\multirow{2}{*}{Model (\#para)} &
\multicolumn{6}{c|}{Subtask 2: Polarization Type Classification (22 Languages / Development Set)} \\
\cline{2-7}
& Political & Racial/Ethnic & Religious & Gender/Sexual & Other & Macro F1 \\
\hline
Gemma-3 (27B)             & 0.7328 & 0.5730 & 0.6626 & 0.4766 & 0.4141 & 0.5718 \\ \hline
Mistral-small-3.2 (24B)   & 0.6770 & 0.5376 & 0.6265 & 0.4450 & 0.4149 & 0.5402 \\ \hline
Phi-4 (14B)               & 0.6662 & 0.5306 & 0.5858 & 0.4290 & 0.3793 & 0.5182 \\ \hline
Majority voting    & 0.7108 & 0.5633 & 0.6535 & 0.4684 & 0.4183 & 0.5629 \\ \hline
Weighted voting    & 0.7204 & 0.5668 & 0.6648 & 0.4869 & 0.4222 & 0.5722 \\ \hline
Stacking Ensemble         & \textbf{0.7366} & \textbf{0.5933} & \textbf{0.6698} & \textbf{0.5468} & \textbf{0.5214} & \textbf{0.6136} \\ \hline
\end{tabular}}

\caption{Fine-tuned SLM results on the development set of Subtask 2. Each label score and Macro F1 are macro-F1 averaged over 22 languages.}

\label{tab:subtask2_dev_22lang}
\end{table*}

