RiteeshGrandhi/sciclaimeval-shared-task huggingface dataset:
\begin{table}
\centering
\begin{adjustbox}{max width=\textwidth}
        \begin{tabular}{lcc}
        \toprule
        \textbf{Models} & \textbf{Binary%2-way
        } & \textbf{3-way} \\        
        \midrule
        \multicolumn{3}{l}{\textbf{Full training}} \\
        mBERT$_\text{Base}$ & 81.95 & 70.89 \\
        $+$ EN Lex.\ & 82.49 & 71.05 \\
        $+$ ML Lex.\ & 92.84 & 81.81 \\
        $+$ ML Lex.\ $+$ Panlex & \textbf{93.40} & 81.82 \\
        $+$ ML Lex.\ $+$ Panlex $+$ Filtering & \textbf{93.39} & \textbf{81.98} \\
        \midrule
        \multicolumn{3}{l}{\textbf{Training with limited data}} \\
        mBERT$_\text{Base}$ & 68.84 & 56.76 \\
        $+$ EN Lex.\ & 72.47 & 60.58 \\
        $+$ ML Lex.\ & 75.05 & 61.42 \\
        $+$ ML Lex.\ $+$ Panlex & 75.34 & 61.78 \\
        $+$ ML Lex.\ $+$ Panlex $+$ Filtering & \textbf{75.39} & \textbf{61.92} \\

        \bottomrule
        \end{tabular}
\end{adjustbox}
\caption{Table 3: Preliminary results, based on averaged macro-F1 scores across 34 languages. ``EN Lex.''\ and ``ML Lex.''\ indicate the English and multilingual NRC-VAD lexicons.}
\end{table}