RiteeshGrandhi/sciclaimeval-shared-task huggingface dataset:
\begin{table}
\centering
\begin{adjustbox}{max width=\textwidth}
        \begin{tabular}{lccccc}
        \toprule
        \multirow{2}{*}{\textbf{Models + ML Lex.}} & \multicolumn{2}{c}{\textbf{Binary}} && \multicolumn{2}{c}{\textbf{3-way}} \\
        \cmidrule{2-3} \cmidrule{5-6}
        & \textbf{Reg.} &\textbf{ Class.} && \textbf{Reg.} & \textbf{Class.} \\
        \midrule
        mBERT$_\text{Base}$ & \textbf{67.43} & 66.29 & & 48.62 & \textbf{48.78} \\
        XLM-R$_\text{Base}$ & \textbf{69.24} & 64.37 & & \textbf{49.27} & 42.38 \\
        XLM-R$_\text{Large}$ & \textbf{75.31} & 74.54 & & \textbf{53.69} & 53.27 \\
        mBART$_\text{Large}$ & \textbf{73.13} & 71.23 & & 49.08 & \textbf{49.19} \\
        mT5$_\text{Base}$ & \textbf{74.55} & 68.27 & & 99.84 & \textbf{53.71} \\
        mT5$_\text{Large}$ & \textbf{75.96} & 72.21 & & 90.94 & \textbf{54.96} \\
        \bottomrule
        \end{tabular}
\end{adjustbox}
\caption{Table 5: Regression vs.\ classification in lexicon-based pretraining for zero-shot sentiment analysis.}
\end{table}