alabnii/sciclaimeval-shared-task huggingface dataset:
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\begin{table}
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\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} \\

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\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}
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