RiteeshGrandhi/sciclaimeval-shared-task huggingface dataset:
\begin{table}
		\centering
		\begin{adjustbox}
			{max width=\textwidth}
			\begin{tabular}{lcc}
				\toprule \textbf{Model}                                                & \makecell{\textbf{F1} \\ \textbf{\textsc{Docile} labeled}} & \makecell{\textbf{F1} \\ \textbf{\textsc{Payslips}}} \\
				\midrule \multicolumn{3}{l}{\textbf{Pre-training on \textsc{IIT-CDIP}}} \\
				\midrule $\textsc{LayoutLM}_{\textrm{BASE}}$                           & \boldmath{$58.35\pm1.63$}                                  & \underline{$62.31\pm5.13$}                           \\
				\midrule \multicolumn{3}{l}{\textbf{Pre-training on \textsc{Docile}}}   \\
				\midrule $\textsc{LayoutLM}_{\textrm{BASE}}$                           & $51.12\pm1.53$                                             & \boldmath{$64.74\pm2.92$}                            \\
				$\textsc{LayoutLM}_{\textrm{6 layers}}$                                & $57.38\pm1.38$                                             & $61.80\pm3.12$                                       \\
				$\textsc{LayoutLM}_{\textrm{2 layers}}$                                & $53.89\pm1.03$                                             & $54.61\pm3.71$                                       \\
				$\textsc{LayoutLM}_{\textrm{1 layer}}$                                 & \underline{$58.30\pm1.52$}                                 & $45.08\pm3.31$                                       \\
				\bottomrule
			\end{tabular}
		\end{adjustbox}
		\caption{Table 2: F1 scores for named-entity recognition using different pre-training
		and fine-tuning datasets. Results are averaged on 100 runs with different
		seeds.}
	\end{table}