\begin{table}[] \centering \scalebox{0.6}{ \begin{tabular}{|c|c|c|c|c|c|c|c|} \hline \textbf{Model name} & \textbf{Optimizer} & \textbf{Learning Rate} & \textbf{Parameters(n)} & \textbf{Epochs} & \textbf{Time(min)} & \textbf{Loss (validation)} & \textbf{Loss (Training)} \\ \hline Model 01 & \multirow{}{}{RMSprop} & \multirow{}{}{0.01} & 8,412,449 & 16 & 7 & 0.3124 & 0.0061 \\ \cline{1-1} \cline{4-8} Model 02 & & & 8,486,561 & 14 & 7 & 0.3267 & 0.0725 \\ \cline{1-1} \cline{4-8} Model 03 & & & 8,782,241 & 20 & 11 & \textbf{0.2709} & 0.0586 \\ \cline{1-1} \cline{4-8} Model 04 & & & 33,943,873 & 15 & 8 & 0.3020 & 0.2887 \\ \cline{1-1} \cline{4-8} Model 05 & & & 135,770,753 & 17 & 11 & 0.3252 & 0.0738 \\ \cline{1-1} \cline{4-8} Model 06 & & & 140,492,417 & 20 & 12 & 0.2989 & 0.2181 \\ \cline{1-1} \cline{4-8} Model 07 & & & 134,589,569 & 13 & 14 & 0.3891 & 0.0322 \\ \hline \end{tabular}} \caption{Experiment 3.1.1: Results: Parameters, Optimizer, epochs, validation, and training loss for different architectures} \label{tab: table 3_1} \end{table}
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