\begin{table*}[htp]
\resizebox{\textwidth}{!}{
\begin{tabular}{lrrrrrr}
\toprule
Model/adapter & EM & # eval & # train & truncated & # prompt tokens & # output tokens \\
\midrule
Llama 3 Instruct (70B) & 0.76 & 100.0 & 5.0 &  & 683.1 & 5.05 \\
Llama 3 Instruct (8B) & 0.31 & 100.0 & 5.0 &  & 683.1 & 3.78 \\
Llama 3.1 Instruct Turbo (405B) & 0.79 & 100.0 & 5.0 &  & 683.1 & 4.89 \\
Llama 3.1 Instruct Turbo (70B) & 0.78 & 100.0 & 5.0 &  & 683.1 & 4.91 \\
Llama 3.1 Instruct Turbo (8B) & 0.5 & 100.0 & 5.0 &  & 683.1 & 5.65 \\
Mistral Instruct v0.3 (7B) & 0.67 & 100.0 & 5.0 &  & 1000.54 & 7.56 \\
Mixtral Instruct (8x22B) & 0.8 & 100.0 & 5.0 &  & 1000.54 & 8.81 \\
Mixtral Instruct (8x7B) & 0.65 & 100.0 & 5.0 &  & 1000.54 & 7.52 \\
Qwen1.5 Chat (72B) & 0.77 & 100.0 & 5.0 &  & 752.13 & 4.94 \\
Qwen2 Instruct (72B) & 0.81 & 100.0 & 5.0 &  & 752.13 & 4.91 \\
Claude 3 Haiku (20240307) & 0.09 & 100.0 & 5.0 &  & 872.16 & 17.09 \\
Claude 3 Sonnet (20240229) & 0.72 & 100.0 & 5.0 &  & 872.16 & 5.96 \\
Claude 3 Opus (20240229) & 0.76 & 100.0 & 5.0 &  & 872.16 & 6.09 \\
Claude 3.5 Sonnet (20240620) & 0.82 & 100.0 & 5.0 &  & 872.16 & 6.13 \\
Gemini 1.5 Pro (001) & 0.81 & 100.0 & 5.0 &  & 915.17 &  \\
Gemini 1.5 Flash (001) & 0.82 & 100.0 & 5.0 &  & 915.17 &  \\
GPT-3.5 Turbo (0125) & 0.76 & 100.0 & 5.0 &  & 683.1 & 3.82 \\
GPT-4o (2024-05-13) & 0.83 & 100.0 & 5.0 &  & 696.86 & 4.04 \\
GPT-4o mini (2024-07-18) & 0.78 & 100.0 & 5.0 &  & 696.86 & 4.03 \\
\bottomrule
\end{tabular}}
\caption{Results for banking77_ (banking77)}
\label{fig:banking77_ (banking77)}
\end{table*}