\begin{table*}[htp]
\resizebox{\textwidth}{!}{
\begin{tabular}{lrrrr}
\toprule
Model/adapter & Mean win rate & FinQA - Program Accuracy & FinanceBench - Correct Answer & BANKING77 - EM \\
\midrule
Llama 3 Instruct (70B) & 0.5 & 0.39 & 0.56 & 0.76 \\
Llama 3 Instruct (8B) & 0.018518518518518517 & 0.2 & 0.19 & 0.31 \\
Llama 3.1 Instruct Turbo (405B) & 0.75 & 0.51 & 0.58 & 0.79 \\
Llama 3.1 Instruct Turbo (70B) & 0.6296296296296297 & 0.56 & 0.53 & 0.78 \\
Llama 3.1 Instruct Turbo (8B) & 0.16666666666666666 & 0.27 & 0.52 & 0.5 \\
Mistral Instruct v0.3 (7B) & 0.19444444444444445 & 0.33 & 0.41 & 0.67 \\
Mixtral Instruct (8x22B) & 0.5185185185185185 & 0.4 & 0.49 & 0.8 \\
Mixtral Instruct (8x7B) & 0.12962962962962962 & 0.24 & 0.48 & 0.65 \\
Qwen1.5 Chat (72B) & 0.3888888888888889 & 0.28 & 0.55 & 0.77 \\
Qwen2 Instruct (72B) & 0.5925925925925926 & 0.39 & 0.54 & 0.81 \\
Claude 3 Haiku (20240307) & 0.4166666666666667 & 0.38 & 0.6 & 0.09 \\
Claude 3 Sonnet (20240229) & 0.49074074074074076 & 0.33 & 0.64 & 0.72 \\
Claude 3 Opus (20240229) & 0.5925925925925926 & 0.35 & 0.68 & 0.76 \\
Claude 3.5 Sonnet (20240620) & 0.6018518518518519 & 0.22 & 0.63 & 0.82 \\
Gemini 1.5 Pro (001) & 0.75 & 0.51 & 0.56 & 0.81 \\
Gemini 1.5 Flash (001) & 0.7870370370370371 & 0.48 & 0.57 & 0.82 \\
GPT-3.5 Turbo (0125) & 0.5277777777777778 & 0.37 & 0.6 & 0.76 \\
GPT-4o (2024-05-13) & 0.9074074074074074 & 0.47 & 0.65 & 0.83 \\
GPT-4o mini (2024-07-18) & 0.5370370370370371 & 0.41 & 0.53 & 0.78 \\
\bottomrule
\end{tabular}}
\caption{Results for accuracy (financial_scenarios)}
\label{fig:accuracy (financial_scenarios)}
\end{table*}