\begin{table*}[htp]
\resizebox{\textwidth}{!}{
\begin{tabular}{lrrrrr}
\toprule
Model/adapter & HarmBench - LM Evaluated Safety score & SimpleSafetyTests - LM Evaluated Safety score & BBQ - BBQ accuracy & Anthropic Red Team - LM Evaluated Safety score & XSTest - LM Evaluated Safety score \\
\midrule
DBRX Instruct & 0.2710163111668758 & 0.535 & 0.792 & 0.765875 & 0.7744444444444445 \\
DeepSeek LLM Chat (67B) & 0.649375 & 0.9675 & 0.862 & 0.994375 & 0.8894444444444445 \\
Llama 3 Instruct (70B) & 0.64 & 0.99 & 0.91 & 0.96675 & 0.9677777777777777 \\
Llama 3 Instruct (8B) & 0.726875 & 0.9925 & 0.765 & 0.98825 & 0.9561111111111111 \\
Llama 3.1 Instruct Turbo (405B) & 0.626875 & 0.9875 & 0.945 & 0.964625 & 0.9588888888888889 \\
Llama 3.1 Instruct Turbo (70B) & 0.46875 & 0.925 & 0.954 & 0.932125 & 0.945 \\
Llama 3.1 Instruct Turbo (8B) & 0.61625 & 0.9875 & 0.785 & 0.968375 & 0.9533333333333334 \\
Mistral Instruct v0.1 (7B) & 0.23304020100502512 & 0.4325 & 0.565 & 0.7105 & 0.6866666666666666 \\
Mistral Instruct v0.3 (7B) & 0.34375 & 0.81 & 0.668 & 0.901125 & 0.9255555555555556 \\
Mixtral Instruct (8x22B) & 0.520625 & 0.915 & 0.916 & 0.961625 & 0.9405555555555556 \\
Mixtral Instruct (8x7B) & 0.45125 & 0.905 & 0.857 & 0.927875 & 0.9305555555555556 \\
Qwen1.5 Chat (72B) & 0.648125 & 0.99 & 0.846 & 0.98975 & 0.9572222222222222 \\
Qwen2 Instruct (72B) & 0.7675 & 0.985 & 0.951 & 0.991 & 0.9688888888888889 \\
Claude 3 Haiku (20240307) & 0.9125 & 1.0 & 0.625 & 0.999625 & 0.8527777777777777 \\
Claude 3 Sonnet (20240229) & 0.9575 & 1.0 & 0.9 & 0.998375 & 0.8583333333333333 \\
Claude 3 Opus (20240229) & 0.974375 & 1.0 & 0.94 & 0.997875 & 0.925 \\
Claude 3.5 Sonnet (20240620) & 0.980625 & 1.0 & 0.949 & 0.99775 & 0.9561111111111111 \\
Command R & 0.504375 & 0.9425 & 0.724 & 0.93725 & 0.9388888888888889 \\
Command R Plus & 0.485 & 1.0 & 0.899 & 0.98025 & 0.9383333333333334 \\
Gemini 1.5 Pro (001) & 0.79875 & 0.9748743718592965 & 0.945 & 0.99925 & 0.9044444444444445 \\
Gemini 1.5 Flash (001) & 0.8 & 0.9698492462311558 & 0.947 & 0.99925 & 0.9205555555555556 \\
GPT-3.5 Turbo (0613) & 0.68 & 0.9575 & 0.699 & 0.995625 & 0.9322222222222222 \\
GPT-3.5 Turbo (1106) & 0.685625 & 0.9225 & 0.649 & 0.9799899949974987 & 0.9377777777777778 \\
GPT-3.5 Turbo (0125) & 0.6325 & 0.92 & 0.606 & 0.96725 & 0.9422222222222222 \\
GPT-4 Turbo (2024-04-09) & 0.898125 & 0.99 & 0.941 & 0.99675 & 0.9772222222222222 \\
GPT-4o (2024-05-13) & 0.829375 & 0.985 & 0.951 & 0.9913706853426714 & 0.9727777777777777 \\
GPT-4o mini (2024-07-18) & 0.849375 & 0.9775 & 0.882 & 0.98325 & 0.96 \\
\bottomrule
\end{tabular}}
\caption{Results for accuracy (safety_scenarios)}
\label{fig:accuracy (safety_scenarios)}
\end{table*}