% 实验结果 \section{实验结果} \begin{frame} \frametitle{实验条件介绍} \begin{itemize} \item[\faLaptop] 硬件配置 \begin{itemize} \item 笔记本型号:Lenovo Legion R7000P 2021H \item CPU:AMD Ryzen 7 5800H \item GPU:NVIDIA GeForce RTX 3060 Laptop GPU(6GB显存) \item 内存:16GB DDR4 \end{itemize} \item[\faUbuntu] 软件环境 \begin{itemize} \item 操作系统:Ubuntu 22.04 LTS(通过WSL2运行) \item Python版本:3.11.6 \item 深度学习框架:PyTorch 2.1.0+cu121 \end{itemize} \item[\faRobot] 微调模型:unsloth官方qwen-2.5-3b-4bit量化模型(\href{https://huggingface.co/unsloth/Qwen2.5-3B-Instruct-bnb-4bit}{https://huggingface.co/unsloth/Qwen2.5-3B-Instruct-bnb-4bit}) \item[\faBook] 仓库文档:unsloth官方仓库文档(\href{https://docs.unsloth.ai/}{https://docs.unsloth.ai/}) \end{itemize} \end{frame} \begin{frame} \frametitle{训练指标变化} \begin{figure}[h] \centering \begin{tikzpicture} \begin{axis}[ xlabel=Step, ylabel=Loss, width=\textwidth, height=0.8\textheight] \addplot[mark=none] table[x=Step,y=loss,col sep=comma] {./figures/training_data.csv}; \end{axis} \end{tikzpicture} \caption{训练损失变化曲线} \end{figure} \end{frame} \begin{frame} \frametitle{训练指标变化} \begin{figure}[h] \centering \begin{tikzpicture} \begin{axis}[ xlabel=Step, ylabel=Grad Norm, width=\textwidth, height=0.8\textheight] \addplot[mark=none] table[x=Step,y=grad_norm,col sep=comma] {./figures/training_data.csv}; \end{axis} \end{tikzpicture} \caption{梯度范数变化曲线} \end{figure} \end{frame} \begin{frame} \frametitle{训练指标变化} \begin{figure}[h] \centering \begin{tikzpicture} \begin{axis}[ xlabel=Step, ylabel=Learning Rate, width=\textwidth, height=0.8\textheight] \addplot[mark=none] table[x=Step,y=learning_rate,col sep=comma] {./figures/training_data.csv}; \end{axis} \end{tikzpicture} \caption{学习率变化曲线} \end{figure} \end{frame} \begin{frame} \frametitle{微调效果验证} \begin{figure}[htbp] \centering \includegraphics[width=0.45\textwidth]{./pic/before_train.png} \hspace{0.05\textwidth} \includegraphics[width=0.45\textwidth]{./pic/after_train.png} \caption{训练前后对比} \end{figure} \end{frame}