📄 中文摘要
微调被视为一种精细工具，能够将通用模型转变为专业模型。然而，微调的使用存在误区，有些人认为只需微调模型就能理解特定领域，而另一些人则认为绝对不应触碰模型权重。实际上，微调的效果取决于使用方式，错误的微调可能导致GPU资源浪费、偏见加剧，甚至使模型性能低于基础版本。微调的分类方式多样，了解不同类型的微调及其成本、执行方法和潜在陷阱对于优化模型表现至关重要。
停止盲目微调：何时微调——何时不触碰模型权重
📄 English Summary
Stop Fine-Tuning Blindly: When to Fine-Tune—and When Not to Touch Model Weights
Fine-tuning is viewed as a precision tool that can transform a generic model into a specialized one. However, misconceptions about its application abound; some believe that simply fine-tuning will enable the model to understand a specific domain, while others argue against altering model weights altogether. In reality, the effectiveness of fine-tuning hinges on its execution, with poor practices potentially leading to wasted GPU resources, increased bias, and models performing worse than their base versions. Understanding the various types of fine-tuning, their costs, execution methods, and the traps that can undermine outcomes is crucial for optimizing model performance.