One of the essential components of deep learning is the choice of the loss function and performance metrics used to train and evaluate models. This paper reviews the most prevalent loss functions and performance measurements in deep learning. We examine the benefits and limits of each technique and illustrate their application to various deep-learning problems. Our review aims to give a comprehensive picture of the different loss functions and performance indicators used in the most common deep learning tasks and help practitioners choose the best method for their specific task.

翻译：深度学习的关键组成部分之一是用于训练和评估模型的损失函数及性能指标的选择。本文综述了深度学习中最常用的损失函数和性能度量方法。我们探讨了每种技术的优缺点，并展示了它们在不同深度学习问题中的应用。本综述旨在全面描绘最常见深度学习任务中使用的各种损失函数与性能指标，帮助从业者针对具体任务选择最优方法。