1. Recently, Christin et al. published an article that reviewed the field of deep learning and offered advice on how to train a deep learning model.
2. We write here to emphasize the importance of model verification, which can help ensure that the model will generalize to new data.
3. Specifically, we discuss the importance of using a test set for model verification, and of defining an explicit research hypothesis.
4. We then present a revised workflow that will help ensure that the accuracy reported for your deep learning model is reliable.

中文翻译：

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测试集验证是模型构建中必不可少的步骤

1. 最近，克里斯汀等。发表了一篇文章，回顾了深度学习领域，并提供了有关如何训练深度学习模型的建议。
2. 我们在这里写来强调模型验证的重要性，这可以帮助确保模型将泛化为新数据。
3. 具体来说，我们讨论了使用测试集进行模型验证以及定义明确的研究假设的重要性。
4. 然后，我们提出了经过修订的工作流程，这将有助于确保为您的深度学习模型报告的准确性是可靠的。