Web原创：郑佳伟 在nlp任务中，会有很多为了提升模型效果而提出的优化，为了方便记忆，所以就把这些方法都整理出来，也有助于大家学习。为了理解，文章并没有引入公式推导，只是介绍这些方法是怎么回事，如何使用。 一、对抗训练 近几年，随着深度学习的发展，对抗样本得到了越来越多的关注。 WebMar 12, 2024 · torch.optim的灵活使用详解 1. 基本用法： 要构建一个优化器Optimizer，必须给它一个包含参数的迭代器来优化，然后，我们可以指定特定的优化选项， 例如学习速率，重量衰减值等。

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Webfrom torch. optim import Optimizer class Lamb ( Optimizer ): r"""Implements Lamb algorithm. It has been proposed in `Large Batch Optimization for Deep Learning: Training BERT in 76 minutes`_. Arguments: params (iterable): iterable of parameters to optimize or dicts defining parameter groups lr (float, optional): learning rate (default: 1e-3) WebTrain and inference with shell commands . Train and inference with Python APIs commentary of ephesians 3

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Webutils.py internally uses the torch.save(state, filepath) method to save the state dictionary that is defined above. You can add more items to the dictionary, such as metrics. The model.state_dict() stores the parameters of the model and optimizer.state_dict() stores the state of the optimizer (such as per-parameter learning rate). Webimport torch from torch.optim import Optimizer class Lamb (Optimizer): r"""Implements Lamb algorithm. It has been proposed in `Large Batch Optimization for Deep Learning: … dry robes best price