TrainingArguments is a class in the Python transformers library. It provides a set of arguments and parameters that can be used to customize the training process for transformer models. These arguments include settings for fine-tuning, batch size, learning rate, gradient accumulation, number of epochs, logging, and more. By utilizing TrainingArguments, developers can easily configure and control the training process of transformer models according to their specific needs and requirements.
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