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Nov, 2023
小而强大:使用小适配器对ViTs进行微调
Mini but Mighty: Finetuning ViTs with Mini Adapters
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Imad Eddine Marouf, Enzo Tartaglione, Stéphane Lathuilière
TL;DR
通过引入适配器逐步减小其尺寸的方法,我们提出了MiMi训练框架,该框架能够在降低计算和存储成本的同时保持高性能,通过适配器层间神经元重要性的比较来自动估计每个适配器的隐藏维度,我们的方法在三个数据集基准DomainNet、VTAB和Multi-task上优于现有方法,寻找准确性和训练参数之间的最佳权衡。
Abstract
vision transformers
(ViTs) have become one of the dominant architectures in computer vision, and pre-trained ViT models are commonly adapted to new tasks via fine-tuning. Recent works proposed several parameter-efficient
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