Software Engineers Improve Model Accuracy With DoRA Method
DoRA outperforms LoRA on fine-tuning large language models like LLaMA & VL-BART with consistent accuracy gains across various downstream tasks.
This is a Plain English Papers summary of a research paper called DoRA: Weight-Decomposed Low-Rank Adaptation. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview Introduces a novel weight decomposition analysis to investigate the differences between full fine-tuning (FT) and Low-Rank Adaptation (LoRA) Proposes a new method called Weight-Decomposed Low-Rank Adaptation (DoRA) to enhance the learning capacity and training stability of LoRA DoRA fine-tunes the pre-trained weight into two components - magnitude and di...