Non-zero initialization of both LoRA matrices improves robustness to small learning rates and preserves fine-tuning accuracy, so LoRA need not start exactly from the pretrained model.
β is tuned among {1, 2, 4, 8, 16}
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Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
Non-zero initialization of both LoRA matrices improves robustness to small learning rates and preserves fine-tuning accuracy, so LoRA need not start exactly from the pretrained model.