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View Code? Open in Web Editor NEW[ICCV 2023 oral] This is the official repository for our paper: ''Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning''.
License: MIT License
[ICCV 2023 oral] This is the official repository for our paper: ''Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning''.
License: MIT License
Does SPT support the selection of sensitive parameters in LLMS?
Very excited to see your work, I want to migrate your work to LLM,
How can I change the code? Can you give me some advice? Thank you very much.
Hello, thanks for providing the code.
I have some questions about calculating sensitivity, and I appreciate it if you could clarify them for me.
alpha
and beta
should generally be used?param_num
is multiplied by 0.02 and 1e6 respectively?Thank you in advance.
Hi, great work! We are unable to achieve the results of the experiment described in the title of the paper. But we can reproduce the results of pre-training the model using other datasets. Can you give us some suggestions for experiments? The following are the experimental results under the parameter quantity of 0.4M. Looking forward to hearing from you.
70.82, 92.42, 71.54, 99.28, 87.22, 55.20, 91.22,Natural.
85.57, 95.96, 85.60, 74.31,Specialized.
81.83, 66.81, 49.36, 78.76, 79.02, 49.38, 27.73, 38.11,Structured.
When I set args.get_sensitivity, I find no such .sh.
I need the .sh for get_sensitivity. Can you provide it?
Thanks very much.
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