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This repository has been archived by the owner on Jul 22, 2024. It is now read-only.
I get 88.82% +- 0.46% which is much higher than what is reported in Table 1 ( 80.48% ± 0.57%). Further adaptation also brings improvement to ProtoNet on other datasets. Have you tried this option?
Thanks.
The text was updated successfully, but these errors were encountered:
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Hi,
Thanks for sharing the code. I have two questions:
Can finetune.py also finetune features learned by meta learning methods (e.g. ProtoNet)?
I notice there is a command option --adaptation to adapt meta-learned features on the support set. And when I run:
I get 88.82% +- 0.46% which is much higher than what is reported in Table 1 ( 80.48% ± 0.57%). Further adaptation also brings improvement to ProtoNet on other datasets. Have you tried this option?
Thanks.
The text was updated successfully, but these errors were encountered: