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A regularized self-labeling approach to improve the generalization and robustness of fine-tuned models

Home Page: https://arxiv.org/abs/2111.04578

License: MIT License

Python 99.51% Shell 0.49%
fine-tuning noisy-labels pytorch

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regularized-self-labeling's Issues

Baseline (L2-SP and L-PGM) implementation in your paper.

The official code of these two methods are all tensorflow based which I can not use.
I have tried to implement them using pytorch by my own, but the accuracies are worse than direct fine-tuning.
Could you please help me to provide the implementation of L2-SP and L-PGM in Table 2 of your paper? Or can you provide the reference code you use?

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