1% label and 10% label in Table 4 (Results of contrasitve learning)

JunlinHan / YOCO

Code for You Only Cut Once: Boosting Data Augmentation with a Single Cut, ICML 2022.

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1% label and 10% label in Table 4 (Results of contrasitve learning) #8

Open khawar-islam opened 7 months ago

khawar-islam commented 7 months ago

Dear @JunlinHan

I hope you are doing well. You have mentioned ImageNet classification result (linear protocol, 1% label and 10% label). I have found the main_lincls.py for linear protocol experiment and main_moco.py for label experiment. However, I'm not able to find where the 1% and 10% label specifications are mentioned in your code. Could you please guide me on this? A prompt response would greatly assist me in my ongoing work.

Regards, Khawar

JunlinHan commented 7 months ago

Hello Khawar,

The ImageNet label is derived from SIMCLR. Please have a look at this link https://github.com/google-research/simclr