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unsupervised contrastive loss

Open Dante-Basile opened this issue 3 years ago • 1 comments

Reference issue

#520

Type of change

This contains the loss function and a basic ResNet50 demo demonstrating training and decreasing loss on CIFAR-10.

What does this implement/fix?

This demonstrates that the ResNet50 network can effectively optimize the loss of the unsupervised contrastive loss function. Future experiments will examine the accuracy of the trained network.

Additional information

NDD 2021

Dante-Basile avatar Dec 12 '21 18:12 Dante-Basile

Codecov Report

Merging #522 (8373149) into staging (634d4d1) will not change coverage. The diff coverage is n/a.

Impacted file tree graph

@@           Coverage Diff            @@
##           staging     #522   +/-   ##
========================================
  Coverage    90.09%   90.09%           
========================================
  Files            7        7           
  Lines          404      404           
========================================
  Hits           364      364           
  Misses          40       40           

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codecov[bot] avatar Dec 12 '21 18:12 codecov[bot]