why does adding a dice loss make the dice score fluctuate even though the model still converges

i am fine tuning a u net for semantic segmentation, about 3 million parameters, 550 training images and 150 validation images. with cross entropy alone the model converges well but when i combine cross entropy with dice loss the dice score swings up and down between epochs while the loss keeps goin…

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1. 2026-09-20 22:53 · r/deeplearning
   why does adding a dice loss make the dice score fluctuate even though the model still converges