Unverified50% confidenceFactExact time
If the BatchNorm layers are set to train mode during fine-tuning, the running mean and running variance will be re-estimated and overwritten by the statistics of the current mini-batch; when the batch size is small (such as 8 or 16), this causes the running statistics to drift drastically and destroys the learned normalization baseline, manifesting as loss oscillation or even a sharp drop in accuracy.
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50%
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Long-term
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10/21/2026
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