AzureML-BERT
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Dedicated vs. Low-priority servers
Hi, I just have a question. Does this code handle being pre-empted on Azure ML low-priority VMs? I've read that BERT is particularly sensitive and requires the model, optimizer state, and dataset shuffling to all be saved and restored if pre-empted during pre-training.