What metrics do you log during pre-training and at what...

Effective monitoring requires high-granularity data. Epoch-level averages are insufficient because they hide transient spikes that are often correlated with specific data artifacts. Therefore, you should log training loss, unclipped global gradient norm, effective learning rate, and hardware throughput at every step, while logging canary batch loss every 100 steps.