What is the critical batch size and how do you use it i...

The critical batch size is defined as the threshold above which gradient noise no longer decreases proportionally with the batch size, making further increases less efficient. Because the critical batch size scales inversely with loss, you should employ a ramp strategy: begin training with a smaller batch size and increase it as the model converges and loss decreases, effectively matching the evolving optimal batch size.