two different batch sizes. In the training of GPT-2 and T5 models, CAME achieves fast convergence speed as Adam without degrading performance. Notably, in the large-batch training of the BERT model, CAME obtains comparable validation accuracy with LAMB using around 15% less memory usage.
   </p>
   <p>
    Q: Can you explain the value of this in basic terms? Like you're talking to a CEO. So what? What's the bottom line here?
   </p>
   <p>
    A: Absolutely. This research is about making the process of trai