Experiment Training Checkpoint

機械支援の翻訳下書き (Japanese) for "Experiment Training Checkpoint": Experiment Training Checkpoint is a ml recovery artifact that saves model state during learning for controlled model comparison. It uses weights, optimizer state, and run metadata so teams can resume or inspect training safely while keeping evidence, reliability, and public-safe operational boundaries clear.

“例文の下書き: The machine learning team used Experiment Training Checkpoint when the experiment showed a metric tradeoff, so the team could resume or inspect training safely before the model moved into evaluation.”