Machine Learning, Artificial Intelligence, Neural Networks, Data Science, Towards Data Science.
Thus, before raising the learning rate, we take a “snapshot” of the model weights. After training M cycles, we have M model snapshots, f₁, f₂,. . . , each of which will be used in the final ensemble. In the ensemble model, we take the average of all of the snapshots and use this to obtain our