Federated Learning for Emoji Prediction in a Mobile Keyboard
Table 2: The results from federated experiments. All numbers reported are after 2000 training rounds. ηs refers to the learning rate used on the server for applying the update aggregated across users in each round.
['[ITALIC] Experiment', '[ITALIC] Accuracy@1', '[ITALIC] AUC']
In FL, the contents of the client caches are constantly changing as old entries are cleared and replaced by new activity. Since these experiments were conducted non-concurrently, the client cache contents are different and therefore numbers cannot be compared across experiments. We conduct experiments to study the effect of client batch size (B), devices per round (K) and server optimizer configuration on model quality. We then take the best model and compare it with a server trained model.