Abstract: The subject technology trains, for a first set of iterations, a first machine learning model using a loss function with a first set of parameters. The subject technology determines, by a second machine learning model, a state of the first machine learning model corresponding to the first set of iterations. The subject technology determines, by the second machine learning model, an action for updating the loss function based on the state of the first machine learning model. The subject technology updates, by the second machine learning model, the loss function based at least in part on the action, where the updated loss function includes a second set of parameters corresponding to a change in values of the first set of parameters. The subject technology trains, for a second set of iterations, the first machine learning model using the updated loss function with the second set of parameters.