A method comprises: generating, at a first computing device, a first set of gradient values associated with a data block processed by nodes of a machine learning model, the first set of gradient values being in a first data format; determining a first shared factor from the first set of gradient values, the first shared factor being in a second data format of a lower a precision than that of the first data format; and scaling the first set of gradient values with the first shared factor, to obtain a second set of gradient values having the second data format. In addition, the method comprises sending the second set of gradient values and the first shared factor to a second computing device; and, in response to receiving a third set of gradient values and a second shared factor from the second computing device, adjusting parameters of the machine learning model.