A model is being trained using an optimization algorithm where parameters are updated by taking a step in the direction opposite to the gradient of a loss function. For a specific parameter, the calculated gradient of the loss is a large negative value (-10.0). If the learning rate is set to a small positive value (0.01), how will this parameter's value change in the next update step?

Diagnosing Training Instability

Calculating a Parameter Update

Deep Learning Minibatch Training Loop