Plot the accuracy and loss of the model

Question

Hello how can i plut in this code. I want to graph the performance of the model on the train and test sets recorded during training using a line plot, one for each of the loss and the classification accuracy.

This is federeted learning. Please consider that in the federated learning local_model.fit is for training local model afetr the global_model trained with local trained data and the global_model trained data supposed to be examined not local model.

`for comm_round in range(comms_round):

global_weights = global_model.get_weights()

scaled_local_weight_list = list()

client_names= list(clients_batched.keys())
random.shuffle(client_names)

for client in client_names:
    local_model = Transformer
    local_model.compile(loss=tf.keras.losses.CategoricalCrossentropy(),
                        optimizer=tf.keras.optimizers.Adam(learning_rate = 0.01),
                        metrics='acc')

    local_model.set_weights(global_weights)

    local_model.fit(clients_batched[client], epochs=1, verbose=0)

    scaling_factor = weight_scalling_factor(clients_batched, client)
    scaled_weights = scale_model_weights(local_model.get_weights(), scaling_factor)
    scaled_local_weight_list.append(scaled_weights)

    K.clear_session()

average_weights = sum_scaled_weights(scaled_local_weight_list)

global_model.set_weights(average_weights)

for(X_test, Y_test) in test_batched:
    global_acc, global_loss = test_model(test_x, test_y, global_model, comm_round + 1)`