if iteration % 100 == 0:
                print('Epoch: {}/{}'.format(e, 200),
                      'Iteration: {}'.format(iteration),
                      'Loss: {}'.format(loss_value))

            if iteration % 1000 == 0:
                predict(device, net, flags.initial_words, n_vocab,
                        vocab_to_int, int_to_vocab, top_k=5)
                torch.save(net.state_dict(),
                           'checkpoint_pt/model-{}.pth'.format(iteration))