training deep leaning models #plot the loss curve and roc curve plt figure(figsize=( , )plt subplot( plt plot(loss_listplt title('loss across epochs'plt ylabel('loss'plt xlabel('epochs'plt subplot( #validation fpr_vtpr_v_ roc_curve(y_testy_test_prob detach(numpy()roc_auc_v auc(fpr_vtpr_v#training fpr_ttpr_t_ roc_curve(y_trainy_train_prob detach(numpy()roc_auc_t auc(fpr_ttpr_tplt title('receiver operating characteristic:validation'plt plot(fpr_vtpr_v' 'label 'validation auc % froc_auc_vplt plot(fpr_ttpr_t' 'label 'training auc % froc_auc_tplt legend(loc 'lower right'plt plot([ ][ ],' --'plt xlim([ ]plt ylim([ ]plt ylabel('true positive rate'plt xlabel('false positive rate'plt show(