Thanks for the inputs.Also , after the 500 iteration can  y_pred be taken as resultant probability output ? And utlized for generating confusion matrix from scikit  ? Something like below code snippet  , is fine an approach for metrics computation ?

output_pred = y_pred.detach().numpy()
print "output_pred"
print output_pred
pred_arr = []
for i in range(len(output_pred)):
    if (round(output_pred[i],4) > 0.5000):
        pred_arr.append(1)
    else :
        pred_arr.append(0)

conf_matrix = confusion_matrix(pred_arr, Y_train)