In the tensorflow implementation you reference, they use:
train_step = tf.train.RMSPropOptimizer(0.001, 0.9).minimize(cost)
Did you try with these parameters ? In your code, it would be:
optimizer = optim.RMSprop(model.parameters(), lr=0.001, weight_decay=0.9)
Maybe you just need to increase the L2 regularization (weight decay)