Log parameters from SGDClassfier for Logistic Regression model in python

Question

I fit a Logistic regression model with SGDClassifier using the loss as 'log loss' and setting the log level verbose = 1.

 clf = SGDClassifier(loss='log',random_state=123,verbose=1)
 clf.fit(X,Y)

The logs I got where as below

-- Epoch 1 Norm: 30075.68, NNZs: 3, Bias: 15.380843, T: 200, Avg. loss: 245306398.448941 Total training time: 0.00 seconds. -- Epoch 2 Norm: 27972.51, NNZs: 3, Bias: -69.971163, T: 400, Avg. loss: 213504329.868022 Total training time: 0.00 seconds. -- Epoch 3 Norm: 77152.19, NNZs: 3, Bias: -129.169105, T: 600, Avg. loss: 141240838.989763 Total training time: 0.00 seconds. -- Epoch 4 Norm: 45522.49, NNZs: 3, Bias: -117.146703, T: 800, Avg. loss: 171279669.044693 Total training time: 0.01 seconds.

Can I please know what parameters like Norm, NNZ and T mean in the above logs.

Thank you.