safrooze commented on a change in pull request #11651: Add logistic regression tutorial URL: https://github.com/apache/incubator-mxnet/pull/11651#discussion_r204186229
########## File path: docs/tutorials/gluon/logistic_regression_explained.md ########## @@ -94,21 +90,13 @@ trainer = Trainer(params=net.collect_params(), optimizer='sgd', accuracy = mx.metric.Accuracy() ``` -Usually, it is not enough to pass the training data through a network only once to achieve high Accuracy. It helps when the network sees each example multiple times. The number of displaying every example to the network is called `epoch`. How big this number should be is unknown in advance, and usually it is estimated using trial and error approach. - -Below we are defining the main training loop, which go through each example in batches specified number of times (epochs). After each epoch we display training loss, validation loss and calculate accuracy of the model using validation set. For now, let's take a look into the code, and I am going to explain the details later. +The next step is to define the training function in which we iterate over all batches of training data, execute the forward pass on each batch and calculate training loss. On line 19, we sum losses of every batch per an epoch into a single variable, because we calculate loss per single batch, but want to display it per epoch. Review comment: "batch ***per epoch***" ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
