At text classification example

[atuzhykov]

What changes were proposed in this pull request?

(Please fill in changes proposed in this fix)

How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)

Please review
https://github.com/eclipse/deeplearning4j/blob/master/CONTRIBUTING.md before opening a pull request.

[AlexDBlack]

Looking good, just a few minor improvements to make.
Can we also make a backup of the branch, then flatten + sign on this branch as described here: https://deeplearning4j.org/eclipse-contributors

Otherwise I'm happy with this 👍

[AlexDBlack]

Maybe let's improve this slightly, add another line under 0.:
BertIterator and BertWordPieceTokenizer implement the Word Piece sub-word tokenization algorithm, with a vocabulary size of 30522 tokens.

[AlexDBlack]

Maybe let's comment out the UI by default, as it adds some overhead (slows down training a bit). Users can uncomment it if they want to run it with UI. That would look like this:

        /*
        //Uncomment this section to run the example with the user interface
        UIServer uiServer = UIServer.getInstance();

        //Configure where the network information (gradients, activations, score vs. time etc) is to be stored
        //Then add the StatsListener to collect this information from the network, as it trains
        StatsStorage statsStorage = new FileStatsStorage(new File(System.getProperty("java.io.tmpdir"), "ui-stats-" + System.currentTimeMillis() + ".dl4j"));
        int listenerFrequency = 20;
        net.setListeners(new StatsListener(statsStorage, listenerFrequency), new ScoreIterationListener(50));
        //Attach the StatsStorage instance to the UI: this allows the contents of the StatsStorage to be visualized
        uiServer.attach(statsStorage);
        */
        
        net.setListeners(new ScoreIterationListener(50));

[AlexDBlack]

For MultiLayerNetwork, we can use net.evaluate(test)

[AlexDBlack]

Leave this commented out with 10.2