class_docstr: Test of Bert biencoder and crossencoder.
  
  Checks that Both Biencoder and CrossEncoder of Bert can be trained for about 100
  samples on convai2
code: def test_bertclassifier(self):
      valid, test = testing_utils.train_model(
          dict(
              task="integration_tests:classifier",
              model="bert_classifier/bert_classifier",
              num_epochs=2,
              batchsize=2,
              learningrate=1e-2,
              gradient_clip=1.0,
              classes=["zero", "one"],
          )
      )
      self.assertGreaterEqual(test["accuracy"], 0.9)
  
file_path: ParlAI/tests/nightly/gpu/test_bert.py
imports: import unittest
  import parlai.utils.testing
  import torch
label_desc: Use image node_id 4 for calling the TestBertModel obj's underlying member method code with example usage: obj.test_bertclassifier() without return types