Hparams for transformer on LM pretraining (with 64k vocab).

def transformer_tall_pretrain_lm():
  """Hparams for transformer on LM pretraining (with 64k vocab)."""
  hparams = transformer_tall()
  hparams.learning_rate_constant = 2e-4
  hparams.learning_rate_schedule = ("linear_warmup*constant*cosdecay")
  hparams.optimizer = "adam_w"
  hparams.optimizer_adam_beta1 = 0.9
  hparams.optimizer_adam_beta2 = 0.999
  hparams.optimizer_adam_epsilon = 1e-8
  # Set max examples to something big when pretraining only the LM, definitely
  # something an order of magnitude bigger than number of train steps.
  hparams.multiproblem_schedule_max_examples = 5e8
  # Set train steps to learning_rate_decay_steps or less
  hparams.learning_rate_decay_steps = 5000000
  return hparams