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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def transformer_tall_finetune_textclass():
 """Hparams for transformer on LM for finetuning on text class problems."""

  hparams = transformer_tall()
  hparams.learning_rate_constant = 6.25e-5
  hparams.learning_rate_schedule = ("linear_warmup*constant*linear_decay")
  hparams.multiproblem_schedule_max_examples = 0
  hparams.multiproblem_target_eval_only = True
  hparams.learning_rate_warmup_steps = 50
  # Set train steps to learning_rate_decay_steps or less
  hparams.learning_rate_decay_steps = 25000
  hparams.multiproblem_reweight_label_loss = True
  hparams.multiproblem_label_weight = 0.95
  return hparams