code: def transformer_tall_finetune_textclass():
    
    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
docs: Hparams for transformer on LM for finetuning on text class problems.