code: def transformer_librispeech_v2():
    
    hparams = transformer_base()
  
    hparams.max_length = 1240000
    hparams.max_input_seq_length = 1550
    hparams.max_target_seq_length = 350
    hparams.batch_size = 16
    hparams.num_decoder_layers = 4
    hparams.num_encoder_layers = 6
    hparams.hidden_size = 384
    hparams.learning_rate = 0.15
    hparams.daisy_chain_variables = False
    hparams.filter_size = 1536
    hparams.num_heads = 2
    hparams.ffn_layer = "conv_relu_conv"
    hparams.conv_first_kernel = 9
    hparams.weight_decay = 0
    hparams.layer_prepostprocess_dropout = 0.2
    hparams.relu_dropout = 0.2
  
    return hparams
docs: HParams for training ASR model on LibriSpeech V2.