Update hyperparams.yaml

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	# ############################################################################
	# Model: E2E ASR with Transformer
	# Encoder: Conformer Encoder
	# Decoder: Transformer Decoder + (CTC/ATT joint) beamsearch + TransformerLM
	# Tokens: unigram
	# losses: CTC + KLdiv (Label Smoothing loss)
	# Training: KsponSpeech 965.2h
	# Based on the works of: Jianyuan Zhong, Titouan Parcollet 2021
	# Authors: Dongwon Kim, Dongwoo Kim 2021
	# ############################################################################
	# Seed needs to be set at top of yaml, before objects with parameters are made

	# Feature parameters
	sample_rate: 16000
	n_fft: 400
	n_mels: 80

	####################### Model parameters ###########################
	# Transformer
	d_model: 256
	nhead: 4
	num_encoder_layers: 12
	num_decoder_layers: 6
	d_ffn: 2048
	transformer_dropout: 0.1
	activation: !name:torch.nn.GELU
	output_neurons: 5000
	vocab_size: 5000

	# Outputs
	blank_index: 0
	pad_index: 0
	bos_index: 1
	eos_index: 2
	unk_index: 0

	# Decoding parameters
	min_decode_ratio: 0.0
	max_decode_ratio: 1.0
	test_beam_size: 66
	lm_weight: 0.60
	ctc_weight_decode: 0.50

	############################## models ################################

	normalizer: !new:speechbrain.processing.features.InputNormalization
	norm_type: global

	CNN: !new:speechbrain.lobes.models.convolution.ConvolutionFrontEnd
	input_shape: (8, 10, 80)
	num_blocks: 3
	num_layers_per_block: 1
	out_channels: (64, 64, 64)
	kernel_sizes: (5, 5, 1)
	strides: (2, 2, 1)
	residuals: (False, False, True)

	Transformer: !new:speechbrain.lobes.models.transformer.TransformerASR.TransformerASR # yamllint disable-line rule:line-length
	input_size: 1280
	tgt_vocab: !ref <output_neurons>
	d_model: !ref <d_model>
	nhead: !ref <nhead>
	num_encoder_layers: !ref <num_encoder_layers>
	num_decoder_layers: !ref <num_decoder_layers>
	d_ffn: !ref <d_ffn>
	dropout: !ref <transformer_dropout>
	activation: !ref <activation>
	encoder_module: conformer
	attention_type: RelPosMHAXL
	normalize_before: True
	causal: False

	# NB: It has to match the pre-trained TransformerLM!!
	lm_model: !new:speechbrain.lobes.models.transformer.TransformerLM.TransformerLM # yamllint disable-line rule:line-length
	vocab: !ref <output_neurons>
	d_model: 768
	nhead: 12
	num_encoder_layers: 12
	num_decoder_layers: 0
	d_ffn: 3072
	dropout: 0.0
	activation: !name:torch.nn.GELU
	normalize_before: False

	tokenizer: !new:sentencepiece.SentencePieceProcessor

	ctc_lin: !new:speechbrain.nnet.linear.Linear
	input_size: !ref <d_model>
	n_neurons: !ref <output_neurons>

	seq_lin: !new:speechbrain.nnet.linear.Linear
	input_size: !ref <d_model>
	n_neurons: !ref <output_neurons>

	transformerlm_scorer: !new:speechbrain.decoders.scorer.TransformerLMScorer
	language_model: !ref <lm_model>
	temperature: 1.15

	ctc_scorer: !new:speechbrain.decoders.scorer.CTCScorer
	eos_index: !ref <eos_index>
	blank_index: !ref <blank_index>
	ctc_fc: !ref <ctc_lin>

	scorer: !new:speechbrain.decoders.scorer.ScorerBuilder
	full_scorers: [!ref <transformerlm_scorer>, !ref <ctc_scorer>]
	weights:
	transformerlm: !ref <lm_weight>
	ctc: !ref <ctc_weight_decode>

	decoder: !new:speechbrain.decoders.S2STransformerBeamSearcher
	modules: [!ref <Transformer>, !ref <seq_lin>]
	bos_index: !ref <bos_index>
	eos_index: !ref <eos_index>
	min_decode_ratio: !ref <min_decode_ratio>
	max_decode_ratio: !ref <max_decode_ratio>
	beam_size: !ref <test_beam_size>
	temperature: 1.15
	using_eos_threshold: False
	length_normalization: True
	scorer: !ref <scorer>


	Tencoder: !new:speechbrain.lobes.models.transformer.TransformerASR.EncoderWrapper
	transformer: !ref <Transformer>

	encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
	input_shape: [null, null, !ref <n_mels>]
	compute_features: !ref <compute_features>
	normalize: !ref <normalizer>
	cnn: !ref <CNN>
	transformer_encoder: !ref <Tencoder>

	asr_model: !new:torch.nn.ModuleList
	- [!ref <CNN>, !ref <Transformer>, !ref <seq_lin>, !ref <ctc_lin>]

	log_softmax: !new:torch.nn.LogSoftmax
	dim: -1


	compute_features: !new:speechbrain.lobes.features.Fbank
	sample_rate: !ref <sample_rate>
	n_fft: !ref <n_fft>
	n_mels: !ref <n_mels>

	modules:
	compute_features: !ref <compute_features>
	normalizer: !ref <normalizer>
	pre_transformer: !ref <CNN>
	transformer: !ref <Transformer>
	asr_model: !ref <asr_model>
	lm_model: !ref <lm_model>
	encoder: !ref <encoder>
	decoder: !ref <decoder>

	# The pretrainer allows a mapping between pretrained files and instances that
	# are declared in the yaml.
	pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
	loadables:
	normalizer: !ref <normalizer>
	asr: !ref <asr_model>
	lm: !ref <lm_model>
	tokenizer: !ref <tokenizer>