asr-crdnn-rnnlm-commonvoice-10.0-de / lm_hyperparams.yaml

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	# Generated 2022-08-17 from:
	# /netscratch/sagar/thesis/speechbrain/recipes/CommonVoice_de/LM/hparams/RNNLM.yaml
	# yamllint disable
	# ############################################################################
	# Model: RNNLM of E2E ASR
	# Tokens: unigram/char
	# losses: NLL
	# Training: Librispeech 960h transcript + LM corpus
	# Authors: Ju-Chieh Chou 2020, Jianyuan Zhong 2021
	# ############################################################################

	# Seed needs to be set at top of yaml, before objects with parameters are made
	seed: 2995
	__set_seed: !apply:torch.manual_seed [2995]
	output_folder: results/RNN/2995
	save_folder: results/RNN/2995/save
	train_log: results/RNN/2995/train_log.txt

	# Data files
	# The data_folder is needed because we train the LM on the training
	# transcriptions of LibriSpeech as well.
	data_folder: ../cv_de_acc/

	# path to the lm_corpus
	# if set to null, it will automatically download from the internet
	# in the case when there is no internet access, set this to your local file
	lm_corpus_path: lm_corpus/orignal_data/de_lm_normalized.txt # 17M sentences


	# Tokenizer model
	tokenizer_file: ../Tokenizer/results/unigram/1000_unigram.model

	# Training parameters
	number_of_epochs: 20
	batch_size: 128
	lr: 0.001
	accu_steps: 1 # Gradient accumulation to simulate large batch training
	ckpt_interval_minutes: 15 # save checkpoint every N min

	# Dataloader options
	train_dataloader_opts:
	batch_size: 128
	shuffle: true

	valid_dataloader_opts:
	batch_size: 1

	test_dataloader_opts:
	batch_size: 1

	# Model parameters
	emb_size: 128
	activation: &id001 !name:torch.nn.LeakyReLU
	dropout: 0.0
	rnn_layers: 2
	rnn_neurons: 2048
	dnn_blocks: 1
	dnn_neurons: 512

	# Outputs
	output_neurons: 1000 # index(blank/eos/bos) = 0 \| char: 32 \| unigram: 1000
	# blank_index: 0
	bos_index: 0
	eos_index: 0


	# Functions
	model: &id002 !new:speechbrain.lobes.models.RNNLM.RNNLM

	output_neurons: 1000
	embedding_dim: 128
	activation: *id001
	dropout: 0.0
	rnn_layers: 2
	rnn_neurons: 2048
	dnn_blocks: 1
	dnn_neurons: 512

	modules:
	model: *id002
	checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
	checkpoints_dir: results/RNN/2995/save
	recoverables:
	model: *id002
	scheduler: &id003 !new:speechbrain.nnet.schedulers.NewBobScheduler
	initial_value: 0.001
	improvement_threshold: 0.0025
	annealing_factor: 0.8
	patient: 0

	counter: &id004 !new:speechbrain.utils.epoch_loop.EpochCounter

	limit: 20

	log_softmax: !new:speechbrain.nnet.activations.Softmax
	apply_log: true

	optimizer: !name:torch.optim.Adam
	lr: 0.001
	betas: (0.9, 0.98)
	eps: 0.000000001

	lr_annealing: *id003
	epoch_counter: *id004
	compute_cost: !name:speechbrain.nnet.losses.nll_loss

	train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
	save_file: results/RNN/2995/train_log.txt

	tokenizer: &id005 !new:sentencepiece.SentencePieceProcessor

	pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
	collect_in: results/RNN/2995/save
	loadables:
	tokenizer: *id005
	paths:
	tokenizer: ../Tokenizer/results/unigram/1000_unigram.model