parent
70166c2026
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# https://yaml.org/type/float.html
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###########################################
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# Data #
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###########################################
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train_manifest: data/manifest.de.train
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dev_manifest: data/manifest.de.dev
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test_manifest: data/manifest.de.test
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###########################################
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# Dataloader #
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###########################################
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vocab_filepath: data/lang_1spm/train_sp.en-de.de_bpe8000_units_tc.txt
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unit_type: 'spm'
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spm_model_prefix: data/lang_1spm/train_sp.en-de.de_bpe8000_tc
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mean_std_filepath: ""
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# preprocess_config: conf/augmentation.json
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batch_size: 20
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feat_dim: 83
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stride_ms: 10.0
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window_ms: 25.0
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sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
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maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
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maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
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minibatches: 0 # for debug
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batch_count: auto
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batch_bins: 0
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batch_frames_in: 0
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batch_frames_out: 0
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batch_frames_inout: 0
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preprocess_config:
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num_workers: 0
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subsampling_factor: 1
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num_encs: 1
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############################################
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# Network Architecture #
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############################################
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cmvn_file: None
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cmvn_file_type: "json"
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# encoder related
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encoder: transformer
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encoder_conf:
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output_size: 256 # dimension of attention
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attention_heads: 4
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linear_units: 2048 # the number of units of position-wise feed forward
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num_blocks: 12 # the number of encoder blocks
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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attention_dropout_rate: 0.0
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input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
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normalize_before: true
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# decoder related
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decoder: transformer
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decoder_conf:
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attention_heads: 4
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linear_units: 2048
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num_blocks: 6
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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self_attention_dropout_rate: 0.0
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src_attention_dropout_rate: 0.0
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# hybrid CTC/attention
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model_conf:
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asr_weight: 0.0
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ctc_weight: 0.0
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lsm_weight: 0.1 # label smoothing option
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length_normalized_loss: false
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###########################################
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# Training #
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###########################################
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n_epoch: 40
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accum_grad: 2
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global_grad_clip: 5.0
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optim: adam
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optim_conf:
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lr: 2.5
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weight_decay: 0.
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scheduler: noam
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scheduler_conf:
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warmup_steps: 25000
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lr_decay: 1.0
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log_interval: 50
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checkpoint:
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kbest_n: 50
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latest_n: 5
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# https://yaml.org/type/float.html
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###########################################
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# Data #
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###########################################
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train_manifest: data/manifest.es.train
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dev_manifest: data/manifest.es.dev
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test_manifest: data/manifest.es.test
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###########################################
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# Dataloader #
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###########################################
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vocab_filepath: data/lang_1spm/train_sp.en-es.es_bpe8000_units_tc.txt
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unit_type: 'spm'
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spm_model_prefix: data/lang_1spm/train_sp.en-es.es_bpe8000_tc
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mean_std_filepath: ""
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# preprocess_config: conf/augmentation.json
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batch_size: 20
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feat_dim: 83
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stride_ms: 10.0
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window_ms: 25.0
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sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
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maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
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maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
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minibatches: 0 # for debug
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batch_count: auto
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batch_bins: 0
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batch_frames_in: 0
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batch_frames_out: 0
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batch_frames_inout: 0
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preprocess_config:
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num_workers: 0
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subsampling_factor: 1
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num_encs: 1
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############################################
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# Network Architecture #
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############################################
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cmvn_file: None
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cmvn_file_type: "json"
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# encoder related
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encoder: transformer
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encoder_conf:
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output_size: 256 # dimension of attention
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attention_heads: 4
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linear_units: 2048 # the number of units of position-wise feed forward
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num_blocks: 12 # the number of encoder blocks
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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attention_dropout_rate: 0.0
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input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
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normalize_before: true
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# decoder related
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decoder: transformer
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decoder_conf:
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attention_heads: 4
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linear_units: 2048
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num_blocks: 6
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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self_attention_dropout_rate: 0.0
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src_attention_dropout_rate: 0.0
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# hybrid CTC/attention
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model_conf:
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asr_weight: 0.0
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ctc_weight: 0.0
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lsm_weight: 0.1 # label smoothing option
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length_normalized_loss: false
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###########################################
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# Training #
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###########################################
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n_epoch: 40
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accum_grad: 2
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global_grad_clip: 5.0
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optim: adam
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optim_conf:
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lr: 2.5
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weight_decay: 0.
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scheduler: noam
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scheduler_conf:
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warmup_steps: 25000
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lr_decay: 1.0
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log_interval: 50
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checkpoint:
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kbest_n: 50
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latest_n: 5
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# https://yaml.org/type/float.html
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###########################################
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# Data #
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###########################################
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train_manifest: data/manifest.fr.train
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dev_manifest: data/manifest.fr.dev
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test_manifest: data/manifest.fr.test
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###########################################
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# Dataloader #
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###########################################
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vocab_filepath: data/lang_1spm/train_sp.en-fr.fr_bpe8000_units_tc.txt
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unit_type: 'spm'
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spm_model_prefix: data/lang_1spm/train_sp.en-fr.fr_bpe8000_tc
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mean_std_filepath: ""
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# preprocess_config: conf/augmentation.json
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batch_size: 20
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feat_dim: 83
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stride_ms: 10.0
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window_ms: 25.0
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sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
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maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
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maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
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minibatches: 0 # for debug
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batch_count: auto
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batch_bins: 0
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batch_frames_in: 0
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batch_frames_out: 0
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batch_frames_inout: 0
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preprocess_config:
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num_workers: 0
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subsampling_factor: 1
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num_encs: 1
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############################################
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# Network Architecture #
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############################################
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cmvn_file: None
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cmvn_file_type: "json"
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# encoder related
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encoder: transformer
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encoder_conf:
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output_size: 256 # dimension of attention
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attention_heads: 4
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linear_units: 2048 # the number of units of position-wise feed forward
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num_blocks: 12 # the number of encoder blocks
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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attention_dropout_rate: 0.0
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input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
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normalize_before: true
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# decoder related
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decoder: transformer
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decoder_conf:
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attention_heads: 4
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linear_units: 2048
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num_blocks: 6
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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self_attention_dropout_rate: 0.0
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src_attention_dropout_rate: 0.0
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# hybrid CTC/attention
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model_conf:
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asr_weight: 0.0
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ctc_weight: 0.0
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lsm_weight: 0.1 # label smoothing option
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length_normalized_loss: false
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###########################################
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# Training #
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###########################################
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n_epoch: 40
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accum_grad: 2
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global_grad_clip: 5.0
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optim: adam
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optim_conf:
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lr: 2.5
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weight_decay: 0.
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scheduler: noam
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scheduler_conf:
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warmup_steps: 25000
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lr_decay: 1.0
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log_interval: 50
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checkpoint:
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kbest_n: 50
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latest_n: 5
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# https://yaml.org/type/float.html
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###########################################
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# Data #
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###########################################
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train_manifest: data/manifest.it.train
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dev_manifest: data/manifest.it.dev
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test_manifest: data/manifest.it.test
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###########################################
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# Dataloader #
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###########################################
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vocab_filepath: data/lang_1spm/train_sp.en-it.it_bpe8000_units_tc.txt
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unit_type: 'spm'
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spm_model_prefix: data/lang_1spm/train_sp.en-it.it_bpe8000_tc
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mean_std_filepath: ""
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# preprocess_config: conf/augmentation.json
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batch_size: 20
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feat_dim: 83
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stride_ms: 10.0
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window_ms: 25.0
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sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
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maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
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maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
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minibatches: 0 # for debug
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batch_count: auto
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batch_bins: 0
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batch_frames_in: 0
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batch_frames_out: 0
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batch_frames_inout: 0
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preprocess_config:
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num_workers: 0
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subsampling_factor: 1
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num_encs: 1
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############################################
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# Network Architecture #
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############################################
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cmvn_file: None
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cmvn_file_type: "json"
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# encoder related
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encoder: transformer
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encoder_conf:
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output_size: 256 # dimension of attention
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attention_heads: 4
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linear_units: 2048 # the number of units of position-wise feed forward
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num_blocks: 12 # the number of encoder blocks
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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attention_dropout_rate: 0.0
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input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
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normalize_before: true
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# decoder related
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decoder: transformer
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decoder_conf:
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attention_heads: 4
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linear_units: 2048
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num_blocks: 6
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dropout_rate: 0.1
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positional_dropout_rate: 0.1
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self_attention_dropout_rate: 0.0
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src_attention_dropout_rate: 0.0
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# hybrid CTC/attention
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model_conf:
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asr_weight: 0.0
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ctc_weight: 0.0
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lsm_weight: 0.1 # label smoothing option
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length_normalized_loss: false
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###########################################
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# Training #
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###########################################
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n_epoch: 40
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accum_grad: 2
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global_grad_clip: 5.0
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optim: adam
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optim_conf:
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lr: 2.5
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weight_decay: 0.
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scheduler: noam
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scheduler_conf:
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warmup_steps: 25000
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lr_decay: 1.0
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log_interval: 50
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checkpoint:
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kbest_n: 50
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latest_n: 5
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# https://yaml.org/type/float.html
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###########################################
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# Data #
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###########################################
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train_manifest: data/manifest.nl.train
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dev_manifest: data/manifest.nl.dev
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test_manifest: data/manifest.nl.test
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###########################################
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# Dataloader #
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###########################################
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vocab_filepath: data/lang_1spm/train_sp.en-nl.nl_bpe8000_units_tc.txt
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unit_type: 'spm'
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spm_model_prefix: data/lang_1spm/train_sp.en-nl.nl_bpe8000_tc
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mean_std_filepath: ""
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# preprocess_config: conf/augmentation.json
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batch_size: 20
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feat_dim: 83
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stride_ms: 10.0
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window_ms: 25.0
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sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
|
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maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
|
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maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
|
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minibatches: 0 # for debug
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batch_count: auto
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batch_bins: 0
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batch_frames_in: 0
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batch_frames_out: 0
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batch_frames_inout: 0
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preprocess_config:
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num_workers: 0
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subsampling_factor: 1
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num_encs: 1
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############################################
|
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# Network Architecture #
|
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############################################
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cmvn_file: None
|
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cmvn_file_type: "json"
|
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# encoder related
|
||||
encoder: transformer
|
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encoder_conf:
|
||||
output_size: 256 # dimension of attention
|
||||
attention_heads: 4
|
||||
linear_units: 2048 # the number of units of position-wise feed forward
|
||||
num_blocks: 12 # the number of encoder blocks
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
attention_dropout_rate: 0.0
|
||||
input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
|
||||
normalize_before: true
|
||||
|
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# decoder related
|
||||
decoder: transformer
|
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decoder_conf:
|
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attention_heads: 4
|
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linear_units: 2048
|
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num_blocks: 6
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
self_attention_dropout_rate: 0.0
|
||||
src_attention_dropout_rate: 0.0
|
||||
|
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# hybrid CTC/attention
|
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model_conf:
|
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asr_weight: 0.0
|
||||
ctc_weight: 0.0
|
||||
lsm_weight: 0.1 # label smoothing option
|
||||
length_normalized_loss: false
|
||||
|
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|
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###########################################
|
||||
# Training #
|
||||
###########################################
|
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n_epoch: 40
|
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accum_grad: 2
|
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global_grad_clip: 5.0
|
||||
optim: adam
|
||||
optim_conf:
|
||||
lr: 2.5
|
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weight_decay: 0.
|
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scheduler: noam
|
||||
scheduler_conf:
|
||||
warmup_steps: 25000
|
||||
lr_decay: 1.0
|
||||
log_interval: 50
|
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checkpoint:
|
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kbest_n: 50
|
||||
latest_n: 5
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@ -0,0 +1,90 @@
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# https://yaml.org/type/float.html
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###########################################
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# Data #
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###########################################
|
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train_manifest: data/manifest.pt.train
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dev_manifest: data/manifest.pt.dev
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test_manifest: data/manifest.pt.test
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|
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###########################################
|
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# Dataloader #
|
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###########################################
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vocab_filepath: data/lang_1spm/train_sp.en-pt.pt_bpe8000_units_tc.txt
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unit_type: 'spm'
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spm_model_prefix: data/lang_1spm/train_sp.en-pt.pt_bpe8000_tc
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mean_std_filepath: ""
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# preprocess_config: conf/augmentation.json
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batch_size: 20
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feat_dim: 83
|
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stride_ms: 10.0
|
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window_ms: 25.0
|
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sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
|
||||
maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
|
||||
maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
|
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minibatches: 0 # for debug
|
||||
batch_count: auto
|
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batch_bins: 0
|
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batch_frames_in: 0
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batch_frames_out: 0
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batch_frames_inout: 0
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preprocess_config:
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num_workers: 0
|
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subsampling_factor: 1
|
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num_encs: 1
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|
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|
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############################################
|
||||
# Network Architecture #
|
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############################################
|
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cmvn_file: None
|
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cmvn_file_type: "json"
|
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# encoder related
|
||||
encoder: transformer
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encoder_conf:
|
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output_size: 256 # dimension of attention
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attention_heads: 4
|
||||
linear_units: 2048 # the number of units of position-wise feed forward
|
||||
num_blocks: 12 # the number of encoder blocks
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
attention_dropout_rate: 0.0
|
||||
input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
|
||||
normalize_before: true
|
||||
|
||||
# decoder related
|
||||
decoder: transformer
|
||||
decoder_conf:
|
||||
attention_heads: 4
|
||||
linear_units: 2048
|
||||
num_blocks: 6
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
self_attention_dropout_rate: 0.0
|
||||
src_attention_dropout_rate: 0.0
|
||||
|
||||
# hybrid CTC/attention
|
||||
model_conf:
|
||||
asr_weight: 0.0
|
||||
ctc_weight: 0.0
|
||||
lsm_weight: 0.1 # label smoothing option
|
||||
length_normalized_loss: false
|
||||
|
||||
|
||||
###########################################
|
||||
# Training #
|
||||
###########################################
|
||||
n_epoch: 40
|
||||
accum_grad: 2
|
||||
global_grad_clip: 5.0
|
||||
optim: adam
|
||||
optim_conf:
|
||||
lr: 2.5
|
||||
weight_decay: 0.
|
||||
scheduler: noam
|
||||
scheduler_conf:
|
||||
warmup_steps: 25000
|
||||
lr_decay: 1.0
|
||||
log_interval: 50
|
||||
checkpoint:
|
||||
kbest_n: 50
|
||||
latest_n: 5
|
@ -0,0 +1,90 @@
|
||||
# https://yaml.org/type/float.html
|
||||
###########################################
|
||||
# Data #
|
||||
###########################################
|
||||
train_manifest: data/manifest.ro.train
|
||||
dev_manifest: data/manifest.ro.dev
|
||||
test_manifest: data/manifest.ro.test
|
||||
|
||||
###########################################
|
||||
# Dataloader #
|
||||
###########################################
|
||||
vocab_filepath: data/lang_1spm/train_sp.en-ro.ro_bpe8000_units_tc.txt
|
||||
unit_type: 'spm'
|
||||
spm_model_prefix: data/lang_1spm/train_sp.en-ro.ro_bpe8000_tc
|
||||
mean_std_filepath: ""
|
||||
# preprocess_config: conf/augmentation.json
|
||||
batch_size: 20
|
||||
feat_dim: 83
|
||||
stride_ms: 10.0
|
||||
window_ms: 25.0
|
||||
sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
|
||||
maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
|
||||
maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
|
||||
minibatches: 0 # for debug
|
||||
batch_count: auto
|
||||
batch_bins: 0
|
||||
batch_frames_in: 0
|
||||
batch_frames_out: 0
|
||||
batch_frames_inout: 0
|
||||
preprocess_config:
|
||||
num_workers: 0
|
||||
subsampling_factor: 1
|
||||
num_encs: 1
|
||||
|
||||
|
||||
############################################
|
||||
# Network Architecture #
|
||||
############################################
|
||||
cmvn_file: None
|
||||
cmvn_file_type: "json"
|
||||
# encoder related
|
||||
encoder: transformer
|
||||
encoder_conf:
|
||||
output_size: 256 # dimension of attention
|
||||
attention_heads: 4
|
||||
linear_units: 2048 # the number of units of position-wise feed forward
|
||||
num_blocks: 12 # the number of encoder blocks
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
attention_dropout_rate: 0.0
|
||||
input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
|
||||
normalize_before: true
|
||||
|
||||
# decoder related
|
||||
decoder: transformer
|
||||
decoder_conf:
|
||||
attention_heads: 4
|
||||
linear_units: 2048
|
||||
num_blocks: 6
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
self_attention_dropout_rate: 0.0
|
||||
src_attention_dropout_rate: 0.0
|
||||
|
||||
# hybrid CTC/attention
|
||||
model_conf:
|
||||
asr_weight: 0.0
|
||||
ctc_weight: 0.0
|
||||
lsm_weight: 0.1 # label smoothing option
|
||||
length_normalized_loss: false
|
||||
|
||||
|
||||
###########################################
|
||||
# Training #
|
||||
###########################################
|
||||
n_epoch: 40
|
||||
accum_grad: 2
|
||||
global_grad_clip: 5.0
|
||||
optim: adam
|
||||
optim_conf:
|
||||
lr: 2.5
|
||||
weight_decay: 0.
|
||||
scheduler: noam
|
||||
scheduler_conf:
|
||||
warmup_steps: 25000
|
||||
lr_decay: 1.0
|
||||
log_interval: 50
|
||||
checkpoint:
|
||||
kbest_n: 50
|
||||
latest_n: 5
|
@ -0,0 +1,90 @@
|
||||
# https://yaml.org/type/float.html
|
||||
###########################################
|
||||
# Data #
|
||||
###########################################
|
||||
train_manifest: data/manifest.ru.train
|
||||
dev_manifest: data/manifest.ru.dev
|
||||
test_manifest: data/manifest.ru.test
|
||||
|
||||
###########################################
|
||||
# Dataloader #
|
||||
###########################################
|
||||
vocab_filepath: data/lang_1spm/train_sp.en-ru.ru_bpe8000_units_tc.txt
|
||||
unit_type: 'spm'
|
||||
spm_model_prefix: data/lang_1spm/train_sp.en-ru.ru_bpe8000_tc
|
||||
mean_std_filepath: ""
|
||||
# preprocess_config: conf/augmentation.json
|
||||
batch_size: 20
|
||||
feat_dim: 83
|
||||
stride_ms: 10.0
|
||||
window_ms: 25.0
|
||||
sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
|
||||
maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
|
||||
maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
|
||||
minibatches: 0 # for debug
|
||||
batch_count: auto
|
||||
batch_bins: 0
|
||||
batch_frames_in: 0
|
||||
batch_frames_out: 0
|
||||
batch_frames_inout: 0
|
||||
preprocess_config:
|
||||
num_workers: 0
|
||||
subsampling_factor: 1
|
||||
num_encs: 1
|
||||
|
||||
|
||||
############################################
|
||||
# Network Architecture #
|
||||
############################################
|
||||
cmvn_file: None
|
||||
cmvn_file_type: "json"
|
||||
# encoder related
|
||||
encoder: transformer
|
||||
encoder_conf:
|
||||
output_size: 256 # dimension of attention
|
||||
attention_heads: 4
|
||||
linear_units: 2048 # the number of units of position-wise feed forward
|
||||
num_blocks: 12 # the number of encoder blocks
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
attention_dropout_rate: 0.0
|
||||
input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
|
||||
normalize_before: true
|
||||
|
||||
# decoder related
|
||||
decoder: transformer
|
||||
decoder_conf:
|
||||
attention_heads: 4
|
||||
linear_units: 2048
|
||||
num_blocks: 6
|
||||
dropout_rate: 0.1
|
||||
positional_dropout_rate: 0.1
|
||||
self_attention_dropout_rate: 0.0
|
||||
src_attention_dropout_rate: 0.0
|
||||
|
||||
# hybrid CTC/attention
|
||||
model_conf:
|
||||
asr_weight: 0.0
|
||||
ctc_weight: 0.0
|
||||
lsm_weight: 0.1 # label smoothing option
|
||||
length_normalized_loss: false
|
||||
|
||||
|
||||
###########################################
|
||||
# Training #
|
||||
###########################################
|
||||
n_epoch: 40
|
||||
accum_grad: 2
|
||||
global_grad_clip: 5.0
|
||||
optim: adam
|
||||
optim_conf:
|
||||
lr: 2.5
|
||||
weight_decay: 0.
|
||||
scheduler: noam
|
||||
scheduler_conf:
|
||||
warmup_steps: 25000
|
||||
lr_decay: 1.0
|
||||
log_interval: 50
|
||||
checkpoint:
|
||||
kbest_n: 50
|
||||
latest_n: 5
|
Loading…
Reference in new issue