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143 lines
3.5 KiB
143 lines
3.5 KiB
2 years ago
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############################################
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# Network Architecture #
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############################################
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freeze_hubert: False
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normalize_wav: True
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output_norm: True
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init_type: kaiming_uniform # !Warning: need to convergence
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enc:
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input_shape: 1024
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dnn_blocks: 2
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dnn_neurons: 1024
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activation: True
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ctc:
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enc_n_units: 1024
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blank_id: 0
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dropout_rate: 0.0
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hubert_params_path: "exp/hubert/hubert-large-lv60.pdparams"
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task_cfg:
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label_rate: 50.0
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sample_rate: 16000
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normalize: True
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enable_padding: False
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max_keep_size: None
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max_sample_size: 250000
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min_sample_size: 32000
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single_target: False
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random_crop: True
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pad_audio: False
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model_cfg:
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dropout_input: 0.0
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final_dropout: 0.0
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dropout: 0.0
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attention_dropout: 0.0
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activation_dropout: 0.1
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apply_mask: True
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mask_length: 10
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mask_prob: 0.5
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mask_selection: static
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mask_other: 0.0
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no_mask_overlap: False
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mask_channel_length: 64
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mask_channel_prob: 0.25
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mask_channel_selection: static
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mask_channel_other: 0.0
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no_mask_channel_overlap: False
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feature_grad_mult: 0.0
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layerdrop: 0.1
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normalize: True
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fp16: True
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label_rate: 50
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extractor_mode: layer_norm
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encoder_layers: 24
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encoder_embed_dim: 1024
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encoder_ffn_embed_dim: 4096
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encoder_attention_heads: 16
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activation_fn: gelu
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encoder_layerdrop: 0.1
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dropout_features: 0.0
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final_dim: 768
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untie_final_proj: True
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layer_norm_first: True
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conv_feature_layers: "[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2"
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conv_bias: False
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logit_temp: 0.1
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target_glu: False
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mask_min_space: 1
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mask_channel_min_space: 1
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conv_pos: 128
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conv_pos_groups: 16
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latent_temp: [2.0, 0.5, 0.999995]
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skip_masked: False
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skip_nomask: True
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###########################################
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# Data #
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###########################################
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train_manifest: data/manifest.train-clean-100
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dev_manifest: data/manifest.dev
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test_manifest: data/manifest.test-clean
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###########################################
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# Dataloader #
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###########################################
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vocab_filepath: data/lang_char/vocab.txt
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unit_type: char
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mean_std_filepath: ""
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preprocess_config: conf/preprocess.yaml
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sortagrad: -1 # Feed samples from shortest to longest ; -1: enabled for all epochs 0: disabled other: enabled for other epochs
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batch_size: 4 # Different batch_size may cause large differences in results
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maxlen_in: 1500 # 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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num_workers: 0
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subsampling_factor: 1
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num_encs: 1
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dist_sampler: True
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shortest_first: True
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return_lens_rate: True
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############################################
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# Data Augmentation #
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############################################
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audio_augment: # for raw audio
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sample_rate: 16000
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speeds: [95, 100, 105]
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###########################################
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# Training #
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###########################################
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n_epoch: 3
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accum_grad: 8
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global_grad_clip: 5.0
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model_optim: adadelta
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model_optim_conf:
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lr: 1.0
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epsilon: 1.0e-6
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rho: 0.95
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model_scheduler: constantlr
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model_scheduler_conf:
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warmup_steps: 25000
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lr_decay: 1.0
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hubert_optim: adadelta
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hubert_optim_conf:
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lr: 0.95
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epsilon: 1.0e-6
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rho: 0.95
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hubert_scheduler: constantlr
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hubert_scheduler_conf:
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warmup_steps: 25000
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lr_decay: 1.0
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log_interval: 1
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checkpoint:
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kbest_n: 50
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latest_n: 5
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