############################################ # Network Architecture # ############################################ freeze_wavlm: False normalize_wav: True output_norm: True init_type: kaiming_uniform # !Warning: need to convergence enc: input_shape: 768 dnn_blocks: 2 dnn_neurons: 768 activation: True normalization: True dropout_rate: [0.15, 0] ctc: enc_n_units: 768 blank_id: 0 dropout_rate: 0.0 wavlm_params_path: exp/wavlm/wavlm-base-plus.pdparams task_cfg: label_rate: 50.0 sample_rate: 16000 normalize: True enable_padding: False max_keep_size: None max_sample_size: 250000 min_sample_size: 32000 dropout_input: 0.1 final_dropout: 0.0 dropout: 0.1 attention_dropout: 0.0 activation_dropout: 0.1 apply_mask: True mask_length: 10 mask_prob: 0.5 mask_selection: static mask_other: 0.0 no_mask_overlap: False mask_channel_length: 10 mask_channel_prob: 0.0 mask_channel_selection: static mask_channel_other: 0.0 no_mask_channel_overlap: False feature_grad_mult: 0.0 layerdrop: 0.1 fp16: True extractor_mode: layer_norm encoder_layers: 12 encoder_embed_dim: 768 encoder_ffn_embed_dim: 3072 encoder_attention_heads: 12 activation_fn: gelu encoder_layerdrop: 0.0 dropout_features: 0.0 final_dim: 768 untie_final_proj: True layer_norm_first: True conv_feature_layers: "[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2" conv_bias: False logit_temp: 0.1 target_glu: False mask_min_space: 1 mask_channel_min_space: 1 conv_pos: 128 conv_pos_groups: 16 latent_temp: [2.0, 0.5, 0.999995] skip_masked: False skip_nomask: True ########################################### # Data # ########################################### train_manifest: data/manifest.train dev_manifest: data/manifest.dev test_manifest: data/manifest.test-clean ########################################### # Dataloader # ########################################### vocab_filepath: data/lang_char/vocab.txt unit_type: char mean_std_filepath: "" preprocess_config: conf/preprocess.yaml sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs 0: disabled other: enabled for other epochs batch_size: 8 # Different batch_size may cause large differences in results maxlen_in: 51200000000 # if input length > maxlen-in batchsize is automatically reduced maxlen_out: 160000 minibatches: 0 # for debug batch_count: auto batch_bins: 0 batch_frames_in: 0 batch_frames_out: 0 batch_frames_inout: 0 num_workers: 0 subsampling_factor: 1 num_encs: 1 dist_sampler: True shortest_first: False return_lens_rate: True ############################################ # Data Augmentation # ############################################ audio_augment: # for raw audio sample_rate: 16000 speeds: [90, 100, 110] ########################################### # Training # ########################################### n_epoch: 10 accum_grad: 8 global_grad_clip: 5.0 model_scheduler: newbobscheduler model_scheduler_conf: improvement_threshold: 0.0025 annealing_factor: 0.8 patient: 0 model_optim: adam model_optim_conf: lr: 0.0001 weight_decay: 0.0 # I changed this wavlm_optim: adam wavlm_optim_conf: lr: 0.00005 weight_decay: 0.0 wavlm_scheduler: constantlr wavlm_scheduler_conf: warmup_steps: 1000 lr_decay: 1.0 log_interval: 1 checkpoint: kbest_n: 50 latest_n: 5