# https://yaml.org/type/float.html ############################################ # Network Architecture # ############################################ cmvn_file: "data/mean_std.json" cmvn_file_type: "json" # encoder related encoder: conformer 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 use_cnn_module: True cnn_module_kernel: 15 activation_type: 'swish' pos_enc_layer_type: 'rel_pos' selfattention_layer_type: 'rel_selfattn' # 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: ctc_weight: 0.3 lsm_weight: 0.1 # label smoothing option length_normalized_loss: false ########################################### # Data # ########################################### train_manifest: data/manifest.tiny dev_manifest: data/manifest.tiny test_manifest: data/manifest.tiny ########################################### # Dataloader # ########################################### mean_std_filepath: "" vocab_filepath: data/lang_char/vocab.txt unit_type: 'spm' spm_model_prefix: 'data/lang_char/bpe_unigram_200' preprocess_config: conf/preprocess.yaml feat_dim: 80 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 batch_size: 4 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 num_workers: 0 subsampling_factor: 1 num_encs: 1 ########################################### # Training # ########################################### n_epoch: 5 accum_grad: 4 global_grad_clip: 5.0 optim: adam optim_conf: lr: 0.002 weight_decay: 1.0e-06 scheduler: warmuplr scheduler_conf: warmup_steps: 25000 lr_decay: 1.0 log_interval: 1 checkpoint: kbest_n: 10 latest_n: 1