citrinet_1024.yaml

# This config contains the default values for training a Citrinet model with CTC loss and BPE-based vocabulary.
# Default learning parameters in this config are set for effective batch size of 1k on 32 GPUs.
# To train it with smaller batch sizes, you may need to re-tune the learning parameters or use higher accumulate_grad_batches.
# If training for a short time, you can also reduce weight decay to 0.

# Training Recipe
# This model can be trained using the default settings in this config with FP32 precision.
# When training under AMP, increase `warmup_steps` to 5000 for stable training.
# In order to create Citrinet-C, change the model.model_defaults.filters parameter.
# When reducing the receptive field of these models, it is advised to reduce the amount of augmentation
# for larger models from 10x time masking to 5x or 2x time masking.
# For further details regarding Citrinet, visit - https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/configs.html#citrinet

name: &name "Citrinet-1024-8x-Stride"

model:
  sample_rate: &sample_rate 16000
  log_prediction: true # enables logging sample predictions in the output during training

  train_ds:
    manifest_filepath: ???
    sample_rate: 16000
    batch_size: 32
    trim_silence: false
    max_duration: 20.0
    shuffle: true
    use_start_end_token: false
    # tarred datasets
    is_tarred: false
    tarred_audio_filepaths: null
    shuffle_n: 2048
    # bucketing params
    bucketing_strategy: "synced_randomized"
    bucketing_batch_size: null

  validation_ds:
    manifest_filepath: ???
    sample_rate: 16000
    batch_size: 32
    shuffle: false
    use_start_end_token: false

  test_ds:
    manifest_filepath: null
    sample_rate: 16000
    batch_size: 32
    shuffle: false
    use_start_end_token: false

  model_defaults:
    repeat: 5
    dropout: 0.1
    separable: true
    se: true
    se_context_size: -1
    kernel_size_factor: 0.25
    filters: 1024
    enc_final: 1024

  tokenizer:
    dir: ???  # path to directory which contains either tokenizer.model (bpe) or vocab.txt (for wpe)
    type: ???  # Can be either bpe or wpe

  preprocessor:
    _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor
    sample_rate: *sample_rate
    normalize: "per_feature"
    window_size: 0.025
    window_stride: 0.01
    window: "hann"
    features: &n_mels 80
    n_fft: 512
    frame_splicing: 1
    dither: 0.00001
    pad_to: 16
    stft_conv: false

  spec_augment:
    _target_: nemo.collections.asr.modules.SpectrogramAugmentation
    freq_masks: 2
    time_masks: 10
    freq_width: 27
    time_width: 0.05

  encoder:
    _target_: nemo.collections.asr.modules.ConvASREncoder
    feat_in: *n_mels
    activation: relu
    conv_mask: true

    jasper:
      - filters: ${model.model_defaults.filters}
        repeat: 1
        kernel: [5]
        stride: [1]
        dilation: [1]
        dropout: 0.0
        residual: false
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [11]
        stride: [2]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        stride_last: true
        residual_mode: "stride_add"
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [13]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [15]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [17]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [19]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [21]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [13]
        stride: [2]  # *stride
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        stride_last: true
        residual_mode: "stride_add"
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [15]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [17]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [19]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [21]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [23]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [25]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [25]
        stride: [2]  # stride
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        stride_last: true
        residual_mode: "stride_add"
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}


      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [27]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [29]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [31]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [33]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [35]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [37]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.filters}
        repeat: ${model.model_defaults.repeat}
        kernel: [39]
        stride: [1]
        dilation: [1]
        dropout: ${model.model_defaults.dropout}
        residual: true
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}



      - filters: ${model.model_defaults.enc_final}
        repeat: 1
        kernel: [41]
        stride: [1]
        dilation: [1]
        dropout: 0.0
        residual: false
        separable: ${model.model_defaults.separable}
        se: ${model.model_defaults.se}
        se_context_size: ${model.model_defaults.se_context_size}
        kernel_size_factor: ${model.model_defaults.kernel_size_factor}


  decoder:
    _target_: nemo.collections.asr.modules.ConvASRDecoder
    feat_in: ${model.model_defaults.enc_final}
    num_classes: -1  # filled with vocabulary size from tokenizer at runtime
    vocabulary: []  # filled with vocabulary from tokenizer at runtime


  optim:
    name: novograd
    lr: 0.05

    # optimizer arguments
    betas: [0.8, 0.25]
    weight_decay: 0.001

    # scheduler setup
    sched:
      name: CosineAnnealing

      # scheduler config override
      warmup_steps: 5000
      warmup_ratio: null
      min_lr: 1e-5
      last_epoch: -1

trainer:
  gpus: 0 # number of gpus
  max_epochs: 100
  max_steps: null # computed at runtime if not set
  num_nodes: 1
  accelerator: ddp
  accumulate_grad_batches: 1
  checkpoint_callback: false  # Provided by exp_manager
  logger: false  # Provided by exp_manager
  log_every_n_steps: 100  # Interval of logging.
  val_check_interval: 1.0 # Set to 0.25 to check 4 times per epoch, or an int for number of iterations
  check_val_every_n_epoch: 1
  precision: 32
  sync_batchnorm: false
  benchmark: false

exp_manager:
  exp_dir: null
  name: *name
  create_tensorboard_logger: true
  create_checkpoint_callback: true
  checkpoint_callback_params:
    monitor: "val_wer"
    mode: "min"
    save_top_k: 3
  create_wandb_logger: false
  wandb_logger_kwargs:
    name: null
    project: null
    entity: null
  resume_if_exists: false
  resume_ignore_no_checkpoint: false

hydra:
  run:
    dir: .
  job_logging:
    root:
      handlers: null