Upload QuartzNet_FT15x5_Maltese.yaml

QuartzNet_FT15x5_Maltese.yaml

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+name: &name "QuartzNet15x5"
+
+model:
+  sample_rate: &sample_rate 16000
+  repeat: &repeat 5
+  dropout: &dropout 0.0
+  separable: &separable true
+  labels: &labels [" ", "'", "-", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z", "à", "á", "è", "é", "ì", "í", "ò", "ó", "ù", "ú", "ċ", "ġ", "ħ", "ż"]
+
+  train_ds:
+    manifest_filepath: ???
+    sample_rate: 16000
+    labels: *labels
+    batch_size: 16
+    trim_silence: True
+    max_duration: 16.7
+    shuffle: True
+    num_workers: 8
+    pin_memory: true
+    # 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
+    labels: *labels
+    batch_size: 16
+    shuffle: False
+    num_workers: 8
+    pin_memory: true
+
+  preprocessor:
+    _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor
+    normalize: "per_feature"
+    window_size: 0.02
+    sample_rate: *sample_rate
+    window_stride: 0.01
+    window: "hann"
+    features: &n_mels 64
+    n_fft: 512
+    frame_splicing: 1
+    dither: 1.0e-05
+
+  spec_augment:
+    _target_: nemo.collections.asr.modules.SpectrogramAugmentation
+    rect_freq: 50
+    rect_masks: 5
+    rect_time: 120
+
+  encoder:
+    _target_: nemo.collections.asr.modules.ConvASREncoder
+    feat_in: *n_mels
+    activation: relu
+    conv_mask: true
+
+    jasper:
+    #1
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [33]
+      repeat: 1
+      residual: false
+      separable: *separable
+      stride: [2]
+    #2
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [33]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #3
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [33]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #4
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [33]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #5
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [39]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #6
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [39]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #7
+    - dilation: [1]
+      dropout: *dropout
+      filters: 256
+      kernel: [39]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #8
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [51]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #9
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [51]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #10
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [51]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #11
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [63]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #12
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [63]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #13
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [63]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #14
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [75]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #15
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [75]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #16
+    - dilation: [1]
+      dropout: *dropout
+      filters: 512
+      kernel: [75]
+      repeat: *repeat
+      residual: true
+      separable: *separable
+      stride: [1]
+    #17
+    - dilation: [2]
+      dropout: *dropout
+      filters: 512
+      kernel: [87]
+      repeat: 1
+      residual: false
+      separable: *separable
+      stride: [1]
+    #18
+    - dilation: [1]
+      dropout: *dropout
+      filters: &enc_filters 1024
+      kernel: [1]
+      repeat: 1
+      residual: false
+      stride: [1]
+
+  decoder:
+    _target_: nemo.collections.asr.modules.ConvASRDecoder
+    feat_in: *enc_filters
+    num_classes: 43
+    vocabulary: *labels
+
+  optim:
+    name: novograd
+    # _target_: nemo.core.optim.optimizers.Novograd
+    lr: 0.0012
+    # optimizer arguments
+    betas: [0.95, 0.25]
+    weight_decay: 0.001
+
+    # scheduler setup
+    sched:
+      name: CosineAnnealing
+
+      # pytorch lightning args
+      # monitor: val_loss
+      # reduce_on_plateau: false
+
+      # Scheduler params
+      warmup_steps: null
+      warmup_ratio: null
+      min_lr: 0.0
+      last_epoch: -1
+
+trainer:
+  devices: 1 # number of gpus
+  max_epochs: 5
+  max_steps: -1 # computed at runtime if not set
+  num_nodes: 1
+  accelerator: gpu
+  strategy: ddp
+  accumulate_grad_batches: 1
+  enable_checkpointing: False  # Provided by exp_manager
+  logger: False  # Provided by exp_manager
+  log_every_n_steps: 1  # 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
+  benchmark: false # needs to be false for models with variable-length speech input as it slows down training
+
+exp_manager:
+  exp_dir: null
+  name: *name
+  create_tensorboard_logger: True
+  create_checkpoint_callback: True
+  checkpoint_callback_params:
+    monitor: "val_wer"
+    mode: "min"
+  create_wandb_logger: False
+  wandb_logger_kwargs:
+    name: null
+    project: null
+