modrec-workflow/conf/app.yaml

general:
  # Run mode. Options are 'prod' or 'dev'.
  run_mode: prod

dataset:
  #where to read the recordings from to produce the data set
  input_dir: data/recordings

  #number of slices you want to split each recording into
  num_slices: 8

  #training/val split between the 2 data sets
  train_split: 0.8
  val_split : 0.2

  #used to initialize a random number generator.
  seed: 25

  #multiple modulations to contain in the dataset
  modulation_types: [bpsk, qpsk, qam16, qam64]

  #where to output the datasets
  output_dir: data/dataset

training:
  #number of training samples being processed together before model updates its weights
  batch_size: 256
  
  #number of passes through the data set during the training process
  epochs: 5

  #how much the weights update during training after every batch
  #suggested range for fine-tuning: (1e-6, 1e-4)
  learning_rate: 1e-4

  use_gpu: true

inference:
  #num classes to classify on
  num_classes: 4


app:
  build_dir: dist