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