• Configuration settings in the editable fields: 
    • Number of Epochs: Determines how many times to train over the entire dataset 
    • Batch Size: Dictates how many samples to process at once. Limited by GPU DRAM. 
    • Learning Rate: Determines the step size to train the model. Too low a number of trains slowly and too high a value would overshoot the optimal solution and perform poorly. 
    • Training configuration recommended values:


  • **25 epochs is recommended if training with 3 or more classes (Not including Unknown) 
  • The T-SDK makes use of the machine’s multiple CPU cores to train at a faster rate.  The user can adjust CPU usage through the cpu_cores_train parameter. The default value to this parameter is cpu_cores_train = 2, which utilizes 50% of the CPU. Using higher values of cpu_cores_train may induce T-SDK instability

train 2

  • Training seeds: Set training_seed1, training_seed2, and training_seed3 from value 0 to 999, recommended setting to 0 
  • Initialize tab (optional): Select initialized weights to start a new training 

train 3