 It provides default values for each parameter, such as the training batch size and learning rate, but you can also set your own values in the training command if you’d like. For example, to activate gradient accumulation, add the --gradient_accumulation_steps parameter to the training command:   Copied accelerate launch train_t2i_adapter_sdxl.py \
  ----gradient_accumulation_steps=4 Many of the basic and important parameters are described in t