write_basic_config() Lastly, if you want to train a model on your own dataset, take a look at the Create a dataset for training guide to learn how to create a dataset that works with the training script.  Script parameters The following sections highlight parts of the training script that are important for understanding how to modify it, but it doesn’t cover every aspect of the script in detail. If you’re interested in learning more, feel free to read through the script and let us know if you have any questions or concerns. The training script provides many parameters to help you customize your training run. All of the parameters and their descriptions are found in the parse_args() function. This function 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 speedup training with mixed precision using the fp16 format, add the --mixed_precision parameter to the training command:   Copied accelerate launch train_text_to_image.py \