super-gradients/src/super_gradients/recipes/imagenet_mobilenetv3_large.yaml

# MobileNetV3 Large Imagenet classification training:
# TODO: Add metrics
#
# Instructions:
#   0. Make sure that the data is stored in dataset_params.dataset_dir or add "dataset_params.data_dir=<PATH-TO-DATASET>" at the end of the command below (feel free to check ReadMe)
#   1. Move to the project root (where you will find the ReadMe and src folder)
#   2. Run the command:
#       python src/super_gradients/examples/train_from_recipe_example/train_from_recipe.py --config-name=imagenet_mobilenetv3_large


defaults:
  - imagenet_mobilenetv3_base
  - arch_params: mobilenet_v3_large_arch_params

arch_params:
  num_classes: 1000
  dropout: 0.2

experiment_name: mobileNetv3_large_training

architecture: mobilenet_v3_large


# THE FOLLOWING PARAMS ARE DIRECTLY USED BY HYDRA
hydra:
  run:
    # Set the output directory (i.e. where .hydra folder that logs all the input params will be generated)
    dir: ${hydra_output_dir:${ckpt_root_dir}, ${experiment_name}}