train.yml

model_params:
  fp16: false       # general flag
  model: FinetuneImage   # model from NETWORKS to use
  img_encoder:
     arch: inception_v4
     num_classes: 340
     pretrained: True

args:
  workers: 4
  model_dir: "quickdraw"
  baselogdir: "./logs/quickdraw"
#  resume: "./logs/inception_v4/checkpoint.best.pth.tar"

stages:
  criterion_params:
    criterion: CrossEntropyLoss

  data_params:
    train_split: "/media/ngxbac/Bac/competition/kaggle/competition_data/quickdraw/data/100k_clean/train/"
    train_token: "/media/ngxbac/Bac/competition/kaggle/competition_data/quickdraw/data/100k_clean/train/"

    valid_split: "/media/ngxbac/Bac/competition/kaggle/competition_data/quickdraw/data/100k_clean/valid/"
    valid_token: "/media/ngxbac/Bac/competition/kaggle/competition_data/quickdraw/data/100k_clean/valid/"

  callbacks_params:
    map_args: [3]

  # train head
  stage1:
    args:
      epochs: 6
      batch_size: 128
      image_size: 256

    optimizer_params:
      optimizer: Adam
      lr: 0.00001
      weight_decay: 0.0001

    scheduler_params:
      scheduler: StepLR
      step_size: 4
      gamma: 0.1

    data_params:
      reload_loaders: true