use_gpu: True
device: 0
seed: 12345
outdir: exp/
federate:
  mode: standalone
  method: fedavg
  total_round_num: 200
  client_num: 18
  save_to: ckpt/
data:
  type: hetero_nlp_tasks
  root: datasets/
  hetero_data_name: ['imdb', 'agnews', 'squad', 'newsqa', 'cnndm', 'msqg']
  num_of_client_for_data: [1, 3, 3, 2, 5, 4]
  max_seq_len: 384
  max_tgt_len: 128
  batch_size: 16
  num_workers: 0
  cache_dir: cache/
model:
  type: atc_model
  model_type: google/bert_uncased_L-2_H-128_A-2
  stage: assign
  task: pretrain
  pretrain_tasks: ['mlm', 'denoise']
aggregator:
  num_agg_groups: 5
  inside_weight: 1.0
  outside_weight: 0.0
personalization:
  local_param: ['classifier']
trainer:
  type: atc_trainer
train:
  batch_or_epoch: batch
  local_update_steps: 50
  optimizer:
    type: AdamW
    lr: 5e-4
    weight_decay: 0.01
  scheduler:
    type: warmup_step
    warmup_ratio: 0.1
grad:
  grad_clip: 1.0
  grad_accum_count: 4
eval:
  metrics: ['acc']
  split: ['test']
  report: ['raw']
  freq: 100000000  # eval freq across rounds