name: mBert stanzas evaluation
project: stanzas-mbert-eval
program: stanzas_eval.py
command:
  - ${env}
  - ${interpreter}
  - ${program}
  - ${args}
method: grid
metric:
  name: eval:f1_macro
  goal: maximize
parameters:
  dataset_name:
    value: linhd-postdata/stanzas
  task_name:
    value: sequence
  model_name:
    value: bert-base-multilingual-cased
  # force_download:
  #   value: true
  num_train_epochs:
    value: 3
  # warmup_steps:
  #   value: 0.1
  weight_decay:
    value: 0.0
  learning_rate:
    value: 3e-5
  train_batch_size:
    value: 8
  cache_dir:
    value: ./cache
  output_dir:
    value: ./output
  save_artifacts:
    value: true
  # run:
  #   values: [1, 2, 3]