sweep_custom.yaml

program: train.py
project: xlsr-trainer
method: random
metric:
  name: eval/loss
  goal: minimize
parameters:
  attention_dropout:
    distribution: log_uniform
    # from 0.1/5 to 0.1*5 - values provided are ln(min) -> ln(max)
    min: -3.9
    max: -0.7
  activation_dropout:
    distribution: log_uniform
    min: -3.9
    max: -1.9
  feat_proj_dropout:
    distribution: log_uniform
    min: -3.9
    max: -0.7
  feat_quantizer_dropout:
    distribution: log_uniform
    min: -3.9
    max: -0.7
  final_dropout:
    distribution: log_uniform
    min: -3.9
    max: -0.7
  hidden_dropout:
    distribution: log_uniform
    min: -3.9
    max: -1.9
  learning_rate:
    distribution: log_uniform
    min: -9.2
    max: -6.9
command:
  - python3
  - ${program}
  - "--custom_set"
  - "./custom_data.csv"
  - "--tokenize_config"
  - "voidful/wav2vec2-large-xlsr-53-tw-gpt"
  - "--xlsr_config"
  - "facebook/wav2vec2-xls-r-1b"
  - "--sweep_split_shard"
  - 90
  - "--logging_steps"
  - 10
  - "--eval_steps"
  - 100
  - "--output_dir"
  - "./model_sweep"
  - "--overwrite_output_dir"
  - "--num_train_epochs"
  - 20
  - "--batch"
  - 8
  - ${args}