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sweep over models/freeze  
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command:
  - python3
  - ${program}
  - --load_best_model_at_end
  - --fp16
  - --do_train
  - --do_eval
  - --trust_remote_code
  - --overwrite_output_dir
  - ${args}
method: grid
metric:
  goal: minimize
  name: eval/accuracy
parameters:
  model_name_or_path:
    values:
      - facebook/mms-lid-126
      - openai/whisper-large-v3
      - facebook/w2v-bert-2.0
  train_dataset_name:
    value: sanchit-gandhi/vctk+facebook/voxpopuli+sanchit-gandhi/edacc
  train_dataset_config_name:
    value: default+en_accented+default
  train_split_name:
    value: train+test+validation
  train_label_column_name:
    value: accent+accent+accent
  eval_dataset_name:
    value: sanchit-gandhi/edacc
  eval_dataset_config_name:
    value: default
  eval_split_name:
    value: test
  eval_label_column_name:
    value: accent
  output_dir:
    value: ./
  remove_unused_columns:
    value: false
  learning_rate:
    value: 1e-4
  max_length_seconds:
    value: 20
  attention_mask:
    value: false
  warmup_ratio:
    value: 0.1
  num_train_epochs:
    value: 5
  per_device_train_batch_size:
    value: 32
  per_device_eval_batch_size:
    value: 32
  preprocessing_num_workers:
    value: 16
  dataloader_num_workers:
    value: 4
  logging_strategy:
    value: steps
  logging_steps:
    value: 10
  evaluation_strategy:
    value: epoch
  save_strategy:
    value: epoch
  metric_for_best_model:
    value: accuracy
  save_total_limit:
    value: 3
  freeze_base_model:
    values:
      - true
      - false
  push_to_hub:
    value: false
program: run_audio_classification.py
project: mms-lid-accent-classification