command:
- python3
- ${program}
- --overwrite_output_dir
- --freeze_feature_encoder
- --predict_with_generate
- --do_lower_case
- --do_train
- --do_eval
- ${args}
method: random
metric:
  goal: minimize
  name: eval/wer
parameters:
  dataset_cache_dir:
    value: /home/sanchitgandhi/cache/huggingface/datasets
  dataset_config_name:
    value: clean
  dataset_name:
    value: librispeech_asr
  eval_split_name:
    value: validation
  eval_steps:
    value: 500
  generation_max_length:
    value: 40
  generation_num_beams:
    value: 1
  gradient_accumulation_steps:
    value: 1
  gradient_checkpointing:
    value: True
  learning_rate:
    distribution: log_uniform
    max: -6.9
    min: -9.2
  length_column_name:
    value: input_length
  logging_steps:
    value: 25
  max_duration_in_seconds:
    value: 20
  max_target_length:
    value: 128
  model_name_or_path:
    value: ./
  num_train_epochs:
    value: 3
  output_dir:
    value: ./output_dir
  per_device_eval_batch_size:
    value: 2
  per_device_train_batch_size:
    value: 1
  preprocessing_num_workers:
    value: 16
  text_column_name:
    value: text
  train_split_name:
    value: train.100
  warmup_steps:
    value: 500
program: run_flax_speech_recognition_seq2seq.py
project: flax-wav2vec2-2-bart-large-checkpointing-scan