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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
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