Wav files and its corresponding text files should be present in the same folder with same name. eg - audio_id/audio.wav, audio_id/audio.txt
make_valid_from_train : If valid set is already present in different folder make this 0 else make it 1 to extract valid percentage from train data
train_wav_path: Directory where your train data(wav files) is present, if wav files are present in multiple folders put them under one parent directory
valid_wav_path: Used only when 'make_valid_from_train' is 0; directory where your valid data(wav files) is present, if wav files are present in multiple folders put them under one parent directory
valid_percentage: Used only when 'make_valid_from_train' is 1; percentage of data to be used for validation purpose. eg - 0.04 if 4%
prep_scripts: Path for utility scripts
config_name: This file contains configurable parameters for finetuning
gpus: Number of gpus to use
run_in_nohup: Make it 1 for running training in background
data_path: Contains files made from running prepare_data.sh
checkpoints_path Directory to save checkpoints generated after each epoch during finetuning. eg- checkpoint_best, checkpoint_last
log_path: nohup.out is saved here as <timestamp_of_running>.out
tensordboard_path: Path where tensorboard logs are to be saved
pretrained_model_path: Path of checkpoint_best.pt generate from pretraining
update_freq: To simulate n gpus by k gpus update frequency will be [n/k]
wav2vec_repo_path: Path of fairseq repository