|
#!/usr/bin/env bash |
|
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \ |
|
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \ |
|
--model_name_or_path="stt_en_conformer_transducer_xlarge" \ |
|
--dataset_name="esc-benchmark/esc-datasets" \ |
|
--tokenizer_path="tokenizer" \ |
|
--vocab_size="1024" \ |
|
--max_steps="100000" \ |
|
--dataset_config_name="librispeech" \ |
|
--output_dir="./" \ |
|
--run_name="conformer-rnnt-librispeech" \ |
|
--wandb_project="rnnt" \ |
|
--per_device_train_batch_size="8" \ |
|
--per_device_eval_batch_size="4" \ |
|
--logging_steps="50" \ |
|
--learning_rate="1e-4" \ |
|
--warmup_steps="500" \ |
|
--save_strategy="steps" \ |
|
--save_steps="20000" \ |
|
--evaluation_strategy="steps" \ |
|
--eval_steps="20000" \ |
|
--report_to="wandb" \ |
|
--preprocessing_num_workers="4" \ |
|
--fused_batch_size="4" \ |
|
--length_column_name="input_lengths" \ |
|
--fuse_loss_wer \ |
|
--group_by_length \ |
|
--overwrite_output_dir \ |
|
--do_train \ |
|
--do_eval \ |
|
--do_predict \ |
|
--use_auth_token |
|
|
