python run_flax_speech_recognition_seq2seq.py \ | |
--dataset_name="esc-benchmark/esc-datasets" \ | |
--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \ | |
--dataset_config_name="chime4" \ | |
--output_dir="./" \ | |
--wandb_name="wav2vec2-aed-chime4" \ | |
--wandb_project="wav2vec2-aed" \ | |
--per_device_train_batch_size="8" \ | |
--per_device_eval_batch_size="4" \ | |
--logging_steps="25" \ | |
--max_steps="50001" \ | |
--eval_steps="10000" \ | |
--save_steps="10000" \ | |
--generation_max_length="40" \ | |
--generation_num_beams="1" \ | |
--final_generation_max_length="250" \ | |
--final_generation_num_beams="5" \ | |
--generation_length_penalty="0.6" \ | |
--learning_rate="1e-4" \ | |
--warmup_steps="500" \ | |
--hidden_dropout="0.2" \ | |
--activation_dropout="0.2" \ | |
--feat_proj_dropout="0.2" \ | |
--overwrite_output_dir \ | |
--gradient_checkpointing \ | |
--freeze_feature_encoder \ | |
--predict_with_generate \ | |
--do_eval \ | |
--do_train \ | |
--do_predict \ | |
--push_to_hub \ | |
--use_auth_token |