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#!/usr/bin/env bash |
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python run_flax_speech_recognition_seq2seq.py \ |
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--dataset_name="esc-benchmark/esc-datasets" \ |
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--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \ |
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--dataset_config_name="ami" \ |
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--output_dir="./" \ |
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--wandb_name="wav2vec2-aed-common-voice" \ |
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--wandb_project="wav2vec2-aed" \ |
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--per_device_train_batch_size="8" \ |
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--per_device_eval_batch_size="2" \ |
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--learning_rate="1e-4" \ |
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--warmup_steps="500" \ |
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--logging_steps="25" \ |
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--max_steps="50000" \ |
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--eval_steps="10000" \ |
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--save_steps="10000" \ |
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--generation_max_length="200" \ |
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--generation_num_beams="5" \ |
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--generation_length_penalty="1.2" \ |
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--max_eval_duration_in_seconds="20" \ |
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--overwrite_output_dir \ |
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--gradient_checkpointing \ |
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--freeze_feature_encoder \ |
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--predict_with_generate \ |
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--do_eval \ |
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--do_train \ |
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--do_predict \ |
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--push_to_hub \ |
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--use_auth_token |
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