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--- |
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language: |
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- en |
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tags: |
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- esc |
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datasets: |
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- switchboard |
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--- |
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To reproduce this run, first call `get_ctc_tokenizer.py` to train the CTC tokenizer and then execute the following command to train the CTC system: |
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```python |
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#!/usr/bin/env bash |
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python run_flax_speech_recognition_ctc.py \ |
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--model_name_or_path="esc-benchmark/wav2vec2-ctc-pretrained" \ |
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--tokenizer_name="wav2vec2-ctc-switchboard-tokenizer" \ |
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--dataset_name="esc-benchmark/esc-datasets" \ |
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--dataset_config_name="switchboard" \ |
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--output_dir="./" \ |
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--wandb_project="wav2vec2-ctc" \ |
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--wandb_name="wav2vec2-ctc-switchboard" \ |
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--max_steps="50000" \ |
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--save_steps="10000" \ |
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--eval_steps="10000" \ |
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--learning_rate="3e-4" \ |
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--logging_steps="25" \ |
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--warmup_steps="5000" \ |
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--preprocessing_num_workers="1" \ |
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--do_train \ |
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--do_eval \ |
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--do_predict \ |
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--overwrite_output_dir \ |
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--gradient_checkpointing \ |
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--freeze_feature_encoder \ |
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--push_to_hub \ |
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--use_auth_token |
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``` |
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