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0234de8418
* add encode labels function to tokenizer * start adding finetuning * init dropout * upload * correct convert script * apply changes * fix second typo * make first dummy training run * adapt convert script * push confg for comparison * remove conf * finish training * adapt data collator * add research folder * update according to fairseq feedback * some minor corrections * refactor masking indices a bit * some minor changes * clean tokenizer * finish clean-up * remove previous logic * update run script * correct training * finish changes * finish model * correct bug * fix training a bit more * add some tests * finish gradient checkpointing * finish example * correct gradient checkpointing * improve tokenization method * revert changes in tokenizer * revert general change * adapt fine-tuning * update * save intermediate test * Update README.md * finish finetuning * delete conversion script * Update src/transformers/models/wav2vec2/configuration_wav2vec2.py * Update src/transformers/models/wav2vec2/processing_wav2vec2.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * finish wav2vec2 script * finish wav2vec2 fine-tuning * finalize test * correct test * adapt tests * finish * remove test file Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
22 lines
587 B
Bash
Executable File
22 lines
587 B
Bash
Executable File
#!/usr/bin/env bash
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python run_asr.py \
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--output_dir="./wav2vec2-base-100h" \
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--num_train_epochs="30" \
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--per_device_train_batch_size="32" \
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--per_device_eval_batch_size="32" \
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--evaluation_strategy="steps" \
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--save_total_limit="3" \
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--save_steps="500" \
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--eval_steps="100" \
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--logging_steps="50" \
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--learning_rate="5e-4" \
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--warmup_steps="3000" \
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--model_name_or_path="facebook/wav2vec2-base" \
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--fp16 \
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--dataset_name="librispeech_asr" \
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--dataset_config_name="clean" \
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--train_split_name="train.100" \
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--preprocessing_num_workers="32" \
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--group_by_length \
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--freeze_feature_extractor
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