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* 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>
5 lines
43 B
Plaintext
5 lines
43 B
Plaintext
transformers
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datasets
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torch >= 1.5.0
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jiwer
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