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transformers/examples/research_projects/wav2vec2/README.md
Patrick von Platen 0234de8418
Add Fine-Tuning for Wav2Vec2 (#10145) 
* 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>
2021-03-01 12:13:17 +03:00

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Fine-tuning Wav2Vec2

The run_training.py script allows one to finetune pretrained Wav2Vec2 models that can be found here.

This finetuning script can also be run as a google colab TODO: here.

The script is actively maintained by Patrick von Platen. Feel free to ask a question on the Forum or post an issue on GitHub and adding @patrickvonplaten as a tag.