pytorch wav2vec2 automatic-speech-recognition ru dataset:SberDevices/Golos transformers audio speech xlsr-fine-tuning-week license:apache-2.0 model-index
---
language: ru
datasets:
- SberDevices/Golos
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Russian by Ivan Bondarenko
  results:
  - task:
      name: Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Sberdevices Golos (crowd)
      type: SberDevices/Golos
      args: ru
    metrics:
       - name: Test WER
         type: wer
         value: 9.85
       - name: Test CER
         type: cer
         value: 2.36
  - task:
      name: Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Sberdevices Golos (farfield)
      type: SberDevices/Golos
      args: ru
    metrics:
       - name: Test WER
         type: wer
         value: 20.64
       - name: Test CER
         type: cer
         value: 5.55
---

# Wav2Vec2-Large-Ru-Golos

Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Russian using the [Sberdevices Golos](https://huggingface.co/datasets/SberDevices/Golos).
When using this model, make sure that your speech input is sampled at 16kHz.

## Citation
If you want to cite this model you can use this:

```bibtex
@misc{bondarenko2022wav2vec2-large-ru-golos,
  title={XLSR Wav2Vec2 Russian by Ivan Bondarenko},
  author={Bondarenko, Ivan},
  publisher={Hugging Face},
  journal={Hugging Face Hub},
  howpublished={\url{https://huggingface.co/bond005/wav2vec2-large-ru-golos}},
  year={2022}
}
```