---
base_model: facebook/wav2vec2-xls-r-300m
language: 
  - uk
license: "apache-2.0"
tags:
- automatic-speech-recognition
datasets:
- mozilla-foundation/common_voice_10_0
metrics:
  - wer
model-index:
  - name: w2v-xls-r-uk
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_10_0
          type: common_voice_10_0
          config: uk
          split: test
          args: uk
        metrics:
          - name: WER
            type: wer
            value: 20.24
          - name: CER
            type: cer
            value: 3.64
---

🚨🚨🚨 **ATTENTION!** 🚨🚨🚨

**Use an updated model**: https://huggingface.co/Yehor/w2v-bert-uk-v2.1

---

## Community

- Discord: https://bit.ly/discord-uds
- Speech Recognition: https://t.me/speech_recognition_uk
- Speech Synthesis: https://t.me/speech_synthesis_uk

See other Ukrainian models: https://github.com/egorsmkv/speech-recognition-uk

## Evaluation results

Metrics (float16) using `evaluate` library with `batch_size=1`:

- WER: 0.2024 metric, 20.24%
- CER: 0.0364 metric, 3.64%
- Accuracy on words: 79.76%
- Accuracy on chars: 96.36%
- Inference time: 63.4848 seconds
- Audio duration: 16665.5212 seconds
- RTF: 0.0038

## Cite this work

```
@misc {smoliakov_2025,
	author       = { {Smoliakov} },
	title        = { w2v-xls-r-uk (Revision 55b6dc0) },
	year         = 2025,
	url          = { https://huggingface.co/Yehor/w2v-xls-r-uk },
	doi          = { 10.57967/hf/4556 },
	publisher    = { Hugging Face }
}
```