readme: ---
  language:
  - da
  license: other
  tasks:
  - automatic-speech-recognition
  datasets:
  - ftspeech
  metrics:
  - wer
  model-index:
  - name: wav2vec2-xls-r-300m-ftspeech
    results:
    - task: 
        type: automatic-speech-recognition
      dataset:
        type: mozilla-foundation/common_voice_8_0
        args: da
        name: Danish Common Voice 8.0
      metrics:
        - type: wer
          value: 17.91
    - task: 
        type: automatic-speech-recognition
      dataset:
        type: Alvenir/alvenir_asr_da_eval
        name: Alvenir ASR test dataset
      metrics:
        - type: wer
          value: 13.84
  ---
  
  # XLS-R-300m-FTSpeech
  
  ## Model description
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [FTSpeech dataset](https://ftspeech.github.io/), being a dataset of 1,800 hours of transcribed speeches from the Danish parliament.
  
  
  ## Performance
  
  The model achieves the following WER scores (lower is better):
  
  | **Dataset** | **WER without LM** | **WER with 5-gram LM** |
  | :---:   | ---: | ---: |
  | [Danish part of Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0/viewer/da/train) | 20.48 | 17.91 |
  | [Alvenir test set](https://huggingface.co/datasets/Alvenir/alvenir_asr_da_eval) | 15.46 | 13.84 |
  
  
  ## License
  
  The use of this model needs to adhere to [this license from the Danish Parliament](https://www.ft.dk/da/aktuelt/tv-fra-folketinget/deling-og-rettigheder).