readme: ---
  language:
  - nl
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - nl
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-large-xls-r-1b-nl
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: nl
      metrics:
      - name: Test WER
        type: wer
        value: 11.12
      - name: Test CER
        type: cer
        value: 3.2
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: nl
      metrics:
      - name: Test WER
        type: wer
        value: 31.92
      - name: Test CER
        type: cer
        value: 13.87
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: nl
      metrics:
      - name: Test WER
        type: wer
        value: 32.17
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # 
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - NL dataset. This model is also available with a language model which improves these results. This model can be found at https://huggingface.co/RuudVelo/wav2vec2-large-xls-r-1b-nl-lm. The Common Voice 8 Dutch test Wer is 9.73 of that model. 
  It achieves the following results on the evaluation set:
  - Loss: 0.1479
  - Wer: 0.1156
  
  ## Model description
  
  Model fine-tuned using the wav2vec-als-r-1b model architecture
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  Model has been trained on Common Voice 8 Dutch
  
  ## Training procedure
  
  ### Training hyperparameters
  
  Model parameters can be found under Files and versions in the run.sh file.
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 1.2223        | 0.52  | 500   | 0.3866          | 0.3425 |
  | 1.0748        | 1.03  | 1000  | 0.2574          | 0.2169 |
  | 1.0416        | 1.55  | 1500  | 0.2177          | 0.1946 |
  | 0.9951        | 2.06  | 2000  | 0.2008          | 0.1760 |
  | 0.975         | 2.58  | 2500  | 0.1961          | 0.1751 |
  | 0.9461        | 3.1   | 3000  | 0.1989          | 0.1782 |
  | 0.9381        | 3.61  | 3500  | 0.1928          | 0.1699 |
  | 0.934         | 4.13  | 4000  | 0.1923          | 0.1633 |
  | 0.9322        | 4.64  | 4500  | 0.1871          | 0.1634 |
  | 0.9012        | 5.16  | 5000  | 0.1890          | 0.1702 |
  | 0.9045        | 5.68  | 5500  | 0.1882          | 0.1740 |
  | 0.8826        | 6.19  | 6000  | 0.1856          | 0.1575 |
  | 0.8848        | 6.71  | 6500  | 0.1861          | 0.1617 |
  | 0.8723        | 7.22  | 7000  | 0.1927          | 0.1646 |
  | 0.8725        | 7.74  | 7500  | 0.1798          | 0.1531 |
  | 0.8573        | 8.26  | 8000  | 0.1781          | 0.1587 |
  | 0.8633        | 8.77  | 8500  | 0.1852          | 0.1628 |
  | 0.8603        | 9.29  | 9000  | 0.1833          | 0.1601 |
  | 0.8421        | 9.8   | 9500  | 0.1788          | 0.1543 |
  | 0.8404        | 10.32 | 10000 | 0.1844          | 0.1556 |
  | 0.8342        | 10.84 | 10500 | 0.1770          | 0.1538 |
  | 0.8161        | 11.35 | 11000 | 0.1821          | 0.1567 |
  | 0.8371        | 11.87 | 11500 | 0.1909          | 0.1629 |
  | 0.8083        | 12.38 | 12000 | 0.1778          | 0.1498 |
  | 0.806         | 12.9  | 12500 | 0.1802          | 0.1547 |
  | 0.8013        | 13.42 | 13000 | 0.1859          | 0.1584 |
  | 0.7913        | 13.93 | 13500 | 0.1875          | 0.1517 |
  | 0.8063        | 14.45 | 14000 | 0.1799          | 0.1571 |
  | 0.7991        | 14.96 | 14500 | 0.1792          | 0.1538 |
  | 0.7843        | 15.48 | 15000 | 0.1753          | 0.1464 |
  | 0.7905        | 16.0  | 15500 | 0.1784          | 0.1508 |
  | 0.7808        | 16.51 | 16000 | 0.1771          | 0.1485 |
  | 0.7743        | 17.03 | 16500 | 0.1795          | 0.1491 |
  | 0.7833        | 17.54 | 17000 | 0.1722          | 0.1484 |
  | 0.7763        | 18.06 | 17500 | 0.1767          | 0.1518 |
  | 0.7698        | 18.58 | 18000 | 0.1720          | 0.1460 |
  | 0.7571        | 19.09 | 18500 | 0.1735          | 0.1478 |
  | 0.7673        | 19.61 | 19000 | 0.1817          | 0.1511 |
  | 0.7415        | 20.12 | 19500 | 0.1763          | 0.1481 |
  | 0.751         | 20.64 | 20000 | 0.1742          | 0.1484 |
  | 0.7563        | 21.16 | 20500 | 0.1810          | 0.1611 |
  | 0.7423        | 21.67 | 21000 | 0.1817          | 0.155