readme: ---
  language:
  - de
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - robust-speech-event
  - de
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: XLS-R-300M - German
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: de
      metrics:
      - name: Test WER
        type: wer
        value: 15.25
      - name: Test CER
        type: cer
        value: 3.78
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: de
      metrics:
      - name: Test WER
        type: wer
        value: 35.29
      - name: Test CER
        type: cer
        value: 13.83
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: de
      metrics:
      - name: Test WER
        type: wer
        value: 36.2
  ---
  
  <!-- 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 - DE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1355
  - Wer: 0.1532
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 7.5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 2.5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 1.0826        | 0.07  | 1000  | 0.4637          | 0.4654 |
  | 1.118         | 0.15  | 2000  | 0.2595          | 0.2687 |
  | 1.1268        | 0.22  | 3000  | 0.2635          | 0.2661 |
  | 1.0919        | 0.29  | 4000  | 0.2417          | 0.2566 |
  | 1.1013        | 0.37  | 5000  | 0.2414          | 0.2567 |
  | 1.0898        | 0.44  | 6000  | 0.2546          | 0.2731 |
  | 1.0808        | 0.51  | 7000  | 0.2399          | 0.2535 |
  | 1.0719        | 0.59  | 8000  | 0.2353          | 0.2528 |
  | 1.0446        | 0.66  | 9000  | 0.2427          | 0.2545 |
  | 1.0347        | 0.73  | 10000 | 0.2266          | 0.2402 |
  | 1.0457        | 0.81  | 11000 | 0.2290          | 0.2448 |
  | 1.0124        | 0.88  | 12000 | 0.2295          | 0.2448 |
  | 1.025         | 0.95  | 13000 | 0.2138          | 0.2345 |
  | 1.0107        | 1.03  | 14000 | 0.2108          | 0.2294 |
  | 0.9758        | 1.1   | 15000 | 0.2019          | 0.2204 |
  | 0.9547        | 1.17  | 16000 | 0.2000          | 0.2178 |
  | 0.986         | 1.25  | 17000 | 0.2018          | 0.2200 |
  | 0.9588        | 1.32  | 18000 | 0.1992          | 0.2138 |
  | 0.9413        | 1.39  | 19000 | 0.1898          | 0.2049 |
  | 0.9339        | 1.47  | 20000 | 0.1874          | 0.2056 |
  | 0.9268        | 1.54  | 21000 | 0.1797          | 0.1976 |
  | 0.9194        | 1.61  | 22000 | 0.1743          | 0.1905 |
  | 0.8987        | 1.69  | 23000 | 0.1738          | 0.1932 |
  | 0.8884        | 1.76  | 24000 | 0.1703          | 0.1873 |
  | 0.8939        | 1.83  | 25000 | 0.1633          | 0.1831 |
  | 0.8629        | 1.91  | 26000 | 0.1549          | 0.1750 |
  | 0.8607        | 1.98  | 27000 | 0.1550          | 0.1738 |
  | 0.8316        | 2.05  | 28000 | 0.1512          | 0.1709 |
  | 0.8321        | 2.13  | 29000 | 0.1481          | 0.1657 |
  | 0.825         | 2.2   | 30000 | 0.1446          | 0.1627 |
  | 0.8115        | 2.27  | 31000 | 0.1396          | 0.1583 |
  | 0.7959        | 2.35  | 32000 | 0.1389          | 0.1569 |
  | 0.7835        | 2.42  | 33000 | 0.1362          | 0.1545 |
  | 0.7959        | 2.49  | 34000 | 0.1355          | 0.1531 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  
  #### Evaluation Commands
  1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
  
  ```bash
  python ./eval.py --model_id AndrewMcDowell/wav2vec2-xls-r-1B-german --dataset mozilla-foundation/common_voice_8_0 --config de --split test --log_outputs
  ```
  
  2. To evaluate on test dev data
  ```bash
  python ./eval.py --model_id AndrewMcDowell/wav2vec2-xls-r-1B-german --da