readme: ---
  language:
  - de
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_9_0
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_9_0
  model-index:
  - name: wav2vec2-large-xlsr-53-german-cv9
    results:   
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 9
        type: mozilla-foundation/common_voice_9_0
        args: de
      metrics:
      - name: Test WER
        type: wer
        value: 9.480663281840769
      - name: Test CER
        type: cer
        value: 1.9167347943074394
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 9
        type: mozilla-foundation/common_voice_9_0
        args: de
      metrics:
      - name: Test WER (+LM)
        type: wer
        value: 7.49027762774117
      - name: Test CER  (+LM)
        type: cer
        value: 1.9167347943074394
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 6.1
        type: common_voice
        args: de
      metrics:
      - name: Test WER
        type: wer
        value: 8.122005951166668
      - name: Test CER
        type: cer
        value: 1.
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 6.1
        type: common_voice
        args: de
      metrics:
      - name: Test WER (+LM)
        type: wer
        value: 6.1453182045203544
      - name: Test CER (+LM)
        type: cer
        value: 1.5247743373447677
  ---
  
  # wav2vec2-large-xlsr-53-german-cv9
  
  This model is a fine-tuned version of [./facebook/wav2vec2-large-xlsr-53](https://huggingface.co/./facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - DE dataset.
  
  It achieves the following results on the test set:
  - CER: 2.273015898213336
  - Wer: 9.480663281840769
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Eval Wer|
  |:-------------:|:-----:|:------:|:---------------:|:------:|
  | 0.4129        | 1.0   | 3557   | 0.3015          | 0.2499 |
  | 0.2121        | 2.0   | 7114   | 0.1596          | 0.1567 |
  | 0.1455        | 3.0   | 10671  | 0.1377          | 0.1354 |
  | 0.1436        | 4.0   | 14228  | 0.1301          | 0.1282 |
  | 0.1144        | 5.0   | 17785  | 0.1225          | 0.1245 |
  | 0.1219        | 6.0   | 21342  | 0.1254          | 0.1208 |
  | 0.104         | 7.0   | 24899  | 0.1198          | 0.1232 |
  | 0.1016        | 8.0   | 28456  | 0.1149          | 0.1174 |
  | 0.1093        | 9.0   | 32013  | 0.1186          | 0.1186 |
  | 0.0858        | 10.0  | 35570  | 0.1182          | 0.1164 |
  | 0.102         | 11.0  | 39127  | 0.1191          | 0.1186 |
  | 0.0834        | 12.0  | 42684  | 0.1161          | 0.1096 |
  | 0.0916        | 13.0  | 46241  | 0.1147          | 0.1107 |
  | 0.0811        | 14.0  | 49798  | 0.1174          | 0.1136 |
  | 0.0814        | 15.0  | 53355  | 0.1132          | 0.1114 |
  | 0.0865        | 16.0  | 56912  | 0.1134          | 0.1097 |
  | 0.0701        | 17.0  | 60469  | 0.1096          | 0.1054 |
  | 0.0891        | 18.0  | 64026  | 0.1110          | 0.1076 |
  | 0.071         | 19.0  | 67583  | 0.1141          | 0.1074 |
  | 0.0726        | 20.0  | 71140  | 0.1094          | 0.1093 |
  | 0.0647        | 21.0  | 74697  | 0.1088          | 0.1095 |
  | 0.0643        | 22.0  | 78254  | 0.1105          | 0.1044 |
  | 0.0764        | 23.0  | 81811  | 0.1072          | 0.1042 |
  | 0.0605        | 24.0  | 85368  | 0.1095          | 0.1026 |
  | 0.0722        | 25.0  | 88925  | 0.1144          | 0.1066 |
  | 0.0597        | 26.0  | 92482  | 0.1087          | 0.1022 |
  | 0.062         | 27.0  | 96039  | 0.1073          | 0.1027 |
  | 0.0536        | 28.0  | 99596  | 0.1068          | 0.1027 |
  | 0.0616        | 29.0  | 103153 | 0.1097          | 0.1037 |
  | 0.0642        | 30.0  | 106710 | 0.1117          | 0.1020 |
  | 0.0555        | 31.0  | 110267 | 0.1109          | 0.0990 |
  | 0.0632        | 32.0  | 113824 | 0.1104          | 0.0977 |
  | 0.0482        | 33.0  | 117381 | 0.1108          | 0.0958 |
  | 0.0601        | 34.0  | 120938 | 0.1095          | 0.0957 |
  | 0.0508        | 35.0  | 124495 | 0.1079          | 0.0973 |
  | 0.0526        | 36.0  | 128052 | 0.1068          | 0.0967 |
  | 0.0487        | 37.0  | 131609 | 0.1081          | 0.0966 |
  | 0.0495        | 38.0  | 13