readme: ---
  language:
  - fr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - fr
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-cls-r-300m-fr
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: fr
      metrics:
      - name: Test WER
        type: wer
        value: 56.62
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: fr
      metrics:
      - name: Test WER
        type: wer
        value: 58.22
  ---
  
  <!-- 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. -->
  
  # wav2vec2-cls-r-300m-fr
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the COMMON_VOICE - FR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6521
  - Wer: 0.4330
  
  ## 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: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.6773        | 0.8   | 500  | 1.3907          | 0.9864 |
  | 0.9526        | 1.6   | 1000 | 0.7760          | 0.6448 |
  | 0.6418        | 2.4   | 1500 | 0.7605          | 0.6194 |
  | 0.5028        | 3.2   | 2000 | 0.6516          | 0.5322 |
  | 0.4133        | 4.0   | 2500 | 0.6303          | 0.5097 |
  | 0.3285        | 4.8   | 3000 | 0.6422          | 0.5062 |
  | 0.2764        | 5.6   | 3500 | 0.5936          | 0.4748 |
  | 0.2361        | 6.4   | 4000 | 0.6486          | 0.4683 |
  | 0.2049        | 7.2   | 4500 | 0.6321          | 0.4532 |
  | 0.176         | 8.0   | 5000 | 0.6230          | 0.4482 |
  | 0.1393        | 8.8   | 5500 | 0.6595          | 0.4403 |
  | 0.1141        | 9.6   | 6000 | 0.6552          | 0.4348 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  