readme: ---
  language:
  - fr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: xls-r-300m-fr
    results:
    - task:
        name: Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8.0 fr
        type: mozilla-foundation/common_voice_8_0
        args: fr
      metrics:
      - name: Test WER
        type: wer
        value: 36.81
    - 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: 35.55
    - 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: 39.94
  ---
  
  <!-- 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-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2388
  - Wer: 0.3681
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1500
  - num_epochs: 2.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 4.3748        | 0.07  | 500   | 3.8784          | 1.0    |
  | 2.8068        | 0.14  | 1000  | 2.8289          | 0.9826 |
  | 1.6698        | 0.22  | 1500  | 0.8811          | 0.7127 |
  | 1.3488        | 0.29  | 2000  | 0.5166          | 0.5369 |
  | 1.2239        | 0.36  | 2500  | 0.4105          | 0.4741 |
  | 1.1537        | 0.43  | 3000  | 0.3585          | 0.4448 |
  | 1.1184        | 0.51  | 3500  | 0.3336          | 0.4292 |
  | 1.0968        | 0.58  | 4000  | 0.3195          | 0.4180 |
  | 1.0737        | 0.65  | 4500  | 0.3075          | 0.4141 |
  | 1.0677        | 0.72  | 5000  | 0.3015          | 0.4089 |
  | 1.0462        | 0.8   | 5500  | 0.2971          | 0.4077 |
  | 1.0392        | 0.87  | 6000  | 0.2870          | 0.3997 |
  | 1.0178        | 0.94  | 6500  | 0.2805          | 0.3963 |
  | 0.992         | 1.01  | 7000  | 0.2748          | 0.3935 |
  | 1.0197        | 1.09  | 7500  | 0.2691          | 0.3884 |
  | 1.0056        | 1.16  | 8000  | 0.2682          | 0.3889 |
  | 0.9826        | 1.23  | 8500  | 0.2647          | 0.3868 |
  | 0.9815        | 1.3   | 9000  | 0.2603          | 0.3832 |
  | 0.9717        | 1.37  | 9500  | 0.2561          | 0.3807 |
  | 0.9605        | 1.45  | 10000 | 0.2523          | 0.3783 |
  | 0.96          | 1.52  | 10500 | 0.2494          | 0.3788 |
  | 0.9442        | 1.59  | 11000 | 0.2478          | 0.3760 |
  | 0.9564        | 1.66  | 11500 | 0.2454          | 0.3733 |
  | 0.9436        | 1.74  | 12000 | 0.2439          | 0.3747 |
  | 0.938         | 1.81  | 12500 | 0.2411          | 0.3716 |
  | 0.9353        | 1.88  | 13000 | 0.2397          | 0.3698 |
  | 0.9271        | 1.95  | 13500 | 0.2388          | 0.3681 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  