readme: ---
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - google/fleurs
  - generated_from_trainer
  datasets:
  - fleurs
  metrics:
  - wer
  model-index:
  - name: facebook/wav2vec2-xls-r-1b
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: GOOGLE/FLEURS - PS_AF
        type: fleurs
        config: ps_af
        split: test
        args: 'Config: ps_af, Training split: train+validation, Eval split: test'
      metrics:
      - name: Wer
        type: wer
        value: 0.9294849931787176
  ---
  
  <!-- 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. -->
  
  # facebook/wav2vec2-xls-r-1b
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GOOGLE/FLEURS - PS_AF dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.1921
  - Wer: 0.9295
  - Cer: 0.9608
  
  ## 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: 1000
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
  | 19.9558       | 1.27  | 100  | 3.2660 | 20.9197         | 1.0    |
  | 19.7186       | 2.53  | 200  | 1.1692 | 19.2447         | 1.0    |
  | 15.203        | 3.8   | 300  | 0.9687 | 15.0053         | 0.9998 |
  | 6.4303        | 5.06  | 400  | 0.9911 | 6.5437          | 0.9632 |
  | 4.5712        | 6.33  | 500  | 0.9546 | 4.9040          | 0.9323 |
  | 3.3986        | 12.66 | 1000 | 4.1921 | 0.9295          | 0.9608 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  