readme: ---
  language:
  - uk
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-xls-r-1b-hy-cv
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_8_0
        name: Common Voice uk
        args: uk
      metrics:
      - type: wer
        value: 12.246920571994902
        name: WER LM
      - type: cer
        value: 2.513653497966816
        name: CER LM
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: uk
      metrics:
      - name: Test WER
        type: wer
        value: 46.56
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: uk
      metrics:
      - name: Test WER
        type: wer
        value: 35.98
  ---
  
  <!-- 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 - UK dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1747
  - Wer: 0.2107
  - Cer: 0.0408
  
  ## 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: 8e-05
  - train_batch_size: 16
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - training_steps: 8000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 1.3719        | 4.35  | 500  | 0.3389          | 0.4236 | 0.0833 |
  | 1.1361        | 8.7   | 1000 | 0.2309          | 0.3162 | 0.0630 |
  | 1.0517        | 13.04 | 1500 | 0.2166          | 0.3056 | 0.0597 |
  | 1.0118        | 17.39 | 2000 | 0.2141          | 0.2784 | 0.0557 |
  | 0.9922        | 21.74 | 2500 | 0.2231          | 0.2941 | 0.0594 |
  | 0.9929        | 26.09 | 3000 | 0.2171          | 0.2892 | 0.0587 |
  | 0.9485        | 30.43 | 3500 | 0.2236          | 0.2956 | 0.0599 |
  | 0.9573        | 34.78 | 4000 | 0.2314          | 0.3043 | 0.0616 |
  | 0.9195        | 39.13 | 4500 | 0.2169          | 0.2812 | 0.0580 |
  | 0.8915        | 43.48 | 5000 | 0.2109          | 0.2780 | 0.0560 |
  | 0.8449        | 47.83 | 5500 | 0.2050          | 0.2534 | 0.0514 |
  | 0.8028        | 52.17 | 6000 | 0.2032          | 0.2456 | 0.0492 |
  | 0.7881        | 56.52 | 6500 | 0.1890          | 0.2380 | 0.0469 |
  | 0.7423        | 60.87 | 7000 | 0.1816          | 0.2245 | 0.0442 |
  | 0.7248        | 65.22 | 7500 | 0.1789          | 0.2165 | 0.0422 |
  | 0.6993        | 69.57 | 8000 | 0.1747          | 0.2107 | 0.0408 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  