readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - en
  - generated_from_trainer
  - hf-asr-leaderboard
  - librispeech_asr
  - robust-speech-event
  datasets:
  - librispeech_asr
  model-index:
  - name: XLS-R-300M - English
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: LibriSpeech (clean)
        type: librispeech_asr
        config: clean
        split: test
        args: 
          language: en
      metrics:
      - name: Test WER
        type: wer
        value: 12.29
      - name: Test CER
        type: cer
        value: 3.34
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: en
      metrics:
      - name: Validation WER
        type: wer
        value: 36.75
      - name: Validation CER
        type: cer
        value: 14.83
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8.0
        type: mozilla-foundation/common_voice_8_0
        config: en
        split: test
        args: 
          language: en
      metrics:
      - name: Test WER
        type: wer
        value: 37.81
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: en
      metrics:
      - name: Test WER
        type: wer
        value: 38.8
  ---
  
  # 
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the librispeech_asr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1444
  - Wer: 0.1167
  
  
  ## 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: 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
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.9365        | 4.17  | 500  | 2.9398          | 0.9999 |
  | 1.5444        | 8.33  | 1000 | 0.5947          | 0.4289 |
  | 1.1367        | 12.5  | 1500 | 0.2751          | 0.2366 |
  | 0.9972        | 16.66 | 2000 | 0.2032          | 0.1797 |
  | 0.9118        | 20.83 | 2500 | 0.1786          | 0.1479 |
  | 0.8664        | 24.99 | 3000 | 0.1641          | 0.1408 |
  | 0.8251        | 29.17 | 3500 | 0.1537          | 0.1267 |
  | 0.793         | 33.33 | 4000 | 0.1525          | 0.1244 |
  | 0.785         | 37.5  | 4500 | 0.1470          | 0.1184 |
  | 0.7612        | 41.66 | 5000 | 0.1446          | 0.1177 |
  | 0.7478        | 45.83 | 5500 | 0.1449          | 0.1176 |
  | 0.7443        | 49.99 | 6000 | 0.1444          | 0.1167 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  