readme: ---
  language:
  - cv
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - cv
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Chuvash
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: cv
      metrics:
      - name: Test WER
        type: wer
        value: 60.31
      - name: Test CER
        type: cer
        value: 15.08
  ---
  
  <!-- 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-large-xls-r-300m-chuvash
  
  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_7_0 - CV dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7651
  - Wer: 0.6166
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.8032        | 8.77  | 500  | 0.8059          | 0.8352 |
  | 1.2608        | 17.54 | 1000 | 0.5828          | 0.6769 |
  | 1.1337        | 26.32 | 1500 | 0.6892          | 0.6908 |
  | 1.0457        | 35.09 | 2000 | 0.7077          | 0.6781 |
  | 0.97          | 43.86 | 2500 | 0.5993          | 0.6228 |
  | 0.8767        | 52.63 | 3000 | 0.7213          | 0.6604 |
  | 0.8223        | 61.4  | 3500 | 0.8161          | 0.6968 |
  | 0.7441        | 70.18 | 4000 | 0.7057          | 0.6184 |
  | 0.7011        | 78.95 | 4500 | 0.7027          | 0.6024 |
  | 0.6542        | 87.72 | 5000 | 0.7092          | 0.5979 |
  | 0.6081        | 96.49 | 5500 | 0.7917          | 0.6324 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  