readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_8_0
  model-index:
  - name: xls-r-ur-large
    results: []
  ---
  
  <!-- 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. -->
  
  # xls-r-ur-large
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_8_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8056
  - Wer: 0.4716
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 6.5282        | 3.25  | 1000 | 3.0650          | 0.9989 |
  | 1.7351        | 6.49  | 2000 | 0.8798          | 0.6284 |
  | 0.7662        | 9.74  | 3000 | 0.7720          | 0.5399 |
  | 0.5675        | 12.99 | 4000 | 0.7661          | 0.5229 |
  | 0.4591        | 16.23 | 5000 | 0.7849          | 0.5041 |
  | 0.3881        | 19.48 | 6000 | 0.8065          | 0.4893 |
  | 0.3522        | 22.73 | 7000 | 0.7915          | 0.4804 |
  | 0.3127        | 25.97 | 8000 | 0.8119          | 0.4804 |
  | 0.2932        | 29.22 | 9000 | 0.8056          | 0.4716 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  