readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2_common_voice_accents_us
    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. -->
  
  # wav2vec2_common_voice_accents_us
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2722
  
  ## 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: 48
  - eval_batch_size: 4
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 8
  - total_train_batch_size: 384
  - total_eval_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 4.549         | 1.28  | 400  | 0.8521          |
  | 0.4066        | 2.56  | 800  | 0.2407          |
  | 0.2262        | 3.83  | 1200 | 0.2070          |
  | 0.1828        | 5.11  | 1600 | 0.2134          |
  | 0.1565        | 6.39  | 2000 | 0.2060          |
  | 0.1448        | 7.67  | 2400 | 0.2100          |
  | 0.1333        | 8.95  | 2800 | 0.2036          |
  | 0.121         | 10.22 | 3200 | 0.2192          |
  | 0.1146        | 11.5  | 3600 | 0.2154          |
  | 0.1108        | 12.78 | 4000 | 0.2223          |
  | 0.1017        | 14.06 | 4400 | 0.2331          |
  | 0.094         | 15.34 | 4800 | 0.2257          |
  | 0.0896        | 16.61 | 5200 | 0.2229          |
  | 0.0825        | 17.89 | 5600 | 0.2229          |
  | 0.0777        | 19.17 | 6000 | 0.2417          |
  | 0.0719        | 20.45 | 6400 | 0.2433          |
  | 0.0659        | 21.73 | 6800 | 0.2447          |
  | 0.0651        | 23.0  | 7200 | 0.2446          |
  | 0.0587        | 24.28 | 7600 | 0.2542          |
  | 0.056         | 25.56 | 8000 | 0.2587          |
  | 0.0521        | 26.84 | 8400 | 0.2640          |
  | 0.0494        | 28.12 | 8800 | 0.2753          |
  | 0.0465        | 29.39 | 9200 | 0.2722          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  