readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2_common_voice_accents_4
    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_4
  
  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: 0.0047
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 4.615         | 1.28  | 400  | 0.8202          |
  | 0.3778        | 2.56  | 800  | 0.1587          |
  | 0.2229        | 3.85  | 1200 | 0.1027          |
  | 0.1799        | 5.13  | 1600 | 0.0879          |
  | 0.1617        | 6.41  | 2000 | 0.0772          |
  | 0.1474        | 7.69  | 2400 | 0.0625          |
  | 0.134         | 8.97  | 2800 | 0.0498          |
  | 0.1213        | 10.26 | 3200 | 0.0429          |
  | 0.1186        | 11.54 | 3600 | 0.0434          |
  | 0.1118        | 12.82 | 4000 | 0.0312          |
  | 0.1026        | 14.1  | 4400 | 0.0365          |
  | 0.0951        | 15.38 | 4800 | 0.0321          |
  | 0.0902        | 16.67 | 5200 | 0.0262          |
  | 0.0843        | 17.95 | 5600 | 0.0208          |
  | 0.0744        | 19.23 | 6000 | 0.0140          |
  | 0.0718        | 20.51 | 6400 | 0.0204          |
  | 0.0694        | 21.79 | 6800 | 0.0133          |
  | 0.0636        | 23.08 | 7200 | 0.0104          |
  | 0.0609        | 24.36 | 7600 | 0.0084          |
  | 0.0559        | 25.64 | 8000 | 0.0050          |
  | 0.0527        | 26.92 | 8400 | 0.0089          |
  | 0.0495        | 28.21 | 8800 | 0.0058          |
  | 0.0471        | 29.49 | 9200 | 0.0047          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  