readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2_common_voice_accents_5
    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_5
  
  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: 0.0027
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 4.4163        | 1.34  | 400  | 0.5520          |
  | 0.3305        | 2.68  | 800  | 0.1698          |
  | 0.2138        | 4.03  | 1200 | 0.1104          |
  | 0.1714        | 5.37  | 1600 | 0.0944          |
  | 0.1546        | 6.71  | 2000 | 0.0700          |
  | 0.1434        | 8.05  | 2400 | 0.0610          |
  | 0.1272        | 9.4   | 2800 | 0.0493          |
  | 0.1183        | 10.74 | 3200 | 0.0371          |
  | 0.1113        | 12.08 | 3600 | 0.0468          |
  | 0.1013        | 13.42 | 4000 | 0.0336          |
  | 0.0923        | 14.77 | 4400 | 0.0282          |
  | 0.0854        | 16.11 | 4800 | 0.0410          |
  | 0.0791        | 17.45 | 5200 | 0.0252          |
  | 0.0713        | 18.79 | 5600 | 0.0128          |
  | 0.0662        | 20.13 | 6000 | 0.0252          |
  | 0.0635        | 21.48 | 6400 | 0.0080          |
  | 0.0607        | 22.82 | 6800 | 0.0098          |
  | 0.0557        | 24.16 | 7200 | 0.0069          |
  | 0.0511        | 25.5  | 7600 | 0.0057          |
  | 0.0474        | 26.85 | 8000 | 0.0046          |
  | 0.045         | 28.19 | 8400 | 0.0037          |
  | 0.0426        | 29.53 | 8800 | 0.0027          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  