readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2_common_voice_accents_3
    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_3
  
  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: 0.0042
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 4.584         | 1.27  | 400  | 1.1439          |
  | 0.481         | 2.55  | 800  | 0.1986          |
  | 0.2384        | 3.82  | 1200 | 0.1060          |
  | 0.1872        | 5.1   | 1600 | 0.1016          |
  | 0.158         | 6.37  | 2000 | 0.0942          |
  | 0.1427        | 7.64  | 2400 | 0.0646          |
  | 0.1306        | 8.92  | 2800 | 0.0612          |
  | 0.1197        | 10.19 | 3200 | 0.0423          |
  | 0.1129        | 11.46 | 3600 | 0.0381          |
  | 0.1054        | 12.74 | 4000 | 0.0326          |
  | 0.0964        | 14.01 | 4400 | 0.0293          |
  | 0.0871        | 15.29 | 4800 | 0.0239          |
  | 0.0816        | 16.56 | 5200 | 0.0168          |
  | 0.0763        | 17.83 | 5600 | 0.0202          |
  | 0.0704        | 19.11 | 6000 | 0.0224          |
  | 0.0669        | 20.38 | 6400 | 0.0208          |
  | 0.063         | 21.66 | 6800 | 0.0074          |
  | 0.0585        | 22.93 | 7200 | 0.0126          |
  | 0.0548        | 24.2  | 7600 | 0.0086          |
  | 0.0512        | 25.48 | 8000 | 0.0080          |
  | 0.0487        | 26.75 | 8400 | 0.0052          |
  | 0.0455        | 28.03 | 8800 | 0.0062          |
  | 0.0433        | 29.3  | 9200 | 0.0042          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  