readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-vi-25p
    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-large-xls-r-300m-vi-25p
  
  This model was trained from scratch on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8293
  - Wer: 0.4109
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - 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 | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.9542        | 1.31  | 400  | 1.4443          | 0.5703 |
  | 1.276         | 2.62  | 800  | 1.4606          | 0.5736 |
  | 1.1311        | 3.93  | 1200 | 1.4552          | 0.5186 |
  | 0.9519        | 5.25  | 1600 | 1.4477          | 0.5300 |
  | 0.8293        | 6.56  | 2000 | 1.4166          | 0.5097 |
  | 0.7555        | 7.87  | 2400 | 1.4100          | 0.4906 |
  | 0.6724        | 9.18  | 2800 | 1.4982          | 0.4880 |
  | 0.6038        | 10.49 | 3200 | 1.4524          | 0.4945 |
  | 0.5338        | 11.8  | 3600 | 1.4995          | 0.4798 |
  | 0.4988        | 13.11 | 4000 | 1.6715          | 0.4653 |
  | 0.461         | 14.43 | 4400 | 1.5699          | 0.4552 |
  | 0.4154        | 15.74 | 4800 | 1.5762          | 0.4557 |
  | 0.3822        | 17.05 | 5200 | 1.5978          | 0.4471 |
  | 0.3466        | 18.36 | 5600 | 1.6579          | 0.4512 |
  | 0.3226        | 19.67 | 6000 | 1.6825          | 0.4378 |
  | 0.2885        | 20.98 | 6400 | 1.7376          | 0.4421 |
  | 0.2788        | 22.29 | 6800 | 1.7150          | 0.4300 |
  | 0.249         | 23.61 | 7200 | 1.7073          | 0.4263 |
  | 0.2317        | 24.92 | 7600 | 1.7349          | 0.4200 |
  | 0.2171        | 26.23 | 8000 | 1.7419          | 0.4186 |
  | 0.1963        | 27.54 | 8400 | 1.8438          | 0.4144 |
  | 0.1906        | 28.85 | 8800 | 1.8293          | 0.4109 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  