readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-vios-google-colab
    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-base-vios-google-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5647
  - Wer: 0.4970
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.7292        | 2.0   | 500  | 3.4159          | 1.0    |
  | 3.0762        | 4.0   | 1000 | 1.3005          | 0.9615 |
  | 0.8812        | 6.0   | 1500 | 0.4664          | 0.4740 |
  | 0.5076        | 8.0   | 2000 | 0.4101          | 0.4180 |
  | 0.4075        | 10.0  | 2500 | 0.3815          | 0.3802 |
  | 0.3724        | 12.0  | 3000 | 0.3785          | 0.3741 |
  | 0.3762        | 14.0  | 3500 | 0.4404          | 0.3766 |
  | 0.4541        | 16.0  | 4000 | 0.4671          | 0.3822 |
  | 0.6391        | 18.0  | 4500 | 0.5643          | 0.4200 |
  | 0.7681        | 20.0  | 5000 | 0.6564          | 0.5214 |
  | 0.8131        | 22.0  | 5500 | 0.5786          | 0.4934 |
  | 0.7448        | 24.0  | 6000 | 0.5561          | 0.4920 |
  | 0.7337        | 26.0  | 6500 | 0.5631          | 0.4964 |
  | 0.7359        | 28.0  | 7000 | 0.5647          | 0.4968 |
  | 0.7397        | 30.0  | 7500 | 0.5647          | 0.4970 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  