readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-vios-v1
    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-v1
  
  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: 0.6352
  - Wer: 0.5161
  
  ## 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: 32
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 5.7944        | 3.98  | 1000  | 1.7427          | 1.0387 |
  | 0.7833        | 7.97  | 2000  | 0.4026          | 0.4364 |
  | 0.4352        | 11.95 | 3000  | 0.3967          | 0.4042 |
  | 0.4988        | 15.94 | 4000  | 0.5446          | 0.4632 |
  | 0.7822        | 19.92 | 5000  | 0.6563          | 0.5491 |
  | 0.8496        | 23.9  | 6000  | 0.5828          | 0.5045 |
  | 0.8072        | 27.89 | 7000  | 0.6318          | 0.5109 |
  | 0.8336        | 31.87 | 8000  | 0.6352          | 0.5161 |
  | 0.8311        | 35.86 | 9000  | 0.6352          | 0.5161 |
  | 0.839         | 39.84 | 10000 | 0.6352          | 0.5161 |
  | 0.8297        | 43.82 | 11000 | 0.6352          | 0.5161 |
  | 0.8288        | 47.81 | 12000 | 0.6352          | 0.5161 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  