readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-base-1
    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-1
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9254
  - Wer: 0.3216
  
  ## 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: 8
  - 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 1.6597        | 2.2   | 1000  | 0.8904          | 0.5388 |
  | 0.4751        | 4.41  | 2000  | 0.7009          | 0.3976 |
  | 0.3307        | 6.61  | 3000  | 0.7068          | 0.3672 |
  | 0.2574        | 8.81  | 4000  | 0.7320          | 0.3544 |
  | 0.2096        | 11.01 | 5000  | 0.7803          | 0.3418 |
  | 0.177         | 13.22 | 6000  | 0.7768          | 0.3423 |
  | 0.1521        | 15.42 | 7000  | 0.8113          | 0.3375 |
  | 0.1338        | 17.62 | 8000  | 0.8153          | 0.3325 |
  | 0.1168        | 19.82 | 9000  | 0.8851          | 0.3306 |
  | 0.104         | 22.03 | 10000 | 0.8811          | 0.3277 |
  | 0.0916        | 24.23 | 11000 | 0.8722          | 0.3254 |
  | 0.083         | 26.43 | 12000 | 0.9527          | 0.3265 |
  | 0.0766        | 28.63 | 13000 | 0.9254          | 0.3216 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  