readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-100libri-english
    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. -->
  
  # wav2vec2-100libri-english
  
  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: 0.0786
  - Wer: 0.1017
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.3602        | 0.28  | 1000  | 0.2307          | 0.2529 |
  | 0.2774        | 0.56  | 2000  | 0.1332          | 0.1606 |
  | 0.1765        | 0.84  | 3000  | 0.1256          | 0.1485 |
  | 0.1488        | 1.12  | 4000  | 0.1179          | 0.1408 |
  | 0.138         | 1.4   | 5000  | 0.1193          | 0.1348 |
  | 0.1338        | 1.68  | 6000  | 0.1065          | 0.1336 |
  | 0.125         | 1.96  | 7000  | 0.0977          | 0.1214 |
  | 0.1048        | 2.24  | 8000  | 0.0975          | 0.1213 |
  | 0.1222        | 2.52  | 9000  | 0.0917          | 0.1181 |
  | 0.094         | 2.8   | 10000 | 0.0867          | 0.1144 |
  | 0.0649        | 3.08  | 11000 | 0.0903          | 0.1127 |
  | 0.0793        | 3.36  | 12000 | 0.0895          | 0.1106 |
  | 0.0698        | 3.64  | 13000 | 0.0856          | 0.1094 |
  | 0.0888        | 3.92  | 14000 | 0.0808          | 0.1058 |
  | 0.0711        | 4.21  | 15000 | 0.0799          | 0.1053 |
  | 0.0713        | 4.49  | 16000 | 0.0796          | 0.1024 |
  | 0.0705        | 4.77  | 17000 | 0.0786          | 0.1017 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 2.8.0
  - Tokenizers 0.10.3
  