readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-10epochs-3e3
    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. -->
  
  # wav2vec2-10epochs-3e3
  
  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: 0.7024
  - Wer: 0.6481
  
  ## 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: 0.003
  - 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0938        | 0.36  | 100  | 0.4842          | 0.3227 |
  | 0.67          | 0.72  | 200  | 0.7219          | 0.5669 |
  | 0.7133        | 1.08  | 300  | 1.0698          | 0.7080 |
  | 1.0312        | 1.44  | 400  | 1.2692          | 0.8953 |
  | 1.2162        | 1.8   | 500  | 1.4763          | 1.0443 |
  | 1.2401        | 2.16  | 600  | 1.4906          | 0.8694 |
  | 1.2022        | 2.52  | 700  | 1.3686          | 0.9518 |
  | 1.154         | 2.88  | 800  | 1.1618          | 0.9109 |
  | 1.0467        | 3.24  | 900  | 1.2007          | 0.8602 |
  | 1.1785        | 3.6   | 1000 | 1.2000          | 0.9160 |
  | 0.979         | 3.96  | 1100 | 1.1464          | 0.8852 |
  | 1.1421        | 4.32  | 1200 | 1.1117          | 0.9018 |
  | 0.9622        | 4.68  | 1300 | 1.0976          | 0.8602 |
  | 1.0939        | 5.04  | 1400 | 1.1126          | 0.8831 |
  | 0.9414        | 5.4   | 1500 | 1.0134          | 0.8448 |
  | 0.9433        | 5.76  | 1600 | 0.9320          | 0.7977 |
  | 0.8389        | 6.12  | 1700 | 0.9013          | 0.7742 |
  | 0.8838        | 6.47  | 1800 | 0.9088          | 0.7509 |
  | 0.7907        | 6.83  | 1900 | 0.8581          | 0.7382 |
  | 0.7704        | 7.19  | 2000 | 0.8300          | 0.7481 |
  | 0.667         | 7.55  | 2100 | 0.8221          | 0.7349 |
  | 0.6111        | 7.91  | 2200 | 0.7803          | 0.7102 |
  | 0.5555        | 8.27  | 2300 | 0.8198          | 0.7314 |
  | 0.4947        | 8.63  | 2400 | 0.8127          | 0.7036 |
  | 0.4697        | 8.99  | 2500 | 0.7514          | 0.6805 |
  | 0.402         | 9.35  | 2600 | 0.7348          | 0.6606 |
  | 0.3682        | 9.71  | 2700 | 0.7024          | 0.6481 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 2.9.0
  - Tokenizers 0.10.3
  