readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-F03-2
    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-demo-F03-2
  
  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: 1.4472
  - Wer: 0.8797
  
  ## 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: 8
  - 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
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 24.7815       | 0.97  | 500   | 3.3881          | 1.0    |
  | 3.3791        | 1.94  | 1000  | 3.2550          | 1.0    |
  | 2.9748        | 2.91  | 1500  | 2.8719          | 1.0    |
  | 2.8305        | 3.88  | 2000  | 2.7878          | 1.0    |
  | 2.6289        | 4.85  | 2500  | 2.5009          | 1.2082 |
  | 2.1553        | 5.83  | 3000  | 1.8680          | 1.3270 |
  | 1.4669        | 6.8   | 3500  | 1.5138          | 1.3266 |
  | 1.0475        | 7.77  | 4000  | 1.3531          | 1.2078 |
  | 0.8132        | 8.74  | 4500  | 1.2666          | 1.1926 |
  | 0.665         | 9.71  | 5000  | 1.2461          | 1.0980 |
  | 0.5538        | 10.68 | 5500  | 1.3152          | 1.0719 |
  | 0.4759        | 11.65 | 6000  | 1.3190          | 1.0902 |
  | 0.4221        | 12.62 | 6500  | 1.3077          | 1.0184 |
  | 0.3836        | 13.59 | 7000  | 1.3410          | 1.0645 |
  | 0.3409        | 14.56 | 7500  | 1.2378          | 1.0246 |
  | 0.3068        | 15.53 | 8000  | 1.3002          | 1.0152 |
  | 0.2911        | 16.5  | 8500  | 1.3603          | 1.0074 |
  | 0.2647        | 17.48 | 9000  | 1.3479          | 0.9375 |
  | 0.2446        | 18.45 | 9500  | 1.3462          | 0.9187 |
  | 0.2208        | 19.42 | 10000 | 1.4029          | 0.9109 |
  | 0.2203        | 20.39 | 10500 | 1.4036          | 0.8977 |
  | 0.204         | 21.36 | 11000 | 1.3755          | 0.8668 |
  | 0.191         | 22.33 | 11500 | 1.3042          | 0.8691 |
  | 0.1784        | 23.3  | 12000 | 1.4343          | 0.8758 |
  | 0.1692        | 24.27 | 12500 | 1.4351          | 0.8492 |
  | 0.1527        | 25.24 | 13000 | 1.4415          | 0.8645 |
  | 0.1444        | 26.21 | 13500 | 1.4684          | 0.8812 |
  | 0.1432        | 27.18 | 14000 | 1.4406          | 0.8906 |
  | 0.1385        | 28.16 | 14500 | 1.4900          | 0.8840 |
  | 0.1392        | 29.13 | 15000 | 1.4472          | 0.8797 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  