readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: colab-demo
    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. -->
  
  # colab-demo
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.9910
  - Wer: 0.9714
  
  ## 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: 16
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1212        | 2.14  | 500  | 3.6706          | 1.0757 |
  | 0.2303        | 4.27  | 1000 | 2.6849          | 1.0578 |
  | 0.3003        | 6.41  | 1500 | 3.2261          | 1.0605 |
  | 0.2705        | 8.55  | 2000 | 3.3483          | 1.0844 |
  | 0.2178        | 10.68 | 2500 | 3.2000          | 1.0219 |
  | 0.1875        | 12.82 | 3000 | 2.2454          | 1.0159 |
  | 0.1792        | 14.96 | 3500 | 2.7510          | 0.9973 |
  | 0.1477        | 17.09 | 4000 | 2.6716          | 0.9847 |
  | 0.1232        | 19.23 | 4500 | 2.5939          | 0.9807 |
  | 0.1051        | 21.37 | 5000 | 3.3308          | 0.9794 |
  | 0.0847        | 23.5  | 5500 | 3.3430          | 0.9814 |
  | 0.0809        | 25.64 | 6000 | 3.2566          | 0.9595 |
  | 0.0642        | 27.78 | 6500 | 3.6392          | 0.9654 |
  | 0.0566        | 29.91 | 7000 | 3.9910          | 0.9714 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.1
  