readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-timit-demo-colab971
    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-timit-demo-colab971
  
  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: 0.6551
  - Wer: 0.4448
  
  ## 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: 2
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.9461        | 1.77  | 500  | 3.2175          | 1.0    |
  | 2.5387        | 3.53  | 1000 | 1.2239          | 0.7851 |
  | 0.9632        | 5.3   | 1500 | 0.7275          | 0.6352 |
  | 0.6585        | 7.07  | 2000 | 0.6218          | 0.5896 |
  | 0.4875        | 8.83  | 2500 | 0.5670          | 0.5651 |
  | 0.397         | 10.6  | 3000 | 0.5796          | 0.5487 |
  | 0.3298        | 12.37 | 3500 | 0.5870          | 0.5322 |
  | 0.2816        | 14.13 | 4000 | 0.5796          | 0.5016 |
  | 0.2396        | 15.9  | 4500 | 0.5956          | 0.5040 |
  | 0.2019        | 17.67 | 5000 | 0.5911          | 0.4847 |
  | 0.1845        | 19.43 | 5500 | 0.6050          | 0.4800 |
  | 0.1637        | 21.2  | 6000 | 0.6518          | 0.4927 |
  | 0.1428        | 22.97 | 6500 | 0.6247          | 0.4645 |
  | 0.1319        | 24.73 | 7000 | 0.6592          | 0.4711 |
  | 0.1229        | 26.5  | 7500 | 0.6526          | 0.4556 |
  | 0.1111        | 28.27 | 8000 | 0.6551          | 0.4448 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  