readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-timit-demo-colab
    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-colab
  
  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: 3.3780
  - Wer: 1.0
  
  ## 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: 32
  - 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: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 0.08  | 10   | 14.0985         | 1.0    |
  | No log        | 0.16  | 20   | 13.8638         | 1.0004 |
  | No log        | 0.24  | 30   | 13.5135         | 1.0023 |
  | No log        | 0.32  | 40   | 12.8708         | 1.0002 |
  | No log        | 0.4   | 50   | 11.6927         | 1.0    |
  | No log        | 0.48  | 60   | 10.2733         | 1.0    |
  | No log        | 0.56  | 70   | 8.1396          | 1.0    |
  | No log        | 0.64  | 80   | 5.3503          | 1.0    |
  | No log        | 0.72  | 90   | 3.7975          | 1.0    |
  | No log        | 0.8   | 100  | 3.4275          | 1.0    |
  | No log        | 0.88  | 110  | 3.3596          | 1.0    |
  | No log        | 0.96  | 120  | 3.3780          | 1.0    |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  