readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-timit-demo-google-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-google-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: 0.5366
  - Wer: 0.3452
  
  ## 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: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.5499        | 2.01  | 500  | 1.9780          | 0.9933 |
  | 0.7517        | 4.02  | 1000 | 0.4654          | 0.4720 |
  | 0.2953        | 6.02  | 1500 | 0.4202          | 0.4049 |
  | 0.1809        | 8.03  | 2000 | 0.4276          | 0.3759 |
  | 0.1335        | 10.04 | 2500 | 0.4458          | 0.3774 |
  | 0.107         | 12.05 | 3000 | 0.4559          | 0.3707 |
  | 0.0923        | 14.06 | 3500 | 0.4607          | 0.3659 |
  | 0.0753        | 16.06 | 4000 | 0.4699          | 0.3531 |
  | 0.0658        | 18.07 | 4500 | 0.4507          | 0.3588 |
  | 0.0569        | 20.08 | 5000 | 0.5089          | 0.3532 |
  | 0.0493        | 22.09 | 5500 | 0.5481          | 0.3515 |
  | 0.043         | 24.1  | 6000 | 0.5066          | 0.3528 |
  | 0.0388        | 26.1  | 6500 | 0.5418          | 0.3534 |
  | 0.034         | 28.11 | 7000 | 0.5566          | 0.3524 |
  | 0.03          | 30.12 | 7500 | 0.4994          | 0.3437 |
  | 0.0274        | 32.13 | 8000 | 0.5588          | 0.3520 |
  | 0.0239        | 34.14 | 8500 | 0.5328          | 0.3458 |
  | 0.0212        | 36.14 | 9000 | 0.5221          | 0.3467 |
  | 0.0186        | 38.15 | 9500 | 0.5366          | 0.3452 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  