readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: data-augmentation-whitenoise-timit-1155
    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. -->
  
  # data-augmentation-whitenoise-timit-1155
  
  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: 0.5458
  - Wer: 0.3324
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 3.5204        | 0.8   | 500   | 1.6948          | 0.9531 |
  | 0.8435        | 1.6   | 1000  | 0.5367          | 0.5113 |
  | 0.4449        | 2.4   | 1500  | 0.4612          | 0.4528 |
  | 0.3182        | 3.21  | 2000  | 0.4314          | 0.4156 |
  | 0.2328        | 4.01  | 2500  | 0.4250          | 0.4031 |
  | 0.1897        | 4.81  | 3000  | 0.4630          | 0.4023 |
  | 0.1628        | 5.61  | 3500  | 0.4445          | 0.3922 |
  | 0.1472        | 6.41  | 4000  | 0.4452          | 0.3793 |
  | 0.1293        | 7.21  | 4500  | 0.4715          | 0.3847 |
  | 0.1176        | 8.01  | 5000  | 0.4267          | 0.3757 |
  | 0.1023        | 8.81  | 5500  | 0.4494          | 0.3821 |
  | 0.092         | 9.62  | 6000  | 0.4501          | 0.3704 |
  | 0.0926        | 10.42 | 6500  | 0.4722          | 0.3643 |
  | 0.0784        | 11.22 | 7000  | 0.5033          | 0.3765 |
  | 0.077         | 12.02 | 7500  | 0.5165          | 0.3684 |
  | 0.0704        | 12.82 | 8000  | 0.5138          | 0.3646 |
  | 0.0599        | 13.62 | 8500  | 0.5664          | 0.3674 |
  | 0.0582        | 14.42 | 9000  | 0.5188          | 0.3575 |
  | 0.0526        | 15.22 | 9500  | 0.5605          | 0.3621 |
  | 0.0512        | 16.03 | 10000 | 0.5400          | 0.3585 |
  | 0.0468        | 16.83 | 10500 | 0.5471          | 0.3603 |
  | 0.0445        | 17.63 | 11000 | 0.5168          | 0.3555 |
  | 0.0411        | 18.43 | 11500 | 0.5772          | 0.3542 |
  | 0.0394        | 19.23 | 12000 | 0.5079          | 0.3567 |
  | 0.0354        | 20.03 | 12500 | 0.5427          | 0.3613 |
  | 0.0325        | 20.83 | 13000 | 0.5532          | 0.3572 |
  | 0.0318        | 21.63 | 13500 | 0.5223          | 0.3514 |
  | 0.0269        | 22.44 | 14000 | 0.6002          | 0.3460 |
  | 0.028         | 23.24 | 14500 | 0.5591          | 0.3432 |
  | 0.0254        | 24.04 | 15000 | 0.5837          | 0.3432 |
  | 0.0235        | 24.84 | 15500 | 0.5571          | 0.3397 |
  | 0.0223        | 25.64 | 16000 | 0.5470          | 0.3383 |
  | 0.0193        | 26.44 | 16500 | 0.5611          | 0.3367 |
  | 0.0227        | 27.24 | 17000 | 0.5405          | 0.3342 |
  | 0.0183        | 28.04 | 17500 | 0.5205          | 0.3330 |
  | 0.017         | 28.85 | 18000 | 0.5512          | 0.3330 |
  | 0.0167        | 29.65 | 18500 | 0.5458          | 0.3324 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  