readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base_toy_train_data_fast_10pct
    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_toy_train_data_fast_10pct
  
  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: 1.3087
  - Wer: 0.7175
  
  ## 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
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.1309        | 1.05  | 250  | 3.4541          | 0.9982 |
  | 3.0499        | 2.1   | 500  | 3.0231          | 0.9982 |
  | 1.4839        | 3.15  | 750  | 1.4387          | 0.9257 |
  | 1.1697        | 4.2   | 1000 | 1.3729          | 0.8792 |
  | 0.9353        | 5.25  | 1250 | 1.2608          | 0.8445 |
  | 0.7298        | 6.3   | 1500 | 1.1867          | 0.8052 |
  | 0.6418        | 7.35  | 1750 | 1.2414          | 0.7997 |
  | 0.5698        | 8.4   | 2000 | 1.2240          | 0.7766 |
  | 0.5084        | 9.45  | 2250 | 1.1910          | 0.7687 |
  | 0.4912        | 10.5  | 2500 | 1.2241          | 0.7617 |
  | 0.4144        | 11.55 | 2750 | 1.2412          | 0.7477 |
  | 0.4153        | 12.6  | 3000 | 1.2736          | 0.7511 |
  | 0.405         | 13.65 | 3250 | 1.2827          | 0.7328 |
  | 0.3852        | 14.7  | 3500 | 1.1981          | 0.7331 |
  | 0.3829        | 15.75 | 3750 | 1.3035          | 0.7347 |
  | 0.3538        | 16.81 | 4000 | 1.3003          | 0.7240 |
  | 0.3385        | 17.86 | 4250 | 1.3354          | 0.7304 |
  | 0.3108        | 18.91 | 4500 | 1.2983          | 0.7229 |
  | 0.3037        | 19.96 | 4750 | 1.3087          | 0.7175 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  