readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base_toy_train_data_masked_audio_10ms
    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_masked_audio_10ms
  
  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: 1.2477
  - Wer: 0.7145
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.1337        | 1.05  | 250  | 3.4081          | 0.9982 |
  | 3.0792        | 2.1   | 500  | 3.2446          | 0.9982 |
  | 2.0577        | 3.15  | 750  | 1.5839          | 0.9492 |
  | 1.3639        | 4.2   | 1000 | 1.3279          | 0.8798 |
  | 1.0814        | 5.25  | 1250 | 1.1629          | 0.8294 |
  | 0.8722        | 6.3   | 1500 | 1.1305          | 0.8140 |
  | 0.7602        | 7.35  | 1750 | 1.1241          | 0.7972 |
  | 0.6982        | 8.4   | 2000 | 1.1429          | 0.7780 |
  | 0.6494        | 9.45  | 2250 | 1.1047          | 0.7620 |
  | 0.5924        | 10.5  | 2500 | 1.1756          | 0.7649 |
  | 0.5385        | 11.55 | 2750 | 1.2230          | 0.7736 |
  | 0.5026        | 12.6  | 3000 | 1.1783          | 0.7472 |
  | 0.4973        | 13.65 | 3250 | 1.1613          | 0.7287 |
  | 0.4726        | 14.7  | 3500 | 1.1923          | 0.7345 |
  | 0.4521        | 15.75 | 3750 | 1.2153          | 0.7171 |
  | 0.4552        | 16.81 | 4000 | 1.2485          | 0.7226 |
  | 0.422         | 17.86 | 4250 | 1.2664          | 0.7240 |
  | 0.3708        | 18.91 | 4500 | 1.2352          | 0.7148 |
  | 0.3516        | 19.96 | 4750 | 1.2477          | 0.7145 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  