readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-wtimit-finetune
    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-wtimit-finetune
  
  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: 0.0383
  - Wer: 0.0160
  
  ## 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: 64
  - eval_batch_size: 16
  - 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.3743        | 2.82  | 500  | 2.9567          | 1.0    |
  | 1.866         | 5.65  | 1000 | 0.2856          | 0.2580 |
  | 0.2005        | 8.47  | 1500 | 0.0979          | 0.0669 |
  | 0.08          | 11.3  | 2000 | 0.0617          | 0.0325 |
  | 0.0497        | 14.12 | 2500 | 0.0578          | 0.0284 |
  | 0.0348        | 16.95 | 3000 | 0.0557          | 0.0239 |
  | 0.0269        | 19.77 | 3500 | 0.0447          | 0.0212 |
  | 0.0198        | 22.6  | 4000 | 0.0437          | 0.0177 |
  | 0.016         | 25.42 | 4500 | 0.0407          | 0.0164 |
  | 0.014         | 28.25 | 5000 | 0.0383          | 0.0160 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  