readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-klay-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-klay-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: 0.0060
  - Wer: 0.1791
  
  ## 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: 500
  - num_epochs: 300
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 15.0  | 300  | 2.4020          | 0.9889 |
  | 2.4596        | 30.0  | 600  | 1.3773          | 0.9833 |
  | 2.4596        | 45.0  | 900  | 0.5241          | 0.7253 |
  | 1.1148        | 60.0  | 1200 | 0.2260          | 0.4472 |
  | 0.3637        | 75.0  | 1500 | 0.1474          | 0.3682 |
  | 0.3637        | 90.0  | 1800 | 0.0742          | 0.2848 |
  | 0.1874        | 105.0 | 2100 | 0.0563          | 0.2681 |
  | 0.1874        | 120.0 | 2400 | 0.0535          | 0.2436 |
  | 0.1273        | 135.0 | 2700 | 0.0335          | 0.2258 |
  | 0.0914        | 150.0 | 3000 | 0.0336          | 0.2214 |
  | 0.0914        | 165.0 | 3300 | 0.0323          | 0.2136 |
  | 0.0733        | 180.0 | 3600 | 0.0225          | 0.2069 |
  | 0.0733        | 195.0 | 3900 | 0.0953          | 0.2314 |
  | 0.0678        | 210.0 | 4200 | 0.0122          | 0.1902 |
  | 0.0428        | 225.0 | 4500 | 0.0104          | 0.1869 |
  | 0.0428        | 240.0 | 4800 | 0.0120          | 0.1791 |
  | 0.0291        | 255.0 | 5100 | 0.0110          | 0.1835 |
  | 0.0291        | 270.0 | 5400 | 0.0062          | 0.1802 |
  | 0.0235        | 285.0 | 5700 | 0.0061          | 0.1802 |
  | 0.0186        | 300.0 | 6000 | 0.0060          | 0.1791 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  