readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - superb
  model-index:
  - name: wav2vec2-base-dataset_asr-demo-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-dataset_asr-demo-colab
  
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the superb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 295.0834
  - Wer: 0.8282
  
  ## 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: 0.001
  - train_batch_size: 32
  - 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: 250
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5638.536      | 1.6   | 500  | 409.4785        | 0.8556 |
  | 2258.6455     | 3.19  | 1000 | 326.0520        | 0.8369 |
  | 1389.4919     | 4.79  | 1500 | 295.0834        | 0.8282 |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  