readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-base-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-demo-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: 0.4409
  - Wer: 0.3484
  
  ## 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: 1000
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.3824        | 1.0   | 500  | 1.4646          | 1.0050 |
  | 0.8251        | 2.01  | 1000 | 0.5555          | 0.5319 |
  | 0.4265        | 3.01  | 1500 | 0.4303          | 0.4456 |
  | 0.2864        | 4.02  | 2000 | 0.4605          | 0.4284 |
  | 0.2124        | 5.02  | 2500 | 0.3851          | 0.3862 |
  | 0.1658        | 6.02  | 3000 | 0.3870          | 0.3815 |
  | 0.136         | 7.03  | 3500 | 0.4154          | 0.3726 |
  | 0.1124        | 8.03  | 4000 | 0.4399          | 0.3642 |
  | 0.0943        | 9.04  | 4500 | 0.4069          | 0.3544 |
  | 0.0772        | 10.04 | 5000 | 0.4544          | 0.3539 |
  | 0.066         | 11.04 | 5500 | 0.4409          | 0.3484 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu116
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  