readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xlsr-53-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-large-xlsr-53-demo-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6901
  - Wer: 1.6299
  
  ## 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: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 8.5034        | 3.42  | 400  | 3.5852          | 1.0    |
  | 1.7853        | 6.83  | 800  | 0.7430          | 1.6774 |
  | 0.5675        | 10.26 | 1200 | 0.6513          | 1.6330 |
  | 0.3761        | 13.67 | 1600 | 0.6208          | 1.6081 |
  | 0.2776        | 17.09 | 2000 | 0.6401          | 1.6081 |
  | 0.2266        | 20.51 | 2400 | 0.6410          | 1.6295 |
  | 0.1949        | 23.93 | 2800 | 0.6910          | 1.6287 |
  | 0.1672        | 27.35 | 3200 | 0.6901          | 1.6299 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  