readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-common-voice-persian-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-common-voice-persian-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: 1.1446
  - Wer: 0.6911
  
  ## 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: 16
  - 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.26  | 300  | 3.0670          | 1.0    |
  | 3.3475        | 2.52  | 600  | 2.5530          | 1.0    |
  | 3.3475        | 3.78  | 900  | 1.4598          | 0.9555 |
  | 2.0348        | 5.04  | 1200 | 1.2189          | 0.8797 |
  | 1.0817        | 6.3   | 1500 | 1.1242          | 0.8268 |
  | 1.0817        | 7.56  | 1800 | 1.0764          | 0.7957 |
  | 0.7973        | 8.82  | 2100 | 1.1023          | 0.7863 |
  | 0.7973        | 10.08 | 2400 | 1.0583          | 0.7785 |
  | 0.6514        | 11.34 | 2700 | 1.0963          | 0.7512 |
  | 0.5878        | 12.61 | 3000 | 1.1200          | 0.7494 |
  | 0.5878        | 13.87 | 3300 | 1.0396          | 0.7402 |
  | 0.484         | 15.13 | 3600 | 1.1407          | 0.7340 |
  | 0.484         | 16.39 | 3900 | 1.1534          | 0.7584 |
  | 0.4384        | 17.65 | 4200 | 1.0973          | 0.7236 |
  | 0.3966        | 18.91 | 4500 | 1.0623          | 0.7358 |
  | 0.3966        | 20.17 | 4800 | 1.1655          | 0.7112 |
  | 0.3408        | 21.43 | 5100 | 1.1825          | 0.7084 |
  | 0.3408        | 22.69 | 5400 | 1.1436          | 0.7029 |
  | 0.3274        | 23.95 | 5700 | 1.1077          | 0.6988 |
  | 0.2948        | 25.21 | 6000 | 1.1454          | 0.7066 |
  | 0.2948        | 26.47 | 6300 | 1.1411          | 0.6956 |
  | 0.2545        | 27.73 | 6600 | 1.0952          | 0.6918 |
  | 0.2545        | 28.99 | 6900 | 1.1446          | 0.6911 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  