readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-base-common-voice-50p-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-50p-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: 1.0939
  - Wer: 0.6537
  
  ## 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: 7.5e-05
  - train_batch_size: 16
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0437        | 2.52  | 600  | 3.0170          | 1.0    |
  | 2.3667        | 5.04  | 1200 | 2.1575          | 0.9988 |
  | 0.9565        | 7.56  | 1800 | 1.0801          | 0.8410 |
  | 0.603         | 10.08 | 2400 | 0.9680          | 0.7678 |
  | 0.507         | 12.61 | 3000 | 0.9554          | 0.7470 |
  | 0.3754        | 15.13 | 3600 | 0.9524          | 0.7157 |
  | 0.4267        | 17.65 | 4200 | 0.9290          | 0.6980 |
  | 0.3308        | 20.17 | 4800 | 0.9557          | 0.7061 |
  | 0.2259        | 22.69 | 5400 | 0.9864          | 0.6830 |
  | 0.2486        | 25.21 | 6000 | 1.1086          | 0.6812 |
  | 0.1956        | 27.73 | 6600 | 1.0497          | 0.6805 |
  | 0.1835        | 30.25 | 7200 | 1.0660          | 0.6596 |
  | 0.1926        | 32.77 | 7800 | 1.1274          | 0.6600 |
  | 0.2765        | 35.29 | 8400 | 1.0882          | 0.6603 |
  | 0.2397        | 37.82 | 9000 | 1.0939          | 0.6537 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  