readme: ---
  language:
  - pt
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Portuguese
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 pt
        type: mozilla-foundation/common_voice_11_0
        config: pt
        split: test
        args: pt
      metrics:
      - name: Wer
        type: wer
        value: 14.684129429892142
  ---
  
  <!-- 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. -->
  
  # Whisper Small Portuguese
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 pt dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3056
  - Wer: 14.6841
  - Cer: 5.8856
  
  ## 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: 5e-06
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
  | 0.2817        | 0.92  | 500  | 0.3352          | 15.9476 | 6.3609 |
  | 0.2245        | 1.84  | 1000 | 0.3047          | 15.0231 | 5.9326 |
  | 0.1587        | 2.76  | 1500 | 0.2985          | 15.0847 | 5.9326 |
  | 0.1181        | 3.68  | 2000 | 0.3056          | 14.6841 | 5.8856 |
  | 0.0741        | 4.6   | 2500 | 0.3162          | 14.9923 | 5.9906 |
  | 0.0438        | 5.52  | 3000 | 0.3466          | 15.4700 | 6.2255 |
  | 0.0294        | 6.45  | 3500 | 0.3799          | 15.2234 | 6.1647 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  