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: 11.972265023112481
  ---
  
  <!-- 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: 0.2738
  - Wer: 11.9723
  - Cer: 4.8273
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
  | 0.5235        | 0.92  | 500  | 0.3605          | 15.4083 | 6.1205 |
  | 0.3839        | 1.84  | 1000 | 0.3034          | 14.2835 | 5.6010 |
  | 0.2828        | 2.76  | 1500 | 0.2852          | 13.4977 | 5.1727 |
  | 0.2367        | 3.68  | 2000 | 0.2768          | 12.9122 | 5.2280 |
  | 0.1832        | 4.6   | 2500 | 0.2728          | 12.2496 | 4.9157 |
  | 0.1549        | 5.52  | 3000 | 0.2730          | 12.0647 | 4.8384 |
  | 0.1318        | 6.45  | 3500 | 0.2757          | 12.0955 | 4.8135 |
  | 0.1077        | 7.37  | 4000 | 0.2738          | 11.9723 | 4.8273 |
  | 0.0969        | 8.29  | 4500 | 0.2784          | 12.1572 | 4.9212 |
  | 0.0813        | 9.21  | 5000 | 0.2805          | 12.3112 | 5.0207 |
  | 0.0751        | 10.13 | 5500 | 0.2831          | 12.0801 | 4.8494 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  