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: 10.245288411425497
  ---
  
  
  # 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](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/pt) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3887
  - Wer: 10.2453
  
  ## 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: 1e-05
  - train_batch_size: 64
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0492        | 3.04  | 1000 | 0.2459          | 10.3562 |
  | 0.0065        | 7.02  | 2000 | 0.3180          | 10.4521 |
  | 0.002         | 11.0  | 3000 | 0.3571          | 10.2924 |
  | 0.0009        | 14.04 | 4000 | 0.3816          | 10.2268 |
  | 0.0008        | 18.02 | 5000 | 0.3887          | 10.2453 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  