readme: ---
  language:
  - it
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Italian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        args: 'config: it, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 17.37085955328124
  ---
  
  # Whisper Small Italian
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  
  - Loss: 0.2421
  - Wer: 17.3709
  
  ## 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: 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: 2
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.4521        | 0.1   | 100  | 1.3771          | 120.3480 |
  | 0.7526        | 0.21  | 200  | 0.9120          | 83.8949  |
  | 0.3023        | 0.31  | 300  | 0.4427          | 26.2063  |
  | 0.2718        | 0.42  | 400  | 0.4282          | 25.9013  |
  | 0.2823        | 0.52  | 500  | 0.4181          | 26.2757  |
  | 0.3151        | 0.63  | 600  | 0.4095          | 25.0624  |
  | 0.2559        | 0.73  | 700  | 0.4028          | 25.4784  |
  | 0.2727        | 0.84  | 800  | 0.2888          | 19.5491  |
  | 0.2532        | 0.94  | 900  | 0.2779          | 19.3832  |
  | 0.232         | 1.05  | 1000 | 0.2722          | 18.6778  |
  | 0.2169        | 1.15  | 1100 | 0.2720          | 18.9268  |
  | 0.2493        | 1.26  | 1200 | 0.2741          | 20.0678  |
  | 0.2312        | 1.36  | 1300 | 0.2666          | 18.2767  |
  | 0.2158        | 1.47  | 1400 | 0.2651          | 19.6529  |
  | 0.2171        | 1.57  | 1500 | 0.2583          | 18.6087  |
  | 0.2074        | 1.68  | 1600 | 0.2551          | 17.6820  |
  | 0.1862        | 1.78  | 1700 | 0.2491          | 17.4124  |
  | 0.2044        | 1.89  | 1800 | 0.2475          | 17.8964  |
  | 0.1877        | 1.99  | 1900 | 0.2421          | 17.3709  |
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  