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: 17.391605006569392
  ---
  # Whisper Small Italian
  
  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1185
  - Wer: 17.3916
  
  ## 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
  - gradient_accumulation_steps: 1
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 954
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Step | Validation Loss | Wer     |
  |:-------------:|:----:|:---------------:|:-------:|
  | 1.4744        | 100  | 1.1852          | 117.6059 |
  | 0.7241        | 200  | 0.7452          | 79.7386 |
  | 0.3321        | 300  | 0.3215          | 21.0497 |
  | 0.2930        | 400  | 0.3030          | 20.2129 |
  | 0.2698        | 500  | 0.2982          | 19.7635 |
  | 0.2453        | 600  | 0.2898          | 19.0097 |
  | 0.2338        | 700  | 0.2768          | 18.7054 |
  | 0.2402        | 800  | 0.2646          | 18.2214 |
  | 0.2340        | 900  | 0.2581          | 17.3916 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2