readme: ---
  language:
    - it
  license: apache-2.0
  tags:
  - generated_from_trainer
  - whisper-event
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: luigisaetta/whisper-medium-it
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 it
        type: mozilla-foundation/common_voice_11_0
        config: it
        split: test
        args: it
      metrics:
      - name: Wer
        type: wer
        value: 5.7191
  ---
  
  
  # luigisaetta/whisper-medium-it
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_11_0 dataset.
  
  It achieves the following results on the evaluation set:
  - Loss: 0.1452
  - Wer: 5.7191
  
  ## Model description
  
  This model is a fine-tuning of the OpenAI Whisper Medium model, on the specified dataset.
  
  ## Intended uses & limitations
  
  This model has been developed as part of the Hugging Face Whisper Fine Tuning sprint, December 2022.
  
  It is meant to spread the knowledge on how these models are built and can be used to develop solutions
  where it is needed ASR on the Italian Language.
  
  It has not been extensively tested. It is possible that on other datasets the accuracy will be lower. 
  
  Please, test it before using it.
  
  ## Training and evaluation data
  
  Trained and tested on Mozilla Common Voice, vers. 11
  
  ## Training procedure
  
  The script **run.sh**, and the Python file, used for the training are saved in the repository.
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - 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: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.1216        | 0.2   | 1000 | 0.2289          | 10.0594 |
  | 0.1801        | 0.4   | 2000 | 0.1851          | 7.6593  |
  | 0.1763        | 0.6   | 3000 | 0.1615          | 6.5258  |
  | 0.1337        | 0.8   | 4000 | 0.1506          | 6.0427  |
  | 0.0742        | 1.05  | 5000 | 0.1452          | 5.7191  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  