readme: ---
  language:
  - it
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Italian - Robust
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 it
        type: mozilla-foundation/common_voice_11_0
        config: it
        split: train
        args: it
      metrics:
      - type: wer
        value: 7.651366149266425
        name: Wer
      - type: wer
        value: 6.6
        name: WER
  ---
  
  <!-- 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 Medium Italian - Robust
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 it dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1388
  - WER (Augmented Test): 7.65
  
  **IMPORTANT** The model has been trained using *data augmentation* to improve its generalization capabilities and robustness. 
  The results on the eval set during training are biased towards data augmentation applied to evaluation data.
  
  **Results on eval set**
  
  - Mozilla CV 11.0 - Italian: 6.60 WER (using official script)
  
  ## 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-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: 7500
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.226         | 0.33  | 2500 | 0.2779          | 14.6642 |
  | 0.1278        | 1.03  | 5000 | 0.1818          | 10.2049 |
  | 0.0304        | 1.36  | 7500 | 0.1388          | 7.5544  |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  