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 Small 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: test
        args: it
      metrics:
      - name: WER
        type: wer
        value: 8.00
  ---
  
  <!-- 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 Small Italian - Robust
  
  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 it dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1980
  - Wer: 8.7457
  
  **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: 8.00 wer (using official script)
  - TODO
  
  ## 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: 25000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.1927        | 1.0   | 2500  | 0.2506          | 14.9991 |
  | 0.0736        | 2.01  | 5000  | 0.2258          | 12.7864 |
  | 0.0413        | 3.01  | 7500  | 0.2144          | 11.4508 |
  | 0.0201        | 4.02  | 10000 | 0.2146          | 10.8774 |
  | 0.0129        | 5.02  | 12500 | 0.2127          | 10.6920 |
  | 0.0091        | 6.03  | 15000 | 0.2117          | 10.2867 |
  | 0.0043        | 7.03  | 17500 | 0.2076          | 9.6860  |
  | 0.0018        | 8.04  | 20000 | 0.2065          | 9.4235  |
  | 0.0013        | 9.04  | 22500 | 0.2003          | 8.9105  |
  | 0.0009        | 10.05 | 25000 | 0.1978          | 8.7497  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  