readme: ---
  language:
  - fr
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny French Cased
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 fr
        type: mozilla-foundation/common_voice_11_0
        config: fr
        split: test
        args: fr
      metrics:
      - name: Wer
        type: wer
        value: 33.06549172161867
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs fr_fr
        type: google/fleurs
        config: fr_fr
        split: test
        args: fr_fr
      metrics:
      - name: Wer
        type: wer
        value: 36.69
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: facebook/voxpopuli fr
        type: facebook/voxpopuli
        config: fr
        split: test
        args: fr
      metrics:
      - name: Wer
        type: wer
        value: 32.71
  ---
  
  <!-- 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 Tiny French Cased
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 fr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6509
  - Wer on `mozilla-foundation/common_voice_11_0` `fr`: 33.0655
  - Wer on `google/fleurs` `fr_fr`: 36.69
  - Wer on `facebook/voxpopuli` `fr`: 32.71
  
  ## 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: 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.7185        | 0.2   | 1000 | 0.7608          | 38.1636 |
  | 0.6052        | 1.2   | 2000 | 0.6949          | 34.9513 |
  | 0.4467        | 2.2   | 3000 | 0.6708          | 34.3393 |
  | 0.4773        | 3.2   | 4000 | 0.6536          | 33.2102 |
  | 0.4479        | 4.2   | 5000 | 0.6509          | 33.0655 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  