readme: ---
  language:
  - fr
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: deepdml/whisper-medium-mix-fr
    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: 11.227820307400155
      - name: Cer
        type: cer
        value: 4.2141
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: FLEURS ASR
        type: google/fleurs
        config: fr_fr
        split: test
        args: fr
      metrics:
      - name: WER
        type: wer
        value: 9.3526
      - name: Cer
        type: cer
        value: 4.144
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Multilingual LibriSpeech
        type: facebook/multilingual_librispeech
        config: french
        split: test
        args:
          language: fr
      metrics:
      - name: WER
        type: wer
        value: 6.3468
      - name: Cer
        type: cer
        value: 3.1561
    - task:
        type: Automatic Speech Recognition
        name: speech-recognition
      dataset:
        name: VoxPopuli
        type: facebook/voxpopuli
        config: fr
        split: test
        args:
          language: fr
      metrics:
      - name: WER
        type: wer
        value: 10.0653
      - name: Cer
        type: cer
        value: 6.5456
  ---
  
  <!-- 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. -->
  
  # deepdml/whisper-medium-mix-fr
  
  This model is a fine-tuned version of [deepdml/whisper-medium-mix-fr](https://huggingface.co/deepdml/whisper-medium-mix-fr) on the mozilla-foundation/common_voice_11_0, google/fleurs, facebook/multilingual_librispeech and facebook/voxpopuli datasets.
  It achieves the following results on the evaluation set:
  - Loss: 0.2599
  - Wer: 11.2278
  
  Using the [evalutaion script](https://github.com/huggingface/community-events/blob/main/whisper-fine-tuning-event/run_eval_whisper_streaming.py) provided in the Whisper Sprint the model achieves these results on the test sets (WER):
  
  - **google/fleurs: 9.3526 %**  
  (python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="google/fleurs" --config="fr_fr" --device=0 --language="fr")
  - **facebook/multilingual_librispeech: 6.3468 %**  
  (python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="facebook/multilingual_librispeech" --config="french" --device=0 --language="fr")
  - **facebook/voxpopuli: 10.0653 %**  
  (python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="facebook/voxpopuli" --config="fr" --device=0 --language="fr")
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  Training data used:
  - **mozilla-foundation/common_voice_11_0:** fr, train+validation
  - **google/fleurs:** fr_fr, train
  - **facebook/multilingual_librispeech:** french, train
  - **facebook/voxpopuli:** fr, train
  - 
  Evaluating over test split from mozilla-foundation/common_voice_11_0 dataset.
  
  ## 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: 4000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0855        | 0.25  | 1000 | 0.2826          | 12.4230 |
  | 0.0569        | 0.5   | 2000 | 0.2768          | 11.9577 |
  | 0.0724        | 0.75  | 3000 | 0.2670          | 11.6106 |
  | 0.069         | 1.0   | 4000 | 0.2599          | 11.2278 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  