readme: ---
  language:
  - br
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: openai/whisper-large-v2-breton
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: br
        split: test
        args: br
      metrics:
      - name: Wer
        type: wer
        value: 39.92705800625217
  ---
  
  <!-- 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. -->
  
  # openai/whisper-large-v2-breton
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7162
  - Wer: 39.9271
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 50
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.7423        | 0.1   | 100  | 0.8363          | 57.1553 |
  | 0.4361        | 1.07  | 200  | 0.6833          | 46.7176 |
  | 0.2227        | 2.03  | 300  | 0.6483          | 42.5929 |
  | 0.1472        | 3.0   | 400  | 0.6511          | 42.4627 |
  | 0.0892        | 3.1   | 500  | 0.6633          | 40.9604 |
  | 0.0651        | 4.07  | 600  | 0.6807          | 39.7534 |
  | 0.0416        | 5.04  | 700  | 0.6870          | 41.2383 |
  | 0.0352        | 6.0   | 800  | 0.7315          | 39.9010 |
  | 0.022         | 6.1   | 900  | 0.7201          | 40.4307 |
  | 0.0195        | 7.07  | 1000 | 0.7162          | 39.9271 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  