readme: ---
  language:
  - es
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Large v2 Spanish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 es
        type: mozilla-foundation/common_voice_11_0
        config: es
        split: test
        args: es
      metrics:
      - name: Wer
        type: wer
        value: 5.288186684683748
  ---
  
  <!-- 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 Large v2 Spanish
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 es dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1702
  - Wer google/fleurs: 4.89
  - Wer mozilla-foundation/common_voice_11_0: 5.2882
  
  ## 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: 8
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.1738        | 0.1   | 1000  | 0.2031          | 7.0384 |
  | 0.2108        | 1.01  | 2000  | 0.1885          | 6.6668 |
  | 0.1599        | 1.11  | 3000  | 0.1814          | 6.5342 |
  | 0.0794        | 2.01  | 4000  | 0.1792          | 6.0314 |
  | 0.0477        | 2.11  | 5000  | 0.1936          | 6.1795 |
  | 0.0341        | 3.02  | 6000  | 0.2038          | 6.0113 |
  | 0.0264        | 3.12  | 7000  | 0.2111          | 5.8410 |
  | 0.0608        | 4.02  | 8000  | 0.1824          | 5.9067 |
  | 0.0523        | 4.12  | 9000  | 0.1768          | 5.3941 |
  | 0.0984        | 5.03  | 10000 | 0.1702          | 5.2882 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221210+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  