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 Es - Javier Alonso
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: es
        split: test
        args: es
      metrics:
      - name: Wer
        type: wer
        value: 5.520113299724547
  ---
  
  <!-- 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 Es - Javier Alonso
  
  This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1571
  - Wer: 5.5201
  
  ## 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: 2
  - 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: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.211         | 0.1   | 1000  | 0.2293          | 8.3896 |
  | 0.2227        | 0.2   | 2000  | 0.2215          | 8.2552 |
  | 0.1496        | 0.3   | 3000  | 0.2121          | 8.0362 |
  | 0.1851        | 0.4   | 4000  | 0.2018          | 7.5197 |
  | 0.1917        | 0.5   | 5000  | 0.1916          | 7.1098 |
  | 0.1857        | 0.6   | 6000  | 0.1817          | 6.5537 |
  | 0.1294        | 0.7   | 7000  | 0.1752          | 6.4062 |
  | 0.1358        | 0.8   | 8000  | 0.1670          | 5.9950 |
  | 0.1542        | 0.9   | 9000  | 0.1604          | 5.7858 |
  | 0.1554        | 1.0   | 10000 | 0.1571          | 5.5201 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  