readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: juancopi81/whisper-medium-es
    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: 5.945636921157944
  ---
  
  <!-- 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. -->
  
  # juancopi81/whisper-medium-es
  
  This model is a fine-tuned version of [juancopi81/whisper-medium-es](https://huggingface.co/juancopi81/whisper-medium-es) on the common_voice_11_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1893
  - Wer: 5.9456
  
  Using the script provided in the Whisper Sprint (Dec. 2022) the models achieves these results on the evaluation sets (WER):
  - google/fleurs: 7.02
  - mozilla-foundation/common_voice_11_0: XXXX
  
  ## 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: 3000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.244         | 1.01  | 1000 | 0.1848          | 6.4894 |
  | 0.0714        | 2.02  | 2000 | 0.1805          | 5.9528 |
  | 0.0285        | 3.03  | 3000 | 0.1893          | 5.9456 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  