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 Small Vi - Shiv Kumar Ganesh
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: vi
        split: test
        args: vi
      metrics:
      - name: Wer
        type: wer
        value: 46.676902829567894
  ---
  
  <!-- 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 Small Vi - Shiv Kumar Ganesh
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7220
  - Wer: 46.6769
  
  ## 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
  - 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: 500
  - training_steps: 1200
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.7433        | 1.02  | 100  | 1.6824          | 155.0559 |
  | 0.5929        | 2.04  | 200  | 0.8475          | 55.5824  |
  | 0.1188        | 3.05  | 300  | 0.6646          | 47.2801  |
  | 0.0672        | 5.0   | 400  | 0.7099          | 61.3292  |
  | 0.0317        | 6.02  | 500  | 0.6951          | 49.9013  |
  | 0.0169        | 7.04  | 600  | 0.7658          | 62.8866  |
  | 0.0089        | 8.06  | 700  | 0.6681          | 34.2509  |
  | 0.004         | 10.01 | 800  | 0.6875          | 43.8364  |
  | 0.0015        | 11.03 | 900  | 0.7129          | 46.8195  |
  | 0.0011        | 12.04 | 1000 | 0.7194          | 47.4775  |
  | 0.0011        | 13.06 | 1100 | 0.7217          | 46.1505  |
  | 0.001         | 15.01 | 1200 | 0.7220          | 46.6769  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  