readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny ID - FLEURS-CV
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: id_id
        split: test
      metrics:
      - type: wer
        value: 30.8
        name: WER
      - type: cer
        value: 11.29
        name: CER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: id
        split: test
      metrics:
      - type: wer
        value: 32.49
        name: WER
      - type: cer
        value: 12.25
        name: CER
  ---
  
  <!-- 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 Tiny ID - FLEURS-CV
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5129
  - Wer: 31.1298
  
  ## 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: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.617         | 1.43  | 500  | 0.5956          | 40.1521 |
  | 0.4062        | 2.86  | 1000 | 0.4991          | 33.2066 |
  | 0.2467        | 4.29  | 1500 | 0.4755          | 31.6802 |
  | 0.1904        | 5.71  | 2000 | 0.4681          | 30.5907 |
  | 0.118         | 7.14  | 2500 | 0.4776          | 30.9368 |
  | 0.0941        | 8.57  | 3000 | 0.4831          | 30.7297 |
  | 0.0771        | 10.0  | 3500 | 0.4912          | 31.1014 |
  | 0.0536        | 11.43 | 4000 | 0.5043          | 31.2319 |
  | 0.0502        | 12.86 | 4500 | 0.5113          | 31.2404 |
  | 0.0418        | 14.29 | 5000 | 0.5129          | 31.1298 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  