readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - whisper
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Turkish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 tr
        type: mozilla-foundation/common_voice_11_0
        config: tr
        split: test
        args: tr
      metrics:
      - name: Wer
        type: wer
        value: 17.275280898876407
  ---
  
  <!-- 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 Turkish
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 tr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2799
  - Wer: 17.2753
  - Cer: 4.5335
  
  ## 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     | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
  | 0.1044        | 1.07  | 1000 | 0.2777          | 18.4046 | 4.8810 |
  | 0.0469        | 3.02  | 2000 | 0.2799          | 17.2753 | 4.5335 |
  | 0.014         | 4.09  | 3000 | 0.3202          | 18.0800 | 4.9039 |
  | 0.0039        | 6.04  | 4000 | 0.3326          | 18.2964 | 5.0192 |
  | 0.0022        | 7.11  | 5000 | 0.3453          | 18.0307 | 4.9470 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  