readme: ---
  language:
  - sr
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Serbian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 sr
        type: mozilla-foundation/common_voice_11_0
        config: sr
        split: test
        args: sr
      metrics:
      - name: Wer
        type: wer
        value: 22.905706191825175
  ---
  
  <!-- 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 Serbian
  
  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 sr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5670
  - Wer: 22.9057
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  The model was trained on the training + validation splits of the Serbian split of the Common Voice dataset and evaluated on the test split of the Serbian split from the Common Voice dataset.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 64
  - eval_batch_size: 32
  - 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: 800
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.4257        | 5.0   | 100  | 0.4377          | 32.4160 |
  | 0.0779        | 10.0  | 200  | 0.3928          | 23.7556 |
  | 0.0108        | 15.0  | 300  | 0.4856          | 23.4318 |
  | 0.0104        | 20.0  | 400  | 0.5637          | 25.4958 |
  | 0.0069        | 25.0  | 500  | 0.5289          | 23.1485 |
  | 0.0022        | 30.0  | 600  | 0.5670          | 22.9057 |
  | 0.0012        | 35.0  | 700  | 0.5746          | 23.0271 |
  | 0.0006        | 40.0  | 800  | 0.5810          | 23.1890 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  