readme: ---
  language:
  - be
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Belarusian
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 be
        type: mozilla-foundation/common_voice_11_0
        config: be
        split: validation
        args: be
      metrics:
      - type: wer
        name: WER
        value: 6.3671568743912
  
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 be
        type: mozilla-foundation/common_voice_11_0
        config: be
        split: test
        args: be
      metrics:
      - type: wer
        name: WER
        value: 6.79
  
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: be_by
        split: test
      metrics:
      - type: wer
        value: 43.615168811067036
        name: "WER (reference column: transcription)"
      - type: wer
        value: 45.89674723962996
        name: "WER (reference column: raw_transcription)"
  ---
  
  <!-- 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 Belarusian
  
  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 be dataset.
  It achieves the following results on the evaluation set:
  - Loss on validation: 0.0706
  - WER on validation set: 6.3672
  - WER on test set: 6.79
  
  ## Source code
  All the source coude is located both in:
  * [GitHub repository](https://github.com/yks72p/whisper-finetuning-be)
  * and under `src` folder
  
  Code in these 2 places should be the same. GitHub is used to make development and training of multiple models (small, base, etc.) easier.
  
  ## 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: 0.0001
  - train_batch_size: 64
  - eval_batch_size: 64
  - 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: 12000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.1907        | 0.08  | 1000  | 0.2546          | 25.4639 |
  | 0.1482        | 0.17  | 2000  | 0.1641          | 17.1676 |
  | 0.1175        | 0.25  | 3000  | 0.1454          | 15.5940 |
  | 0.0958        | 0.33  | 4000  | 0.1261          | 13.2625 |
  | 0.099         | 0.42  | 5000  | 0.1012          | 10.6143 |
  | 0.028         | 1.05  | 6000  | 0.1053          | 9.8794  |
  | 0.0473        | 1.13  | 7000  | 0.1029          | 10.3078 |
  | 0.0391        | 1.21  | 8000  | 0.0924          | 9.2419  |
  | 0.0423        | 1.3   | 9000  | 0.0797          | 7.9249  |
  | 0.0604        | 1.38  | 10000 | 0.0688          | 7.0150  |
  | 0.0121        | 2.01  | 11000 | 0.0696          | 6.4638  |
  | 0.0155        | 2.1   | 12000 | 0.0706          | 6.3672  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  