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metadata
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:
          name: Automatic Speech Recognition
          type: 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:
          - name: Wer
            type: wer
            value: 6.3671568743912

Whisper Small Belarusian

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 be dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0706
  • Wer: 6.3672

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