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Whisper Small Norwegian Bokmål

This model is a fine-tuned version of openai/whisper-small trained on several datasets.

It is currently in the middle of a large training. Currently it achieves the following results on the evaluation set:

  • Loss: 0.3230
  • Wer: 15.56

Model description

The model is trained on a large corpus of roughly 5.000 hours of voice. The sources are subtitles from the Norwegian broadcaster NRK, transcribed speeches from the Norwegian parliament and voice recordings from Norsk Språkteknologi.

Intended uses & limitations

The model will be free for everyone to use when it is finished.

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-06
  • train_batch_size: 128
  • gradient_accumulation_steps: 2
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant with warmup
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 50.000 (currently @1.000)
  • mixed_precision_training: fp16
  • deepspeed: true

Live Training results

See Tensorboad Metrics

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Datasets used to train NbAiLab/whisper-small-nob

Evaluation results