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Whisper whisper-large-v3-turbo xho

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the dsfsi-anv/za-african-next-voices dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3618
  • Wer: 19.6309

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3576 1.007 500 0.3938 29.3971
0.2536 2.014 1000 0.3147 22.4916
0.1773 3.021 1500 0.3101 21.7084
0.1419 4.028 2000 0.3081 20.6204
0.0905 5.035 2500 0.3142 20.8713
0.0611 6.042 3000 0.3231 20.3719
0.0617 7.049 3500 0.3326 20.4680
0.036 8.056 4000 0.3375 20.4235
0.0304 9.063 4500 0.3595 20.3766
0.0208 10.07 5000 0.3618 19.6309

Framework versions

  • Transformers 4.52.0
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.4
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