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Whisper whisper-large-v3 sot

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

  • Loss: 0.4477
  • Wer: 22.0832

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • 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: 100
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.9876 0.2 200 0.7042 44.9886
0.3854 0.4 400 0.5672 28.1945
0.2921 0.6 600 0.5097 24.3182
0.7161 0.8 800 0.4786 27.4673
0.5566 1.0 1000 0.4477 22.0832

Framework versions

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