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Whisper Small Ha - Eldad Akhaumere

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 4.9575
  • Wer Ortho: 110.3468
  • Wer: 108.1055

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: 0.0005
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 13.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
1.5785 3.1847 500 3.8839 99.5593 99.8438
1.1623 6.3694 1000 4.4847 97.7582 98.0078
0.9893 9.5541 1500 4.7922 108.7373 107.6172
0.8816 12.7389 2000 4.9575 110.3468 108.1055

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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Dataset used to train eldad-akhaumere/whisper-small-ha-v9

Evaluation results