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Whisper Small Bemba - Beijuka Bruno

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

  • Loss: 1.3874
  • Wer: 0.4833
  • Cer: 0.1314

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: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.3572 1.0 638 0.9726 0.6131 0.2029
0.7143 2.0 1276 0.8546 0.5769 0.1907
0.4485 3.0 1914 0.8472 0.5749 0.1936
0.2568 4.0 2552 0.9305 0.6149 0.1963
0.1328 5.0 3190 0.9798 0.5448 0.1658
0.0678 6.0 3828 1.0441 0.5373 0.1647
0.0366 7.0 4466 1.1153 0.5366 0.1719
0.0223 8.0 5104 1.1549 0.5441 0.1626
0.0169 9.0 5742 1.2010 0.5364 0.1698
0.0122 10.0 6380 1.2321 0.5384 0.1560
0.0098 11.0 7018 1.2646 0.5202 0.1522
0.0092 12.0 7656 1.2855 0.5279 0.1570
0.0085 13.0 8294 1.3001 0.5218 0.1568
0.0094 14.0 8932 1.3090 0.5240 0.1573
0.008 15.0 9570 1.3016 0.5220 0.1524
0.0064 16.0 10208 1.3748 0.5195 0.1532
0.0061 17.0 10846 1.3741 0.5147 0.1561
0.0072 18.0 11484 1.3958 0.5211 0.1560
0.007 19.0 12122 1.3849 0.5233 0.1554
0.0042 20.0 12760 1.4370 0.5124 0.1521
0.0046 21.0 13398 1.4660 0.5177 0.1529
0.0048 22.0 14036 1.4625 0.5115 0.1509
0.0057 23.0 14674 1.4502 0.5197 0.1554
0.005 24.0 15312 1.4473 0.5174 0.1568
0.0037 25.0 15950 1.4782 0.5258 0.1545
0.0035 26.0 16588 1.4798 0.5154 0.1533
0.0034 27.0 17226 1.5074 0.5170 0.1539
0.0042 28.0 17864 1.4976 0.5227 0.1572
0.0045 29.0 18502 1.5364 0.5110 0.1565
0.0025 30.0 19140 1.5072 0.5206 0.1545

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.1.0+cu118
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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