EYEDOL/whisper-tiny-yoruba1

This model is a fine-tuned version of EYEDOL/whisper-tiny-yoruba on the EYEDOL/naija-voices-yoruba-split_0-4 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8130
  • Wer Ortho: 0.7657
  • Wer: 0.6755

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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
1.5706 1.0 583 0.7699 0.8067 0.7173
1.4778 2.0 1166 0.7536 0.7432 0.6515
1.3621 3.0 1749 0.7465 0.7352 0.6440
1.2687 4.0 2332 0.7418 0.7670 0.6748
1.1844 5.0 2915 0.7442 0.7682 0.6766
1.1091 6.0 3498 0.7471 0.7690 0.6733
1.0363 7.0 4081 0.7512 0.7385 0.6481
0.9677 8.0 4664 0.7607 0.7673 0.6829
0.9016 9.0 5247 0.7728 0.7618 0.6768
0.8397 10.0 5830 0.7889 0.7395 0.6530
0.7784 11.0 6413 0.7975 0.7635 0.6761
0.7197 12.0 6996 0.8130 0.7657 0.6755

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.8.3
  • Tokenizers 0.22.2
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Dataset used to train EYEDOL/whisper-tiny-yoruba1

Evaluation results