Hokkien-to-Tai Lo Whisper ver 4

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

  • Loss: 0.4709
  • Wer: 84.1740

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-06
  • train_batch_size: 8
  • eval_batch_size: 16
  • 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: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 8000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3834 0.256 800 0.5102 83.2549
0.4023 0.512 1600 0.4974 82.0220
0.4024 0.768 2400 0.4877 83.6808
0.3819 1.024 3200 0.4820 80.9460
0.3125 1.28 4000 0.4772 79.4889
0.315 1.536 4800 0.4762 82.0220
0.3057 1.792 5600 0.4707 80.2062
0.3093 2.048 6400 0.4695 82.0444
0.2507 2.304 7200 0.4716 83.4342
0.2476 2.56 8000 0.4709 84.1740

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0
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