Fine-tuned Whisper model for Legislative Yuan of Taiwan

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

  • Loss: 0.0167
  • Wer: 62.0249

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: 16
  • 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
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0161 0.2034 1000 0.0196 67.4840
0.0191 0.4068 2000 0.0185 65.3481
0.0152 0.6103 3000 0.0176 64.0898
0.0157 0.8137 4000 0.0171 62.9154
0.011 1.0171 5000 0.0167 62.0249

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.5.1
  • Datasets 2.19.1
  • Tokenizers 0.20.1
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