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Whisper Small Taiwanese

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9011
  • Cer: 50.3995

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.6

Training results

Training Loss Epoch Step Cer Validation Loss
1.1421 0.4 1000 61.1639 1.1692
1.0556 0.8 2000 51.7749 1.0215
0.7837 1.2 3000 54.1978 0.9572
0.7332 1.6 4000 50.3966 0.9230
0.6957 2.0 5000 50.5772 0.9064
0.6211 2.4 6000 0.9177 49.8590
0.5584 2.8 7000 0.8962 47.5366
0.3952 3.2 8000 0.9025 48.2925
0.4248 3.6 9000 0.9011 50.3995

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.1.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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