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Whisper Small LoRA tuned zh-TW

This model is a fine-tuned version of openai/whisper-small on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2094
  • CER: 13.1583%

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: 4
  • 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: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.2284 1.0 1453 0.2305
0.2221 2.0 2906 0.2183
0.1939 3.0 4359 0.2149
0.2085 4.0 5812 0.2125
0.2202 5.0 7265 0.2112
0.2097 6.0 8718 0.2103
0.2072 7.0 10171 0.2095
0.1906 8.0 11624 0.2094
0.1818 9.0 13077 0.2091
0.2054 10.0 14530 0.2093
0.1597 11.0 15983 0.2094
0.1797 12.0 17436 0.2095
0.204 13.0 18889 0.2096
0.1872 14.0 20342 0.2094
0.1879 15.0 21795 0.2094

Framework versions

  • PEFT 0.9.1.dev0
  • Transformers 4.40.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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