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Whisper Tiny chinese - VingeNie

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

  • Loss: 0.7976
  • Cer Ortho: 35.9855
  • Cer: 29.9636

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 25
  • training_steps: 1500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Ortho Cer
0.8364 1.0 300 0.8423 44.8697 32.3523
0.5618 2.0 600 0.7816 44.3497 31.3998
0.3559 3.0 900 0.7747 41.4869 30.1052
0.2016 4.0 1200 0.7828 37.2903 30.2107
0.0953 5.0 1500 0.7976 35.9855 29.9636

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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Finetuned from

Dataset used to train VingeNie/whisper-tiny-zh_CN_lr4_lowdata