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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: 0.6244
  • Cer Ortho: 28.9724
  • Cer: 24.2287

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: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Ortho Cer
0.783 0.4796 600 0.7962 54.2372 31.6835
0.6578 0.9592 1200 0.6968 32.3398 27.9872
0.5028 1.4388 1800 0.6624 40.8123 27.6832
0.4887 1.9185 2400 0.6265 31.8488 25.8712
0.3368 2.3981 3000 0.6200 31.5221 25.3234
0.3395 2.8777 3600 0.6106 38.9218 25.3534
0.2078 3.3573 4200 0.6184 28.7037 24.7440
0.1943 3.8369 4800 0.6139 32.2586 24.3287
0.1206 4.3165 5400 0.6272 30.4763 24.2656
0.102 4.7962 6000 0.6244 28.9724 24.2287

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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Dataset used to train VingeNie/whisper-tiny-zh_CN_lr4_b16