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Whisper Medium Zh - Kimas

This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0635
  • Wer: 100.0

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_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1461 0.28 1000 0.1406 100.0
0.0803 0.57 2000 0.1181 100.0
0.0715 0.85 3000 0.1039 100.0
0.0255 1.14 4000 0.0925 100.0207
0.0199 1.42 5000 0.0810 100.0
0.027 1.7 6000 0.0767 100.0207
0.0328 1.99 7000 0.0706 100.0
0.0026 2.27 8000 0.0700 100.0
0.0082 2.56 9000 0.0646 100.0
0.0099 2.84 10000 0.0635 100.0

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 1.12.1
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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