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jethrowang/whisper-tiny_tat_vanilla_evaluated_on_android

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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Whisper Tiny Taiwanese Condenser

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

  • —eval_loss: 0.6266
  • —evalmodelpreparation_time: 0.0025
  • —eval_cer: 11.3753
  • —eval_runtime: 1520.3341
  • —evalsamplesper_second: 3.694
  • —evalstepsper_second: 0.116
  • —step: 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: 0.0001
  • —trainbatchsize: 64
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 681
  • —training_steps: 6810
  • —mixedprecisiontraining: Native AMP

Framework versions

  • —Transformers 4.49.0
  • —Pytorch 2.0.0.post304
  • —Datasets 3.3.2
  • —Tokenizers 0.21.0