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HouraMor/wh-ft-lre5-dtstf5-adm-ga1ba16-st15k-pat3-v2-evalstp500

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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wh-ft-lre5-dtstf5-adm-ga1ba16-st15k-pat3-v2-evalstp500

This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.5000
  • —Wer: 0.2427
  • —Cer: 0.1794

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
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —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: 750
  • —training_steps: 15000
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWerCer
0.54680.30475000.51340.29060.2173
0.50770.609410000.48970.28760.2224
0.46720.914115000.48170.31400.2437
0.29241.218820000.47400.22770.1714
0.29981.523525000.47490.24530.1858
0.33011.828230000.46490.24550.1862
0.14842.132835000.50020.22650.1695
0.1412.437540000.50070.23400.1713
0.15382.742245000.50000.24270.1794

Framework versions

  • —Transformers 4.52.3
  • —Pytorch 2.7.0+cu118
  • —Datasets 3.5.1
  • —Tokenizers 0.21.1