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fathyy/Graduation_Project_Distilation_Whisper2

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

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Whisper base AR - BA

This model is a fine-tuned version of openai/whisper-base on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1141
  • —Wer: 0.2425

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: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 32
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 15
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
7.74011.03130.12120.2782
6.97232.06260.12500.2510
5.08273.09390.11900.2505
4.34544.012520.12070.2300
3.50295.015650.12180.2393
2.94646.018780.11660.2393
2.68877.021910.11480.2259
2.47158.025040.11300.2378
2.21749.028170.11220.2315
2.006110.031300.11170.2352
1.868111.034430.11140.2244
1.766912.037560.11090.2243
1.657913.040690.11120.2274
1.554114.043820.11080.2266
1.51914.953646800.11070.2252

Framework versions

  • —Transformers 4.51.1
  • —Pytorch 2.5.1+cu124
  • —Datasets 3.5.0
  • —Tokenizers 0.21.0