Whisper Medium ar-quran

This model is a fine-tuned version of openai/whisper-medium on the Quran dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0002
  • Wer: 0.0225
  • Cer: 0.0065

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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.04
  • training_steps: 41811

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.0314 0.0239 1000 0.0630 4.8259 1.4337
0.022 0.0478 2000 0.0381 3.2238 1.2475
0.0201 0.0718 3000 0.0232 1.8863 0.5372
0.0056 0.0957 4000 0.0181 1.4976 0.4436
0.01 0.1196 5000 0.0138 1.2360 0.4163
0.0299 0.1435 6000 0.0097 0.8300 0.2353
0.005 0.1674 7000 0.0111 0.9460 0.2609
0.0041 0.1913 8000 0.0085 0.6724 0.1903
0.0031 0.2153 9000 0.0085 0.7467 0.2519
0.0015 0.2392 10000 0.0065 0.5152 0.1718
0.0024 0.2631 11000 0.0055 0.4879 0.1368
0.0013 0.2870 12000 0.0049 0.3987 0.1141
0.0013 0.3109 13000 0.0053 0.4605 0.1257
0.0015 0.3348 14000 0.0041 0.3633 0.1081
0.0011 0.3588 15000 0.0037 0.3359 0.1115
0.0041 0.3827 16000 0.0047 0.3666 0.1026
0.0031 0.4066 17000 0.0041 0.3522 0.1118
0.0008 0.4305 18000 0.0030 0.2569 0.0788
0.0012 0.4544 19000 0.0028 0.2674 0.0811
0.0012 1.0072 20000 0.0025 0.2415 0.0753
0.0011 1.0311 21000 0.0029 0.2689 0.0795
0.001 1.0550 22000 0.0022 0.1989 0.0608
0.001 1.0789 23000 0.0017 0.1840 0.0852
0.0006 1.1028 24000 0.0017 0.1711 0.0500
0.0003 1.1267 25000 0.0013 0.1591 0.0670
0.0 1.1507 26000 0.0013 0.1212 0.0362
0.0008 1.1746 27000 0.0013 0.1716 0.0679
0.0001 1.1985 28000 0.0012 0.1730 0.0727
0.0005 1.2224 29000 0.0013 0.1054 0.0314
0.0003 1.2463 30000 0.0009 0.1021 0.0284
0.0002 1.2702 31000 0.0009 0.0925 0.0235
0.0001 1.2942 32000 0.0008 0.0863 0.0223
0.0 1.3181 33000 0.0008 0.0695 0.0193
0.0002 1.3420 34000 0.0007 0.0623 0.0159
0.0001 1.3659 35000 0.0005 0.0613 0.0195
0.0 1.3898 36000 0.0004 0.0474 0.0148
0.0003 1.4137 37000 0.0003 0.0364 0.0125
0.0002 1.4377 38000 0.0003 0.0321 0.0113
0.0 1.4616 39000 0.0002 0.0211 0.0063
0.0001 2.0148 40000 0.0002 0.0220 0.0064
0.0 2.0387 41000 0.0002 0.0225 0.0065

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1

Citation

Please cite the model using the following BibTeX entry:

@misc{deepdml/whisper-medium-ar-quran-mix-norm,
      title={Fine-tuned Whisper medium ASR model for speech recognition in Arabic},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-medium-ar-quran-mix-norm}},
      year={2026}
    }
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Evaluation results