Whisper Medium ar-quran

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0757
  • Wer: 0.1553

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: 16
  • eval_batch_size: 8
  • 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: 15000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0377 1.0 15000 1.0757 0.1553

Framework versions

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

Citation

@misc{deepdml/whisper-medium-ar-quran-mix,
      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}},
      year={2025}
    }
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