Whisper Tiny ar

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

  • Loss: 0.5962
  • Wer: 52.3622
  • Cer: 18.7245

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.04
  • training_steps: 18000

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.1234 0.0556 1000 0.8106 67.0994 25.5658
0.8957 0.1111 2000 0.7234 62.5310 23.3911
0.7114 0.1667 3000 0.6871 59.7675 21.8722
0.6346 0.2222 4000 0.6637 58.1976 20.7336
0.4961 0.2778 5000 0.6545 57.7404 20.7048
0.4354 0.3333 6000 0.6473 56.7948 20.2061
0.3924 0.3889 7000 0.6325 55.8400 20.0139
0.3466 0.4444 8000 0.6274 55.4176 20.1441
0.2979 0.5 9000 0.6206 54.6997 19.6005
0.3099 0.5556 10000 0.6150 54.0166 19.3231
0.2681 0.6111 11000 0.6120 53.5980 19.1106
0.2383 0.6667 12000 0.6113 53.5576 19.4238
0.2582 0.7222 13000 0.6060 52.7515 18.7573
0.1543 0.7778 14000 0.6018 52.6175 18.4895
0.2356 0.8333 15000 0.6023 52.9902 18.9782
0.2031 0.8889 16000 0.5984 52.5165 18.8550
0.2437 0.9444 17000 0.5951 52.4926 18.7514
0.2269 1.0 18000 0.5962 52.3622 18.7245

Framework versions

  • Transformers 4.48.0.dev0
  • Pytorch 2.5.1+cu121
  • Datasets 3.6.0
  • Tokenizers 0.21.0

Citation

Please cite the model using the following BibTeX entry:

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