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whisper-quran

Automatic Speech Recognition
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metadata
language:
  - ar
license: apache-2.0
base_model: tarteel-ai/whisper-base-ar-quran
tags:
  - generated_from_trainer
datasets:
  - zolfa
metrics:
  - wer
model-index:
  - name: Whisper-raghadomar
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Zolfa Dataset
          type: zolfa
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 10.344827586206897

Whisper-raghadomar

This model is a fine-tuned version of tarteel-ai/whisper-base-ar-quran on the Zolfa Dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0325
  • Wer: 10.3448

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: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0002 1.0 21 0.0317 10.3448
0.0002 2.0 42 0.0287 10.3448
0.0001 3.0 63 0.0293 10.3448
0.0002 4.0 84 0.0298 10.3448
0.0002 5.0 105 0.0281 10.3448
0.0002 6.0 126 0.0308 10.3448
0.0002 7.0 147 0.0262 10.3448
0.0008 8.0 168 0.0341 10.3448
0.0002 9.0 189 0.0223 3.4483
0.0003 10.0 210 0.0411 10.3448
0.0002 11.0 231 0.0357 10.3448
0.0003 12.0 252 0.0349 10.3448
0.0001 13.0 273 0.0429 10.3448
0.0003 14.0 294 0.0311 10.3448
0.0003 15.0 315 0.0372 10.3448
0.0002 16.0 336 0.0329 10.3448
0.0002 17.0 357 0.0390 10.3448
0.0004 18.0 378 0.0333 10.3448
0.0002 19.0 399 0.0450 10.3448
0.0003 20.0 420 0.0384 10.3448
0.0002 21.0 441 0.0366 10.3448
0.0002 22.0 462 0.0360 10.3448
0.0001 23.0 483 0.0441 10.3448
0.0006 23.8095 500 0.0325 10.3448

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1