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QURANIC Whisper Large V3 - 10000

This model is a fine-tuned version of openai/whisper-large-v3 on the QURANICWhisperDataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2528
  • Wer: 99.9391

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: 8
  • 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_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0907 2.0 1000 0.1326 107.4287
0.0545 4.0 2000 0.1366 156.4231
0.0211 6.0 3000 0.1515 245.3308
0.0076 8.0 4000 0.1627 330.6630
0.0031 10.0 5000 0.1788 170.7794
0.0035 12.0 6000 0.1947 107.0630
0.0006 14.0 7000 0.2107 98.0091
0.0 16.0 8000 0.2208 97.8533
0.0 18.0 9000 0.2426 99.7833
0.0 20.0 10000 0.2528 99.9391

Framework versions

  • Transformers 4.39.2
  • Pytorch 2.2.0
  • Datasets 2.18.0
  • Tokenizers 0.15.1
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Dataset used to train ahishamm/finetuned-whisper-quranic-large-v3-10000

Evaluation results