Whisper Large ArabicEnglish - Mostafa Khedr

This model is a fine-tuned version of openai/whisper-large-v2 on the arabic-english-code-switching dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7108
  • Wer: 31.6184

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: 16
  • seed: 42
  • optimizer: Use OptimizerNames.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_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.558 0.6748 1000 0.5802 46.1378
0.3725 1.3495 2000 0.5258 43.1008
0.2131 2.0243 3000 0.5152 34.4890
0.204 2.6991 4000 0.5111 37.8727
0.1012 3.3738 5000 0.5475 34.1839
0.0593 4.0486 6000 0.5693 33.2686
0.0436 4.7233 7000 0.5895 33.0190
0.0189 5.3981 8000 0.6472 31.9235
0.0063 6.0729 9000 0.6850 32.2701
0.0046 6.7476 10000 0.7108 31.6184

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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Dataset used to train MostafaKhidr/whisper-Large-ArabicEnglish

Evaluation results