Whisper Medium Ar - Mostafa Khedr

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2694
  • Wer: 38.0957

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_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2458 0.4156 1000 0.3291 42.8960
0.2301 0.8313 2000 0.2966 42.4461
0.1394 1.2469 3000 0.2905 41.3148
0.108 1.6625 4000 0.2722 38.6282
0.0534 2.0781 5000 0.2694 38.0957

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.4.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1
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