Whisper Small - Egyptian Arabic

This model is a fine-tuned version of openai/whisper-small on the Egyptian Arabic Speech Recognition dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9560
  • Wer: 41.6677

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: 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0518 7.6336 1000 0.7113 42.9166
0.004 15.2672 2000 0.8712 41.2157
0.001 22.9008 3000 0.9327 42.0245
0.0006 30.5344 4000 0.9560 41.6677

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.4.1.post303
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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