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: 0.1510
  • Wer: 8.3289

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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1195 2.9326 1000 0.1951 19.3987
0.0139 5.8651 2000 0.1341 8.9514
0.0021 8.7977 3000 0.1413 8.7343
0.001 11.7302 4000 0.1489 8.1841
0.0005 14.6628 5000 0.1510 8.3289

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.4.1.post303
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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