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Egyptian Whisper Small

This model is a fine-tuned version of openai/whisper-small on the Egyptian-ASR-MGB-3 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9939
  • Wer: 46.2893

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
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4615 6.8966 100 0.6496 48.0162
0.072 13.7931 200 0.7459 46.3990
0.0122 20.6897 300 0.8380 45.6863
0.0054 27.5862 400 0.8981 45.0764
0.0033 34.4828 500 0.9322 45.2820
0.0025 41.3793 600 0.9555 45.4670
0.002 48.2759 700 0.9724 46.1454
0.0017 55.1724 800 0.9843 45.9467
0.0016 62.0690 900 0.9916 46.0769
0.0015 68.9655 1000 0.9939 46.2893

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.3.0+cu118
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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