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Whisper Small Ar_Eg

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

  • Loss: 0.4820
  • Wer: 23.1

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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.058 6.6667 1000 0.3934 23.6625
0.0014 13.3333 2000 0.4452 22.9875
0.0005 20.0 3000 0.4719 22.9375
0.0004 26.6667 4000 0.4820 23.1

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.1.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Evaluation results