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Whisper small withaq - T5SA

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

  • Loss: 1.6060
  • Wer: 64.0180

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: 6
  • 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
0.0051 22.22 1000 1.3485 66.5792
0.0003 44.44 2000 1.5180 62.4313
0.0002 66.67 3000 1.5829 63.3683
0.0001 88.89 4000 1.6060 64.0180

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Tokenizers 0.15.1
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Evaluation results