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Whisper Medium Arabic

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

  • eval_loss: 0.0794
  • eval_wer: 5.4226
  • eval_runtime: 200.1714
  • eval_samples_per_second: 0.5
  • eval_steps_per_second: 0.5
  • epoch: 5.7143
  • step: 250

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 400

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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