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Whisper Small Eg - Tariq Hasaballah 100330

This model is a fine-tuned version of openai/whisper-small on the ASR-EGARBCSC: AN EGYPTIAN ARABIC CONVERSATIONAL SPEECH CORPUS dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5626
  • Wer: 47.4960

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer
0.7309 0.7267 125 0.5984 52.4512
0.3608 1.4535 250 0.5488 48.6031
0.1789 2.1802 375 0.5537 46.5999
0.1844 2.9070 500 0.5626 47.4960

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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