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QURANIC Whisper Large V3 - revised

This model is a fine-tuned version of openai/whisper-large-v3 on the Common_voice_16_1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2252
  • Wer: 163.3859

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: 4
  • eval_batch_size: 4
  • 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: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3095 0.21 2000 0.3293 155.0801
0.2412 0.41 4000 0.3059 287.9687
0.1762 0.62 6000 0.2843 152.7845
0.1906 0.82 8000 0.2645 124.8897
0.0952 1.03 10000 0.2535 129.0233
0.0955 1.24 12000 0.2567 141.4259
0.0865 1.44 14000 0.2360 205.5690
0.1363 1.65 16000 0.2288 187.0938
0.1038 1.86 18000 0.2197 178.2311
0.062 2.06 20000 0.2252 163.3859

Framework versions

  • Transformers 4.39.2
  • Pytorch 2.2.0
  • Datasets 2.18.0
  • Tokenizers 0.15.1
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Dataset used to train ahishamm/finetuned-whisper-quranic-large-v3-revised

Evaluation results