Whisper base AR - BH

This model is a fine-tuned version of openai/whisper-base on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0151
  • Wer: 17.8284
  • Cer: 5.3577

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 7
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Cer Validation Loss Wer
0.0425 0.3011 400 11.2952 0.0330 37.6901
0.0258 0.6023 800 7.9539 0.0218 25.4742
0.0197 0.9034 1200 7.0188 0.0194 22.3362
0.0083 1.2637 1600 6.1604 0.0183 20.2225
0.0066 1.5794 2000 5.9469 0.0176 19.4205
0.0065 1.8952 2400 5.8609 0.0174 19.0958
0.0161 2.1084 2800 5.8786 0.0167 18.8094
0.0157 2.4096 3200 5.6719 0.0162 18.4526
0.0157 2.7107 3600 5.6150 0.0160 18.3772
0.0063 3.1595 4000 5.4820 0.0160 18.0877
0.0052 3.4752 4400 5.4747 0.0161 18.2023
0.0049 3.7910 4800 5.5285 0.0161 17.9922
0.0154 3.9155 5200 5.5457 0.0159 18.1641
0.0142 4.2168 5600 5.4871 0.0158 17.9721
0.0143 4.5180 6000 5.5382 0.0157 18.0495
0.0155 4.8191 6400 5.4620 0.0156 17.9460
0.005 5.3710 6800 5.4875 0.0157 17.7691
0.0052 5.6868 7200 5.4416 0.0157 17.8646
0.0085 4.8653 7600 5.5002 0.0157 17.8817
0.0096 5.1216 8000 5.5124 0.0156 17.8264
0.0094 5.3776 8400 5.6387 0.0155 17.7500
0.0093 5.6336 8800 5.4429 0.0154 17.6736
0.01 5.8896 9200 5.3128 0.0153 17.2856
0.0091 6.1453 9600 5.2836 0.0153 17.2424
0.0088 6.4019 10000 0.0153 17.2434 5.2826
0.008 6.6579 10400 0.0153 17.1288 5.2957
0.007 6.9139 10800 0.0153 17.1680 5.2889

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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