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YoussefAshmawy
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Graduation_Project_Whisper_base

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
Generated from Trainer
arabic
quran
Eval Results (legacy)
Model card Files
xet
Metrics Community
YoussefAshmawy commited on
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  1. README.md +30 -30
  2. model.safetensors +1 -1
  3. runs/Feb23_14-26-32_aacc43f5c62c/events.out.tfevents.1740356311.aacc43f5c62c.23.1 +3 -0
README.md CHANGED
@@ -20,9 +20,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0077
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- - Wer: 0.0682
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- - Cer: 0.0271
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  ## Model description
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@@ -55,33 +55,33 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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- |:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
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- | 0.0059 | 0.9991 | 562 | 0.0050 | 0.0695 | 0.0253 |
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- | 0.0017 | 2.0 | 1125 | 0.0060 | 0.0719 | 0.0263 |
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- | 0.0014 | 2.9991 | 1687 | 0.0070 | 0.0813 | 0.0302 |
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- | 0.0009 | 4.0 | 2250 | 0.0073 | 0.0715 | 0.0263 |
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- | 0.0009 | 4.9991 | 2812 | 0.0074 | 0.0706 | 0.0250 |
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- | 0.001 | 6.0 | 3375 | 0.0073 | 0.0722 | 0.0290 |
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- | 0.0008 | 6.9991 | 3937 | 0.0082 | 0.0753 | 0.0260 |
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- | 0.0004 | 8.0 | 4500 | 0.0081 | 0.0740 | 0.0257 |
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- | 0.0003 | 8.9991 | 5062 | 0.0083 | 0.0753 | 0.0299 |
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- | 0.0002 | 10.0 | 5625 | 0.0080 | 0.0637 | 0.0240 |
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- | 0.0004 | 10.9991 | 6187 | 0.0086 | 0.0758 | 0.0276 |
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- | 0.0003 | 12.0 | 6750 | 0.0083 | 0.0760 | 0.0279 |
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- | 0.0002 | 12.9991 | 7312 | 0.0079 | 0.0699 | 0.0267 |
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- | 0.0002 | 14.0 | 7875 | 0.0084 | 0.0655 | 0.0243 |
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- | 0.0001 | 14.9991 | 8437 | 0.0082 | 0.0671 | 0.0246 |
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- | 0.0001 | 16.0 | 9000 | 0.0084 | 0.0641 | 0.0237 |
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- | 0.0 | 16.9991 | 9562 | 0.0092 | 0.0673 | 0.0249 |
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- | 0.0001 | 18.0 | 10125 | 0.0083 | 0.0749 | 0.0276 |
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- | 0.0 | 18.9991 | 10687 | 0.0087 | 0.0670 | 0.0239 |
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- | 0.0 | 20.0 | 11250 | 0.0084 | 0.0661 | 0.0248 |
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- | 0.0 | 20.9991 | 11812 | 0.0085 | 0.0668 | 0.0251 |
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- | 0.0 | 22.0 | 12375 | 0.0087 | 0.0666 | 0.0248 |
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- | 0.0 | 22.9991 | 12937 | 0.0088 | 0.0661 | 0.0246 |
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- | 0.0 | 24.0 | 13500 | 0.0088 | 0.0658 | 0.0271 |
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- | 0.0 | 24.9778 | 14050 | 0.0089 | 0.0653 | 0.0245 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0088
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+ - Wer: 0.0676
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+ - Cer: 0.0268
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
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+ | 0.0015 | 1.0 | 500 | 0.0068 | 0.0731 | 0.0283 |
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+ | 0.0011 | 2.0 | 1000 | 0.0081 | 0.0753 | 0.0294 |
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+ | 0.0004 | 3.0 | 1500 | 0.0075 | 0.0796 | 0.0322 |
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+ | 0.0008 | 4.0 | 2000 | 0.0085 | 0.0764 | 0.0281 |
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+ | 0.0007 | 5.0 | 2500 | 0.0089 | 0.0807 | 0.0311 |
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+ | 0.0006 | 6.0 | 3000 | 0.0083 | 0.0860 | 0.0310 |
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+ | 0.0006 | 7.0 | 3500 | 0.0081 | 0.0784 | 0.0289 |
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+ | 0.0006 | 8.0 | 4000 | 0.0088 | 0.0773 | 0.0270 |
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+ | 0.0003 | 9.0 | 4500 | 0.0079 | 0.0820 | 0.0344 |
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+ | 0.0003 | 10.0 | 5000 | 0.0088 | 0.0813 | 0.0285 |
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+ | 0.0003 | 11.0 | 5500 | 0.0083 | 0.0786 | 0.0282 |
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+ | 0.0001 | 12.0 | 6000 | 0.0083 | 0.0760 | 0.0295 |
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+ | 0.0001 | 13.0 | 6500 | 0.0083 | 0.0691 | 0.0257 |
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+ | 0.0001 | 14.0 | 7000 | 0.0089 | 0.0767 | 0.0298 |
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+ | 0.0002 | 15.0 | 7500 | 0.0085 | 0.0733 | 0.0277 |
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+ | 0.0 | 16.0 | 8000 | 0.0085 | 0.0726 | 0.0268 |
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+ | 0.0 | 17.0 | 8500 | 0.0088 | 0.0681 | 0.0252 |
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+ | 0.0001 | 18.0 | 9000 | 0.0093 | 0.0751 | 0.0309 |
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+ | 0.0003 | 19.0 | 9500 | 0.0087 | 0.0771 | 0.0287 |
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+ | 0.0 | 20.0 | 10000 | 0.0081 | 0.0728 | 0.0255 |
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+ | 0.0 | 21.0 | 10500 | 0.0084 | 0.0737 | 0.0272 |
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+ | 0.0 | 22.0 | 11000 | 0.0086 | 0.0715 | 0.0268 |
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+ | 0.0 | 23.0 | 11500 | 0.0087 | 0.0717 | 0.0268 |
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+ | 0.0 | 24.0 | 12000 | 0.0088 | 0.0676 | 0.0268 |
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+ | 0.0 | 25.0 | 12500 | 0.0088 | 0.0711 | 0.0267 |
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  ### Framework versions
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