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Baselhany
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Graduation_Project_Whisper_tiny3

Automatic Speech Recognition
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Safetensors
Arabic
whisper
Generated from Trainer
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  1. README.md +22 -22
  2. model.safetensors +1 -1
  3. runs/Feb11_06-57-04_e6f34342fa60/events.out.tfevents.1739279666.e6f34342fa60.18.1 +3 -0
README.md CHANGED
@@ -20,8 +20,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) 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: 0.0063
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- - Wer: 0.0715
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  - Cer: 0.0287
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  ## Model description
@@ -57,26 +57,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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- | 0.0063 | 1.0 | 157 | 0.0063 | 0.0671 | 0.0274 |
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- | 0.0064 | 2.0 | 314 | 0.0062 | 0.0695 | 0.0280 |
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- | 0.005 | 3.0 | 471 | 0.0062 | 0.0673 | 0.0268 |
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- | 0.0047 | 4.0 | 628 | 0.0063 | 0.0646 | 0.0259 |
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- | 0.0035 | 5.0 | 785 | 0.0064 | 0.0653 | 0.0259 |
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- | 0.0016 | 6.0 | 942 | 0.0068 | 0.0675 | 0.0264 |
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- | 0.0028 | 7.0 | 1099 | 0.0071 | 0.0690 | 0.0276 |
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- | 0.0022 | 8.0 | 1256 | 0.0076 | 0.0681 | 0.0266 |
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- | 0.0016 | 9.0 | 1413 | 0.0081 | 0.0652 | 0.0262 |
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- | 0.0014 | 10.0 | 1570 | 0.0085 | 0.0671 | 0.0261 |
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- | 0.0007 | 11.0 | 1727 | 0.0090 | 0.0668 | 0.0274 |
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- | 0.0006 | 12.0 | 1884 | 0.0094 | 0.0688 | 0.0363 |
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- | 0.0004 | 13.0 | 2041 | 0.0096 | 0.0662 | 0.0350 |
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- | 0.0002 | 14.0 | 2198 | 0.0099 | 0.0686 | 0.0353 |
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- | 0.0003 | 15.0 | 2355 | 0.0100 | 0.0686 | 0.0355 |
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- | 0.0002 | 16.0 | 2512 | 0.0102 | 0.0697 | 0.0363 |
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- | 0.0001 | 17.0 | 2669 | 0.0103 | 0.0695 | 0.0360 |
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- | 0.0001 | 18.0 | 2826 | 0.0104 | 0.0695 | 0.0363 |
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- | 0.0001 | 19.0 | 2983 | 0.0103 | 0.0876 | 0.0458 |
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- | 0.0001 | 19.8768 | 3120 | 0.0104 | 0.0691 | 0.0365 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) 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: 0.0062
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+ - Wer: 0.0707
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  - Cer: 0.0287
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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+ | 0.0056 | 1.0 | 157 | 0.0061 | 0.0646 | 0.0262 |
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+ | 0.0061 | 2.0 | 314 | 0.0060 | 0.0643 | 0.0263 |
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+ | 0.0055 | 3.0 | 471 | 0.0059 | 0.0715 | 0.0321 |
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+ | 0.0047 | 4.0 | 628 | 0.0060 | 0.0661 | 0.0272 |
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+ | 0.0023 | 5.0 | 785 | 0.0061 | 0.0633 | 0.0257 |
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+ | 0.0035 | 6.0 | 942 | 0.0063 | 0.0652 | 0.0267 |
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+ | 0.0029 | 7.0 | 1099 | 0.0067 | 0.0659 | 0.0274 |
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+ | 0.0017 | 8.0 | 1256 | 0.0070 | 0.0652 | 0.0270 |
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+ | 0.0016 | 9.0 | 1413 | 0.0075 | 0.0668 | 0.0269 |
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+ | 0.0009 | 10.0 | 1570 | 0.0079 | 0.0688 | 0.0282 |
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+ | 0.0007 | 11.0 | 1727 | 0.0082 | 0.0708 | 0.0285 |
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+ | 0.0003 | 12.0 | 1884 | 0.0085 | 0.0713 | 0.0375 |
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+ | 0.0005 | 13.0 | 2041 | 0.0087 | 0.0720 | 0.0299 |
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+ | 0.0002 | 14.0 | 2198 | 0.0089 | 0.0735 | 0.0381 |
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+ | 0.0002 | 15.0 | 2355 | 0.0091 | 0.0742 | 0.0396 |
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+ | 0.0003 | 16.0 | 2512 | 0.0092 | 0.0713 | 0.0299 |
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+ | 0.0001 | 17.0 | 2669 | 0.0093 | 0.0711 | 0.0283 |
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+ | 0.0003 | 18.0 | 2826 | 0.0093 | 0.0710 | 0.0281 |
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+ | 0.0002 | 19.0 | 2983 | 0.0098 | 0.0987 | 0.0418 |
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+ | 0.0001 | 19.8768 | 3120 | 0.0094 | 0.0708 | 0.0279 |
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  ### Framework versions
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