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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 +23 -23
  2. model.safetensors +1 -1
  3. runs/Feb04_08-22-41_60f3dcd1b7f6/events.out.tfevents.1738680933.60f3dcd1b7f6.18.1 +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-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: 0.0180
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- - Wer: 0.1110
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- - Cer: 0.0427
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  ## Model description
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@@ -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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- | 0.0141 | 1.0 | 157 | 0.0135 | 0.1618 | 0.0599 |
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- | 0.0129 | 2.0 | 314 | 0.0135 | 0.1479 | 0.0451 |
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- | 0.0079 | 3.0 | 471 | 0.0161 | 0.1741 | 0.0609 |
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- | 0.0061 | 4.0 | 628 | 0.0159 | 0.1707 | 0.0537 |
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- | 0.0052 | 5.0 | 785 | 0.0162 | 0.1551 | 0.0519 |
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- | 0.0038 | 6.0 | 942 | 0.0166 | 0.1540 | 0.0520 |
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- | 0.0024 | 7.0 | 1099 | 0.0173 | 0.1332 | 0.0429 |
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- | 0.0019 | 8.0 | 1256 | 0.0171 | 0.1419 | 0.0446 |
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- | 0.0013 | 9.0 | 1413 | 0.0173 | 0.1455 | 0.0514 |
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- | 0.0011 | 10.0 | 1570 | 0.0170 | 0.1374 | 0.0453 |
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- | 0.0006 | 11.0 | 1727 | 0.0166 | 0.1292 | 0.0421 |
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- | 0.0004 | 12.0 | 1884 | 0.0170 | 0.1314 | 0.0415 |
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- | 0.0003 | 13.0 | 2041 | 0.0177 | 0.1274 | 0.0407 |
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- | 0.0003 | 14.0 | 2198 | 0.0171 | 0.1207 | 0.0381 |
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- | 0.0002 | 15.0 | 2355 | 0.0173 | 0.1240 | 0.0417 |
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- | 0.0001 | 16.0 | 2512 | 0.0175 | 0.1137 | 0.0362 |
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- | 0.0 | 17.0 | 2669 | 0.0171 | 0.1106 | 0.0378 |
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- | 0.0 | 18.0 | 2826 | 0.0172 | 0.1015 | 0.0341 |
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- | 0.0 | 19.0 | 2983 | 0.0183 | 0.1225 | 0.0464 |
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- | 0.0 | 19.8768 | 3120 | 0.0176 | 0.1821 | 0.0720 |
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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: 0.0190
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+ - Wer: 0.1120
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+ - Cer: 0.0412
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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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+ | 0.0 | 1.0 | 157 | 0.0180 | 0.1046 | 0.0447 |
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+ | 0.0004 | 2.0 | 314 | 0.0212 | 0.1330 | 0.0435 |
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+ | 0.0012 | 3.0 | 471 | 0.0225 | 0.1584 | 0.0497 |
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+ | 0.0017 | 4.0 | 628 | 0.0199 | 0.1611 | 0.0527 |
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+ | 0.0017 | 5.0 | 785 | 0.0210 | 0.1488 | 0.0509 |
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+ | 0.0013 | 6.0 | 942 | 0.0202 | 0.1417 | 0.0458 |
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+ | 0.001 | 7.0 | 1099 | 0.0200 | 0.1520 | 0.0507 |
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+ | 0.001 | 8.0 | 1256 | 0.0199 | 0.1405 | 0.0445 |
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+ | 0.0006 | 9.0 | 1413 | 0.0193 | 0.1491 | 0.0493 |
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+ | 0.0005 | 10.0 | 1570 | 0.0189 | 0.1271 | 0.0411 |
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+ | 0.0004 | 11.0 | 1727 | 0.0197 | 0.1354 | 0.0454 |
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+ | 0.0003 | 12.0 | 1884 | 0.0198 | 0.1289 | 0.0421 |
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+ | 0.0002 | 13.0 | 2041 | 0.0192 | 0.1298 | 0.0439 |
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+ | 0.0001 | 14.0 | 2198 | 0.0197 | 0.1238 | 0.0407 |
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+ | 0.0001 | 15.0 | 2355 | 0.0198 | 0.1189 | 0.0412 |
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+ | 0.0 | 16.0 | 2512 | 0.0191 | 0.1146 | 0.0398 |
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+ | 0.0 | 17.0 | 2669 | 0.0194 | 0.1140 | 0.0395 |
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+ | 0.0 | 18.0 | 2826 | 0.0199 | 0.1073 | 0.0359 |
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+ | 0.0 | 19.0 | 2983 | 0.0215 | 0.1089 | 0.0403 |
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+ | 0.0 | 19.8768 | 3120 | 0.0210 | 0.1084 | 0.0363 |
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  ### Framework versions
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