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Baselhany
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Graduation_Project_Whisper_tiny

Automatic Speech Recognition
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Safetensors
Arabic
whisper
Generated from Trainer
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  1. README.md +22 -27
  2. model.safetensors +1 -1
  3. runs/Dec27_16-42-01_dd832112ce1d/events.out.tfevents.1735332648.dd832112ce1d.40.1 +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: 0.0256
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- - Wer: 0.1250
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- - Cer: 0.0445
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  ## Model description
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@@ -41,7 +41,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -50,33 +50,28 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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- - num_epochs: 20
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  - mixed_precision_training: Native AMP
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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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- | 0.0263 | 0.9973 | 187 | 0.0205 | 0.1624 | 0.0613 |
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- | 0.0093 | 2.0 | 375 | 0.0149 | 0.1519 | 0.0529 |
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- | 0.0051 | 2.9973 | 562 | 0.0157 | 0.1580 | 0.0512 |
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- | 0.004 | 4.0 | 750 | 0.0181 | 0.1636 | 0.0539 |
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- | 0.002 | 4.9973 | 937 | 0.0193 | 0.1557 | 0.0502 |
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- | 0.0011 | 6.0 | 1125 | 0.0206 | 0.1558 | 0.0506 |
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- | 0.0009 | 6.9973 | 1312 | 0.0213 | 0.1513 | 0.0498 |
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- | 0.0005 | 8.0 | 1500 | 0.0214 | 0.1544 | 0.0504 |
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- | 0.0004 | 8.9973 | 1687 | 0.0220 | 0.1464 | 0.0458 |
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- | 0.0004 | 10.0 | 1875 | 0.0216 | 0.1459 | 0.0461 |
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- | 0.0002 | 10.9973 | 2062 | 0.0224 | 0.1452 | 0.0454 |
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- | 0.0001 | 12.0 | 2250 | 0.0224 | 0.1437 | 0.0452 |
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- | 0.0001 | 12.9973 | 2437 | 0.0234 | 0.2224 | 0.0832 |
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- | 0.0 | 14.0 | 2625 | 0.0231 | 0.1356 | 0.0540 |
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- | 0.0 | 14.9973 | 2812 | 0.0236 | 0.2134 | 0.0797 |
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- | 0.0 | 16.0 | 3000 | 0.0241 | 0.2159 | 0.0796 |
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- | 0.0 | 16.9973 | 3187 | 0.0253 | 0.1338 | 0.0517 |
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- | 0.0 | 18.0 | 3375 | 0.0257 | 0.1271 | 0.0493 |
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- | 0.0 | 18.9973 | 3562 | 0.0264 | 0.1287 | 0.0492 |
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- | 0.0 | 19.9467 | 3740 | 0.0266 | 0.1280 | 0.0489 |
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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: 0.0206
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+ - Wer: 0.1174
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+ - Cer: 0.0425
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 15
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  - mixed_precision_training: Native AMP
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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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+ | 0.0204 | 1.0 | 250 | 0.0218 | 0.1251 | 0.0425 |
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+ | 0.0116 | 2.0 | 500 | 0.0125 | 0.1298 | 0.0427 |
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+ | 0.0086 | 3.0 | 750 | 0.0116 | 0.1229 | 0.0421 |
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+ | 0.0049 | 4.0 | 1000 | 0.0121 | 0.1227 | 0.0449 |
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+ | 0.0041 | 5.0 | 1250 | 0.0130 | 0.1231 | 0.0415 |
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+ | 0.0029 | 6.0 | 1500 | 0.0143 | 0.1207 | 0.0407 |
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+ | 0.0013 | 7.0 | 1750 | 0.0155 | 0.12 | 0.0390 |
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+ | 0.0018 | 8.0 | 2000 | 0.0165 | 0.1265 | 0.0449 |
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+ | 0.0008 | 9.0 | 2250 | 0.0173 | 0.1245 | 0.0414 |
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+ | 0.0002 | 10.0 | 2500 | 0.0179 | 0.1222 | 0.0406 |
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+ | 0.0002 | 11.0 | 2750 | 0.0182 | 0.1186 | 0.0400 |
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+ | 0.0002 | 12.0 | 3000 | 0.0184 | 0.1198 | 0.0398 |
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+ | 0.0001 | 13.0 | 3250 | 0.0187 | 0.1198 | 0.0404 |
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+ | 0.0001 | 14.0 | 3500 | 0.0206 | 0.1174 | 0.0425 |
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+ | 0.0 | 15.0 | 3750 | 0.0190 | 0.1189 | 0.0399 |
 
 
 
 
 
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  ### Framework versions
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