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--- |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: tarteel-ai/whisper-base-ar-quran |
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tags: |
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- generated_from_trainer |
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datasets: |
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- zolfa |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper-raghadomar |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Zolfa Dataset |
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type: zolfa |
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args: 'config: ar, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 10.344827586206897 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper-raghadomar |
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This model is a fine-tuned version of [tarteel-ai/whisper-base-ar-quran](https://huggingface.co/tarteel-ai/whisper-base-ar-quran) on the Zolfa Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0325 |
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- Wer: 10.3448 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 2 |
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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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- training_steps: 500 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:| |
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| 0.0002 | 1.0 | 21 | 0.0317 | 10.3448 | |
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| 0.0002 | 2.0 | 42 | 0.0287 | 10.3448 | |
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| 0.0001 | 3.0 | 63 | 0.0293 | 10.3448 | |
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| 0.0002 | 4.0 | 84 | 0.0298 | 10.3448 | |
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| 0.0002 | 5.0 | 105 | 0.0281 | 10.3448 | |
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| 0.0002 | 6.0 | 126 | 0.0308 | 10.3448 | |
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| 0.0002 | 7.0 | 147 | 0.0262 | 10.3448 | |
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| 0.0008 | 8.0 | 168 | 0.0341 | 10.3448 | |
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| 0.0002 | 9.0 | 189 | 0.0223 | 3.4483 | |
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| 0.0003 | 10.0 | 210 | 0.0411 | 10.3448 | |
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| 0.0002 | 11.0 | 231 | 0.0357 | 10.3448 | |
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| 0.0003 | 12.0 | 252 | 0.0349 | 10.3448 | |
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| 0.0001 | 13.0 | 273 | 0.0429 | 10.3448 | |
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| 0.0003 | 14.0 | 294 | 0.0311 | 10.3448 | |
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| 0.0003 | 15.0 | 315 | 0.0372 | 10.3448 | |
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| 0.0002 | 16.0 | 336 | 0.0329 | 10.3448 | |
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| 0.0002 | 17.0 | 357 | 0.0390 | 10.3448 | |
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| 0.0004 | 18.0 | 378 | 0.0333 | 10.3448 | |
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| 0.0002 | 19.0 | 399 | 0.0450 | 10.3448 | |
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| 0.0003 | 20.0 | 420 | 0.0384 | 10.3448 | |
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| 0.0002 | 21.0 | 441 | 0.0366 | 10.3448 | |
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| 0.0002 | 22.0 | 462 | 0.0360 | 10.3448 | |
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| 0.0001 | 23.0 | 483 | 0.0441 | 10.3448 | |
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| 0.0006 | 23.8095 | 500 | 0.0325 | 10.3448 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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