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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: Zolfa-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: 5.263157894736842 |
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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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# Zolfa-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: 0.0157 |
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- Wer: 5.2632 |
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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: 8 |
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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: 5 |
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- training_steps: 1000 |
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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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| 0.0155 | 2.8571 | 100 | 0.0156 | 5.2632 | |
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| 0.0037 | 5.7143 | 200 | 0.0199 | 5.2632 | |
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| 0.0011 | 8.5714 | 300 | 0.0175 | 5.2632 | |
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| 0.0006 | 11.4286 | 400 | 0.0123 | 5.2632 | |
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| 0.0003 | 14.2857 | 500 | 0.0187 | 5.2632 | |
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| 0.0001 | 17.1429 | 600 | 0.0126 | 5.2632 | |
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| 0.0001 | 20.0 | 700 | 0.0159 | 5.2632 | |
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| 0.0002 | 22.8571 | 800 | 0.0137 | 5.2632 | |
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| 0.0001 | 25.7143 | 900 | 0.0149 | 5.2632 | |
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| 0.0001 | 28.5714 | 1000 | 0.0157 | 5.2632 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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