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--- |
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library_name: transformers |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper base AR - BA |
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results: [] |
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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 base AR - BA |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) 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: 0.0875 |
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- Wer: 0.1939 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 1.9262 | 1.0 | 469 | 0.0907 | 0.1917 | |
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| 1.8739 | 2.0 | 938 | 0.0907 | 0.1874 | |
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| 1.4395 | 3.0 | 1407 | 0.0898 | 0.1991 | |
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| 1.3835 | 4.0 | 1876 | 0.0880 | 0.2003 | |
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| 1.1837 | 5.0 | 2345 | 0.0884 | 0.2065 | |
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| 1.0963 | 6.0 | 2814 | 0.0870 | 0.2020 | |
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| 1.0446 | 7.0 | 3283 | 0.0877 | 0.1967 | |
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| 0.8945 | 8.0 | 3752 | 0.0867 | 0.1895 | |
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| 0.8261 | 9.0 | 4221 | 0.0858 | 0.1986 | |
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| 0.7863 | 10.0 | 4690 | 0.0849 | 0.1889 | |
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| 0.7641 | 11.0 | 5159 | 0.0854 | 0.1932 | |
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| 0.6898 | 12.0 | 5628 | 0.0853 | 0.1910 | |
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| 0.6968 | 13.0 | 6097 | 0.0845 | 0.1914 | |
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| 0.6905 | 14.0 | 6566 | 0.0846 | 0.1914 | |
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| 0.6316 | 14.9685 | 7020 | 0.0846 | 0.1858 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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