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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: 0.0892 |
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- Wer: 0.1918 |
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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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| 1.406 | 1.0 | 625 | 0.0887 | 0.1907 | |
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| 1.3322 | 2.0 | 1250 | 0.0906 | 0.1874 | |
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| 1.2587 | 3.0 | 1875 | 0.0903 | 0.1844 | |
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| 1.1135 | 4.0 | 2500 | 0.0892 | 0.1954 | |
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| 1.0444 | 5.0 | 3125 | 0.0879 | 0.1883 | |
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| 0.9344 | 6.0 | 3750 | 0.0867 | 0.1802 | |
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| 0.9135 | 7.0 | 4375 | 0.0874 | 0.1854 | |
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| 0.8567 | 8.0 | 5000 | 0.0861 | 0.1882 | |
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| 0.7738 | 9.0 | 5625 | 0.0857 | 0.1951 | |
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| 0.7419 | 10.0 | 6250 | 0.0852 | 0.1958 | |
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| 0.7167 | 11.0 | 6875 | 0.0854 | 0.1933 | |
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| 0.6929 | 12.0 | 7500 | 0.0850 | 0.1874 | |
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| 0.6539 | 13.0 | 8125 | 0.0847 | 0.1908 | |
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| 0.6448 | 14.0 | 8750 | 0.0845 | 0.1883 | |
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| 0.5887 | 15.0 | 9375 | 0.0846 | 0.1892 | |
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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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