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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 - BH |
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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 - BH |
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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-segments dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0253 |
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- Wer: 0.1830 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use 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: 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.0158 | 1.0 | 100 | 0.0179 | 0.2185 | |
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| 0.0131 | 2.0 | 200 | 0.0161 | 0.2154 | |
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| 0.0105 | 3.0 | 300 | 0.0148 | 0.2059 | |
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| 0.0066 | 4.0 | 400 | 0.0144 | 0.2011 | |
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| 0.0046 | 5.0 | 500 | 0.0145 | 0.2011 | |
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| 0.0021 | 6.0 | 600 | 0.0150 | 0.1985 | |
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| 0.0012 | 7.0 | 700 | 0.0154 | 0.1945 | |
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| 0.0004 | 8.0 | 800 | 0.0161 | 0.1890 | |
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| 0.0002 | 9.0 | 900 | 0.0169 | 0.1894 | |
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| 0.0001 | 10.0 | 1000 | 0.0177 | 0.1899 | |
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| 0.0 | 11.0 | 1100 | 0.0185 | 0.1842 | |
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| 0.0 | 12.0 | 1200 | 0.0193 | 0.1850 | |
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| 0.0 | 13.0 | 1300 | 0.0203 | 0.1839 | |
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| 0.0 | 14.0 | 1400 | 0.0214 | 0.1844 | |
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| 0.0 | 15.0 | 1500 | 0.0224 | 0.1804 | |
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| 0.0 | 16.0 | 1600 | 0.0234 | 0.1833 | |
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| 0.0 | 17.0 | 1700 | 0.0243 | 0.1818 | |
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| 0.0 | 18.0 | 1800 | 0.0253 | 0.1830 | |
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| 0.0 | 19.0 | 1900 | 0.0259 | 0.1854 | |
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| 0.0 | 20.0 | 2000 | 0.0261 | 0.1854 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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