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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: 0.0037 |
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- Wer: 0.0571 |
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- Cer: 0.0223 |
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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: 16 |
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- eval_batch_size: 16 |
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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 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: 25 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 0.0078 | 1.0 | 282 | 0.0037 | 0.0529 | 0.0209 | |
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| 0.0047 | 2.0 | 564 | 0.0040 | 0.0550 | 0.0208 | |
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| 0.0018 | 3.0 | 846 | 0.0050 | 0.0646 | 0.0261 | |
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| 0.0013 | 4.0 | 1128 | 0.0053 | 0.0594 | 0.0224 | |
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| 0.0009 | 5.0 | 1410 | 0.0062 | 0.0659 | 0.0241 | |
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| 0.0008 | 6.0 | 1692 | 0.0066 | 0.0659 | 0.0257 | |
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| 0.0008 | 7.0 | 1974 | 0.0068 | 0.0626 | 0.0243 | |
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| 0.0006 | 8.0 | 2256 | 0.0072 | 0.0615 | 0.0223 | |
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| 0.0006 | 9.0 | 2538 | 0.0075 | 0.0668 | 0.0256 | |
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| 0.0003 | 10.0 | 2820 | 0.0077 | 0.0643 | 0.0238 | |
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| 0.0003 | 11.0 | 3102 | 0.0082 | 0.0577 | 0.0211 | |
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| 0.0002 | 12.0 | 3384 | 0.0090 | 0.0643 | 0.0237 | |
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| 0.0002 | 13.0 | 3666 | 0.0100 | 0.0637 | 0.0222 | |
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| 0.0001 | 14.0 | 3948 | 0.0100 | 0.0615 | 0.0229 | |
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| 0.0001 | 15.0 | 4230 | 0.0104 | 0.0603 | 0.0232 | |
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| 0.0001 | 16.0 | 4512 | 0.0111 | 0.0606 | 0.0216 | |
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| 0.0001 | 17.0 | 4794 | 0.0115 | 0.0614 | 0.0211 | |
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| 0.0 | 18.0 | 5076 | 0.0115 | 0.0570 | 0.0196 | |
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| 0.0 | 19.0 | 5358 | 0.0121 | 0.0614 | 0.0225 | |
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| 0.0 | 20.0 | 5640 | 0.0119 | 0.0595 | 0.0219 | |
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| 0.0 | 21.0 | 5922 | 0.0121 | 0.0588 | 0.0209 | |
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| 0.0 | 22.0 | 6204 | 0.0121 | 0.0597 | 0.0215 | |
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| 0.0 | 23.0 | 6486 | 0.0121 | 0.0601 | 0.0215 | |
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| 0.0 | 24.0 | 6768 | 0.0126 | 0.0609 | 0.0234 | |
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| 0.0 | 24.9130 | 7025 | 0.0121 | 0.0588 | 0.0204 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.0 |
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