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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-tiny |
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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 tiny 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 tiny AR - BH |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) 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: 0.0180 |
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- Wer: 0.1110 |
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- Cer: 0.0427 |
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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: 4 |
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- total_train_batch_size: 64 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 0.0141 | 1.0 | 157 | 0.0135 | 0.1618 | 0.0599 | |
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| 0.0129 | 2.0 | 314 | 0.0135 | 0.1479 | 0.0451 | |
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| 0.0079 | 3.0 | 471 | 0.0161 | 0.1741 | 0.0609 | |
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| 0.0061 | 4.0 | 628 | 0.0159 | 0.1707 | 0.0537 | |
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| 0.0052 | 5.0 | 785 | 0.0162 | 0.1551 | 0.0519 | |
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| 0.0038 | 6.0 | 942 | 0.0166 | 0.1540 | 0.0520 | |
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| 0.0024 | 7.0 | 1099 | 0.0173 | 0.1332 | 0.0429 | |
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| 0.0019 | 8.0 | 1256 | 0.0171 | 0.1419 | 0.0446 | |
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| 0.0013 | 9.0 | 1413 | 0.0173 | 0.1455 | 0.0514 | |
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| 0.0011 | 10.0 | 1570 | 0.0170 | 0.1374 | 0.0453 | |
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| 0.0006 | 11.0 | 1727 | 0.0166 | 0.1292 | 0.0421 | |
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| 0.0004 | 12.0 | 1884 | 0.0170 | 0.1314 | 0.0415 | |
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| 0.0003 | 13.0 | 2041 | 0.0177 | 0.1274 | 0.0407 | |
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| 0.0003 | 14.0 | 2198 | 0.0171 | 0.1207 | 0.0381 | |
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| 0.0002 | 15.0 | 2355 | 0.0173 | 0.1240 | 0.0417 | |
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| 0.0001 | 16.0 | 2512 | 0.0175 | 0.1137 | 0.0362 | |
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| 0.0 | 17.0 | 2669 | 0.0171 | 0.1106 | 0.0378 | |
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| 0.0 | 18.0 | 2826 | 0.0172 | 0.1015 | 0.0341 | |
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| 0.0 | 19.0 | 2983 | 0.0183 | 0.1225 | 0.0464 | |
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| 0.0 | 19.8768 | 3120 | 0.0176 | 0.1821 | 0.0720 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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