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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: 0.0190 |
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- Wer: 0.1120 |
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- Cer: 0.0412 |
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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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| 0.0 | 1.0 | 157 | 0.0180 | 0.1046 | 0.0447 | |
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| 0.0004 | 2.0 | 314 | 0.0212 | 0.1330 | 0.0435 | |
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| 0.0012 | 3.0 | 471 | 0.0225 | 0.1584 | 0.0497 | |
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| 0.0017 | 4.0 | 628 | 0.0199 | 0.1611 | 0.0527 | |
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| 0.0017 | 5.0 | 785 | 0.0210 | 0.1488 | 0.0509 | |
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| 0.0013 | 6.0 | 942 | 0.0202 | 0.1417 | 0.0458 | |
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| 0.001 | 7.0 | 1099 | 0.0200 | 0.1520 | 0.0507 | |
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| 0.001 | 8.0 | 1256 | 0.0199 | 0.1405 | 0.0445 | |
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| 0.0006 | 9.0 | 1413 | 0.0193 | 0.1491 | 0.0493 | |
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| 0.0005 | 10.0 | 1570 | 0.0189 | 0.1271 | 0.0411 | |
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| 0.0004 | 11.0 | 1727 | 0.0197 | 0.1354 | 0.0454 | |
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| 0.0003 | 12.0 | 1884 | 0.0198 | 0.1289 | 0.0421 | |
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| 0.0002 | 13.0 | 2041 | 0.0192 | 0.1298 | 0.0439 | |
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| 0.0001 | 14.0 | 2198 | 0.0197 | 0.1238 | 0.0407 | |
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| 0.0001 | 15.0 | 2355 | 0.0198 | 0.1189 | 0.0412 | |
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| 0.0 | 16.0 | 2512 | 0.0191 | 0.1146 | 0.0398 | |
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| 0.0 | 17.0 | 2669 | 0.0194 | 0.1140 | 0.0395 | |
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| 0.0 | 18.0 | 2826 | 0.0199 | 0.1073 | 0.0359 | |
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| 0.0 | 19.0 | 2983 | 0.0215 | 0.1089 | 0.0403 | |
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| 0.0 | 19.8768 | 3120 | 0.0210 | 0.1084 | 0.0363 | |
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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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