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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: 0.0060 |
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- Wer: 0.0688 |
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- Cer: 0.0280 |
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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: 5e-06 |
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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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| 0.0058 | 1.0 | 157 | 0.0056 | 0.0608 | 0.0253 | |
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| 0.0052 | 2.0 | 314 | 0.0055 | 0.0583 | 0.0240 | |
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| 0.0037 | 3.0 | 471 | 0.0054 | 0.0586 | 0.0247 | |
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| 0.0032 | 4.0 | 628 | 0.0054 | 0.0615 | 0.0242 | |
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| 0.0038 | 5.0 | 785 | 0.0056 | 0.0581 | 0.0235 | |
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| 0.0015 | 6.0 | 942 | 0.0058 | 0.0610 | 0.0245 | |
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| 0.0023 | 7.0 | 1099 | 0.0062 | 0.0612 | 0.0245 | |
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| 0.0014 | 8.0 | 1256 | 0.0066 | 0.0639 | 0.0251 | |
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| 0.0013 | 9.0 | 1413 | 0.0070 | 0.0693 | 0.0361 | |
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| 0.0007 | 10.0 | 1570 | 0.0074 | 0.0671 | 0.0349 | |
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| 0.0006 | 11.0 | 1727 | 0.0078 | 0.0695 | 0.0363 | |
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| 0.0002 | 12.0 | 1884 | 0.0082 | 0.0733 | 0.0387 | |
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| 0.0001 | 13.0 | 2041 | 0.0084 | 0.0710 | 0.0374 | |
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| 0.0001 | 14.0 | 2198 | 0.0086 | 0.0688 | 0.0452 | |
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| 0.0002 | 15.0 | 2355 | 0.0088 | 0.0706 | 0.0454 | |
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| 0.0001 | 16.0 | 2512 | 0.0089 | 0.0717 | 0.0455 | |
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| 0.0001 | 17.0 | 2669 | 0.0090 | 0.0711 | 0.0455 | |
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| 0.0001 | 18.0 | 2826 | 0.0090 | 0.0711 | 0.0361 | |
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| 0.0 | 19.0 | 2983 | 0.0098 | 0.0870 | 0.0457 | |
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| 0.0001 | 19.8768 | 3120 | 0.0091 | 0.0706 | 0.0362 | |
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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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