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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: 0.0191 |
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- Wer: 0.1462 |
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- Cer: 0.0494 |
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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-05 |
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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 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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| 0.0148 | 1.0 | 250 | 0.0146 | 0.1685 | 0.0520 | |
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| 0.0109 | 2.0 | 500 | 0.0144 | 0.1765 | 0.0595 | |
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| 0.0082 | 3.0 | 750 | 0.0152 | 0.1634 | 0.0542 | |
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| 0.0065 | 4.0 | 1000 | 0.0155 | 0.1593 | 0.0505 | |
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| 0.0033 | 5.0 | 1250 | 0.0181 | 0.1644 | 0.0571 | |
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| 0.0025 | 6.0 | 1500 | 0.0182 | 0.1558 | 0.0533 | |
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| 0.0024 | 7.0 | 1750 | 0.0180 | 0.1544 | 0.0492 | |
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| 0.0014 | 8.0 | 2000 | 0.0190 | 0.1461 | 0.0508 | |
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| 0.001 | 9.0 | 2250 | 0.0196 | 0.1430 | 0.0479 | |
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| 0.0006 | 10.0 | 2500 | 0.0198 | 0.1467 | 0.0497 | |
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| 0.0005 | 11.0 | 2750 | 0.0198 | 0.1531 | 0.0503 | |
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| 0.0004 | 12.0 | 3000 | 0.0197 | 0.1446 | 0.0473 | |
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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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