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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: 0.0076 |
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- Wer: 0.0861 |
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- Cer: 0.0359 |
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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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| 0.008 | 1.0 | 235 | 0.0066 | 0.0804 | 0.0302 | |
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| 0.0062 | 2.0 | 470 | 0.0064 | 0.0793 | 0.0305 | |
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| 0.0066 | 3.0 | 705 | 0.0063 | 0.0753 | 0.0302 | |
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| 0.0038 | 4.0 | 940 | 0.0064 | 0.0767 | 0.0288 | |
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| 0.0037 | 5.0 | 1175 | 0.0067 | 0.0766 | 0.0296 | |
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| 0.0031 | 6.0 | 1410 | 0.0069 | 0.0751 | 0.0291 | |
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| 0.002 | 7.0 | 1645 | 0.0074 | 0.0809 | 0.0309 | |
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| 0.0013 | 8.0 | 1880 | 0.0077 | 0.0796 | 0.0297 | |
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| 0.0016 | 9.0 | 2115 | 0.0079 | 0.0796 | 0.0297 | |
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| 0.001 | 10.0 | 2350 | 0.0083 | 0.0795 | 0.0297 | |
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| 0.0005 | 11.0 | 2585 | 0.0085 | 0.0780 | 0.0290 | |
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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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