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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: 0.0121 |
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- Wer: 13.2495 |
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- Cer: 4.3278 |
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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: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:-------:|:---------------:|:--------:| |
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| 0.0258 | 0.1408 | 400 | 52.2218 | 0.0246 | 104.9348 | |
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| 0.0177 | 0.2817 | 800 | 10.2633 | 0.0184 | 26.2089 | |
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| 0.0116 | 0.4225 | 1200 | 7.3210 | 0.0160 | 20.9517 | |
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| 0.0101 | 0.5633 | 1600 | 5.8227 | 0.0141 | 17.5020 | |
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| 0.008 | 0.7042 | 2000 | 5.1235 | 0.0127 | 16.3695 | |
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| 0.0057 | 0.8450 | 2400 | 4.8168 | 0.0119 | 15.2343 | |
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| 0.0056 | 0.9858 | 2800 | 4.6678 | 0.0116 | 14.6364 | |
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| 0.0071 | 1.1267 | 3200 | 0.0135 | 15.8929 | 5.3042 | |
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| 0.0059 | 1.2676 | 3600 | 0.0132 | 15.7165 | 5.0437 | |
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| 0.0056 | 1.4084 | 4000 | 0.0124 | 14.5758 | 5.3648 | |
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| 0.0041 | 1.5492 | 4400 | 0.0122 | 14.2259 | 4.7531 | |
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| 0.0038 | 1.6901 | 4800 | 0.0120 | 13.8043 | 4.7431 | |
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| 0.004 | 1.8309 | 5200 | 0.0119 | 14.1818 | 4.9569 | |
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| 0.0036 | 1.9717 | 5600 | 0.0118 | 14.0743 | 4.9171 | |
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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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