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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: 0.0256 |
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- Wer: 0.1250 |
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- Cer: 0.0445 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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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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| 0.0263 | 0.9973 | 187 | 0.0205 | 0.1624 | 0.0613 | |
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| 0.0093 | 2.0 | 375 | 0.0149 | 0.1519 | 0.0529 | |
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| 0.0051 | 2.9973 | 562 | 0.0157 | 0.1580 | 0.0512 | |
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| 0.004 | 4.0 | 750 | 0.0181 | 0.1636 | 0.0539 | |
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| 0.002 | 4.9973 | 937 | 0.0193 | 0.1557 | 0.0502 | |
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| 0.0011 | 6.0 | 1125 | 0.0206 | 0.1558 | 0.0506 | |
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| 0.0009 | 6.9973 | 1312 | 0.0213 | 0.1513 | 0.0498 | |
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| 0.0005 | 8.0 | 1500 | 0.0214 | 0.1544 | 0.0504 | |
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| 0.0004 | 8.9973 | 1687 | 0.0220 | 0.1464 | 0.0458 | |
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| 0.0004 | 10.0 | 1875 | 0.0216 | 0.1459 | 0.0461 | |
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| 0.0002 | 10.9973 | 2062 | 0.0224 | 0.1452 | 0.0454 | |
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| 0.0001 | 12.0 | 2250 | 0.0224 | 0.1437 | 0.0452 | |
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| 0.0001 | 12.9973 | 2437 | 0.0234 | 0.2224 | 0.0832 | |
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| 0.0 | 14.0 | 2625 | 0.0231 | 0.1356 | 0.0540 | |
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| 0.0 | 14.9973 | 2812 | 0.0236 | 0.2134 | 0.0797 | |
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| 0.0 | 16.0 | 3000 | 0.0241 | 0.2159 | 0.0796 | |
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| 0.0 | 16.9973 | 3187 | 0.0253 | 0.1338 | 0.0517 | |
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| 0.0 | 18.0 | 3375 | 0.0257 | 0.1271 | 0.0493 | |
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| 0.0 | 18.9973 | 3562 | 0.0264 | 0.1287 | 0.0492 | |
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| 0.0 | 19.9467 | 3740 | 0.0266 | 0.1280 | 0.0489 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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