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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: 0.0148 |
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- Wer: 0.1025 |
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- Cer: 0.0366 |
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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: 1e-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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| 0.0104 | 1.0 | 313 | 0.0092 | 0.1131 | 0.0389 | |
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| 0.009 | 2.0 | 626 | 0.0091 | 0.1104 | 0.0405 | |
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| 0.006 | 3.0 | 939 | 0.0093 | 0.1046 | 0.0371 | |
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| 0.0056 | 4.0 | 1252 | 0.0097 | 0.1061 | 0.0369 | |
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| 0.002 | 5.0 | 1565 | 0.0110 | 0.1061 | 0.0375 | |
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| 0.0021 | 6.0 | 1878 | 0.0110 | 0.1052 | 0.0464 | |
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| 0.0012 | 7.0 | 2191 | 0.0117 | 0.1019 | 0.0353 | |
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| 0.0008 | 8.0 | 2504 | 0.0126 | 0.1071 | 0.0457 | |
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| 0.0002 | 9.0 | 2817 | 0.0129 | 0.1019 | 0.0372 | |
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| 0.0002 | 10.0 | 3130 | 0.0140 | 0.1056 | 0.0380 | |
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| 0.0001 | 11.0 | 3443 | 0.0138 | 0.1003 | 0.0337 | |
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| 0.0001 | 12.0 | 3756 | 0.0142 | 0.0977 | 0.0327 | |
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| 0.0 | 13.0 | 4069 | 0.0146 | 0.1014 | 0.0346 | |
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| 0.0 | 14.0 | 4382 | 0.0152 | 0.0988 | 0.0340 | |
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| 0.0 | 15.0 | 4695 | 0.0164 | 0.1040 | 0.0390 | |
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| 0.0 | 16.0 | 5008 | 0.0161 | 0.1005 | 0.0336 | |
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| 0.0 | 17.0 | 5321 | 0.0165 | 0.1005 | 0.0330 | |
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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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