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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: 0.0278 |
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- Wer: 0.8483 |
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- Cer: 0.4043 |
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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: 25 |
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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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| 0.0691 | 1.0 | 157 | 0.0645 | 4.6639 | 1.8253 | |
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| 0.0429 | 2.0 | 314 | 0.0408 | 1.8489 | 0.8577 | |
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| 0.0287 | 3.0 | 471 | 0.0332 | 2.3785 | 1.2099 | |
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| 0.0224 | 4.0 | 628 | 0.0293 | 1.3376 | 0.7609 | |
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| 0.012 | 5.0 | 785 | 0.0276 | 1.8050 | 0.9207 | |
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| 0.0098 | 6.0 | 942 | 0.0273 | 2.0293 | 1.0277 | |
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| 0.0076 | 7.0 | 1099 | 0.0272 | 1.1354 | 0.5388 | |
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| 0.0068 | 8.0 | 1256 | 0.0288 | 0.6950 | 0.3135 | |
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| 0.0042 | 9.0 | 1413 | 0.0292 | 0.9439 | 0.4304 | |
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| 0.003 | 10.0 | 1570 | 0.0290 | 1.5183 | 0.7840 | |
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| 0.0024 | 11.0 | 1727 | 0.0301 | 0.8514 | 0.3949 | |
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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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