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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-base |
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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 base 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 base AR - BH |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text-segments dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0231 |
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- Wer: 0.2331 |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 0.017 | 1.3333 | 100 | 0.0233 | 0.2610 | |
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| 0.0148 | 2.6667 | 200 | 0.0216 | 0.2495 | |
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| 0.0094 | 4.0 | 300 | 0.0204 | 0.2438 | |
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| 0.0048 | 5.3333 | 400 | 0.0203 | 0.2409 | |
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| 0.0027 | 6.6667 | 500 | 0.0206 | 0.2421 | |
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| 0.0017 | 8.0 | 600 | 0.0213 | 0.2491 | |
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| 0.0007 | 9.3333 | 700 | 0.0218 | 0.2384 | |
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| 0.0005 | 10.6667 | 800 | 0.0221 | 0.2368 | |
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| 0.0003 | 12.0 | 900 | 0.0224 | 0.2372 | |
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| 0.0003 | 13.3333 | 1000 | 0.0226 | 0.2347 | |
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| 0.0003 | 14.6667 | 1100 | 0.0228 | 0.2327 | |
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| 0.0002 | 16.0 | 1200 | 0.0229 | 0.2335 | |
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| 0.0002 | 17.3333 | 1300 | 0.0230 | 0.2331 | |
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| 0.0002 | 18.6667 | 1400 | 0.0231 | 0.2331 | |
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| 0.0002 | 20.0 | 1500 | 0.0231 | 0.2335 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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