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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: 0.0206 |
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- Wer: 0.1174 |
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- Cer: 0.0425 |
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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: 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: 15 |
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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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| 0.0204 | 1.0 | 250 | 0.0218 | 0.1251 | 0.0425 | |
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| 0.0116 | 2.0 | 500 | 0.0125 | 0.1298 | 0.0427 | |
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| 0.0086 | 3.0 | 750 | 0.0116 | 0.1229 | 0.0421 | |
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| 0.0049 | 4.0 | 1000 | 0.0121 | 0.1227 | 0.0449 | |
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| 0.0041 | 5.0 | 1250 | 0.0130 | 0.1231 | 0.0415 | |
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| 0.0029 | 6.0 | 1500 | 0.0143 | 0.1207 | 0.0407 | |
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| 0.0013 | 7.0 | 1750 | 0.0155 | 0.12 | 0.0390 | |
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| 0.0018 | 8.0 | 2000 | 0.0165 | 0.1265 | 0.0449 | |
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| 0.0008 | 9.0 | 2250 | 0.0173 | 0.1245 | 0.0414 | |
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| 0.0002 | 10.0 | 2500 | 0.0179 | 0.1222 | 0.0406 | |
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| 0.0002 | 11.0 | 2750 | 0.0182 | 0.1186 | 0.0400 | |
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| 0.0002 | 12.0 | 3000 | 0.0184 | 0.1198 | 0.0398 | |
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| 0.0001 | 13.0 | 3250 | 0.0187 | 0.1198 | 0.0404 | |
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| 0.0001 | 14.0 | 3500 | 0.0206 | 0.1174 | 0.0425 | |
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| 0.0 | 15.0 | 3750 | 0.0190 | 0.1189 | 0.0399 | |
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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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