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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 - BA |
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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 - BA |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0034 |
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- Wer: 0.0479 |
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- Cer: 0.0195 |
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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: 0.0001 |
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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 OptimizerNames.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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| 0.0039 | 1.0 | 215 | 0.0034 | 0.0436 | 0.0167 | |
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| 0.0028 | 2.0 | 430 | 0.0039 | 0.0525 | 0.0204 | |
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| 0.0019 | 3.0 | 645 | 0.0051 | 0.0605 | 0.0231 | |
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| 0.0012 | 4.0 | 860 | 0.0054 | 0.0628 | 0.0232 | |
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| 0.0008 | 5.0 | 1075 | 0.0057 | 0.0648 | 0.0240 | |
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| 0.0006 | 6.0 | 1290 | 0.0061 | 0.0597 | 0.0212 | |
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| 0.0006 | 7.0 | 1505 | 0.0063 | 0.0621 | 0.0252 | |
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| 0.0004 | 8.0 | 1720 | 0.0073 | 0.0644 | 0.0251 | |
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| 0.0004 | 9.0 | 1935 | 0.0074 | 0.0621 | 0.0248 | |
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| 0.0002 | 10.0 | 2150 | 0.0081 | 0.0671 | 0.0253 | |
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| 0.0004 | 11.0 | 2365 | 0.0080 | 0.0632 | 0.0221 | |
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| 0.0002 | 12.0 | 2580 | 0.0083 | 0.0565 | 0.0207 | |
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| 0.0001 | 13.0 | 2795 | 0.0090 | 0.0570 | 0.0201 | |
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| 0.0001 | 14.0 | 3010 | 0.0105 | 0.0630 | 0.0263 | |
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| 0.0001 | 15.0 | 3225 | 0.0109 | 0.0608 | 0.0242 | |
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| 0.0001 | 16.0 | 3440 | 0.0118 | 0.0597 | 0.0221 | |
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| 0.0 | 17.0 | 3655 | 0.0119 | 0.0595 | 0.0220 | |
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| 0.0 | 18.0 | 3870 | 0.0130 | 0.0621 | 0.0235 | |
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| 0.0 | 19.0 | 4085 | 0.0133 | 0.0597 | 0.0231 | |
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| 0.0 | 20.0 | 4300 | 0.0133 | 0.0592 | 0.0240 | |
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| 0.0 | 21.0 | 4515 | 0.0135 | 0.0605 | 0.0237 | |
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| 0.0 | 22.0 | 4730 | 0.0135 | 0.0592 | 0.0231 | |
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| 0.0 | 23.0 | 4945 | 0.0135 | 0.0592 | 0.0231 | |
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| 0.0 | 24.0 | 5160 | 0.0124 | 0.0589 | 0.0228 | |
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| 0.0 | 25.0 | 5375 | 0.0135 | 0.0590 | 0.0231 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.0 |
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