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--- |
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base_model: openai/whisper-small |
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datasets: |
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- audiofolder |
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language: |
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- ar |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: quran-recitation-errors-test |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- type: wer |
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value: 9.619238476953909 |
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name: Wer |
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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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# quran-recitation-errors-test |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0732 |
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- Wer: 9.6192 |
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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: 0.001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 100 |
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- training_steps: 500 |
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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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| 0.7162 | 1.6949 | 100 | 0.7662 | 89.5792 | |
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| 0.5519 | 3.3898 | 200 | 0.5851 | 96.9940 | |
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| 0.3149 | 5.0847 | 300 | 0.2195 | 59.9198 | |
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| 0.0931 | 6.7797 | 400 | 0.1326 | 36.6733 | |
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| 0.0072 | 8.4746 | 500 | 0.0732 | 9.6192 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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