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--- |
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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-large-v3 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- ahishamm/QURANICWhisperDataset |
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metrics: |
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- wer |
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model-index: |
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- name: QURANIC Whisper Large V3 - 10000 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: QURANICWhisperDataset |
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type: ahishamm/QURANICWhisperDataset |
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args: 'config: ar, split: train' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 99.93905329450803 |
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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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# QURANIC Whisper Large V3 - 10000 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the QURANICWhisperDataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2528 |
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- Wer: 99.9391 |
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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: 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: 500 |
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- training_steps: 10000 |
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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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| 0.0907 | 2.0 | 1000 | 0.1326 | 107.4287 | |
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| 0.0545 | 4.0 | 2000 | 0.1366 | 156.4231 | |
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| 0.0211 | 6.0 | 3000 | 0.1515 | 245.3308 | |
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| 0.0076 | 8.0 | 4000 | 0.1627 | 330.6630 | |
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| 0.0031 | 10.0 | 5000 | 0.1788 | 170.7794 | |
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| 0.0035 | 12.0 | 6000 | 0.1947 | 107.0630 | |
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| 0.0006 | 14.0 | 7000 | 0.2107 | 98.0091 | |
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| 0.0 | 16.0 | 8000 | 0.2208 | 97.8533 | |
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| 0.0 | 18.0 | 9000 | 0.2426 | 99.7833 | |
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| 0.0 | 20.0 | 10000 | 0.2528 | 99.9391 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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