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End of training

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README.md ADDED
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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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+
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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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+
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+ # QURANIC Whisper Large V3 - 10000
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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