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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-small
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tags:
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- generated_from_trainer
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datasets:
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- MightyStudent/Egyptian-ASR-MGB-3
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metrics:
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- wer
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model-index:
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- name: 'Egyptian Whisper Small '
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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: Egyptian-ASR-MGB-3
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type: MightyStudent/Egyptian-ASR-MGB-3
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args: 'config: ar, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 46.28931679572398
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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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# Egyptian Whisper Small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Egyptian-ASR-MGB-3 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9939
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- Wer: 46.2893
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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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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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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: 1000
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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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| 0.4615 | 6.8966 | 100 | 0.6496 | 48.0162 |
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| 0.072 | 13.7931 | 200 | 0.7459 | 46.3990 |
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| 0.0122 | 20.6897 | 300 | 0.8380 | 45.6863 |
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| 0.0054 | 27.5862 | 400 | 0.8981 | 45.0764 |
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| 0.0033 | 34.4828 | 500 | 0.9322 | 45.2820 |
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| 0.0025 | 41.3793 | 600 | 0.9555 | 45.4670 |
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| 0.002 | 48.2759 | 700 | 0.9724 | 46.1454 |
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| 0.0017 | 55.1724 | 800 | 0.9843 | 45.9467 |
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| 0.0016 | 62.0690 | 900 | 0.9916 | 46.0769 |
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| 0.0015 | 68.9655 | 1000 | 0.9939 | 46.2893 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.3.0+cu118
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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