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update model card README.md

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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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+ tags:
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+ - hf-asr-leaderboard
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+ - generated_from_trainer
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+ datasets:
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+ - MohammadJamalaldeen/Sudanese_Dialect
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Sudanese Whisper - MohammadJamalaldeen
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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: Sudanese Dialect
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+ type: MohammadJamalaldeen/Sudanese_Dialect
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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: 109.00443880786304
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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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+ # Sudanese Whisper - MohammadJamalaldeen
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sudanese Dialect dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9342
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+ - Wer: 109.0044
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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: 4000
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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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+ | 0.3694 | 1.66 | 1000 | 0.8267 | 83.6398 |
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+ | 0.136 | 3.31 | 2000 | 0.8340 | 107.5460 |
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+ | 0.0695 | 4.97 | 3000 | 0.8763 | 80.6806 |
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+ | 0.0198 | 6.62 | 4000 | 0.9342 | 109.0044 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.2