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Make sure you have the necessary input data ready for the fine-tuning process.
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Clone the shahrukhx01bert-mini repo from Github and navigate to the directory.
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Run the 'python run_glue.py' command with the necessary arguments to start the fine-tuning process.
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Monitor the training progress and adjust hyperparameters as needed.
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Once the fine-tuning is completed, evaluate the model performance and make any necessary adjustments.

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shahrukhx01bert-mini-finetune-question-detection at main is a machine learning model optimized for detecting questions in text, often used in natural language processing tasks.
Individuals or organizations that utilize this model for projects requiring question detection and analysis may need to file relevant documentation.
To fill out the shahrukhx01bert-mini-finetune-question-detection at main, users typically input text data into the model, which processes it to identify questions.
The purpose of shahrukhx01bert-mini-finetune-question-detection at main is to accurately identify and categorize questions within textual data for various applications.
The information that must be reported includes the input text, the detected questions, and any relevant performance metrics of the model.
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