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  ---
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  license: mit
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  ---
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- BERT-based Text Classification Model
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  This model is a fine-tuned version of the bert-base-uncased model, specifically adapted for text classification across a diverse set of categories. The model has been trained on a rich dataset collected from multiple sources, including the News Category Dataset on Kaggle and various other websites.
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  The model classifies text into one of the following 12 categories:
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  Convenience
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  The model has demonstrated robust performance with an accuracy of 0.721459, F1 score of 0.659451, precision of 0.707620, and recall of 0.635155.
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- Model Architecture
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  The model leverages the BertForSequenceClassification architecture, It has been fine-tuned on the aforementioned dataset, with the following key configuration parameters:
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  Hidden size: 768
 
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  ---
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  license: mit
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  ---
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+ ## BERT-based Text Classification Model
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  This model is a fine-tuned version of the bert-base-uncased model, specifically adapted for text classification across a diverse set of categories. The model has been trained on a rich dataset collected from multiple sources, including the News Category Dataset on Kaggle and various other websites.
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  The model classifies text into one of the following 12 categories:
 
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  Convenience
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  The model has demonstrated robust performance with an accuracy of 0.721459, F1 score of 0.659451, precision of 0.707620, and recall of 0.635155.
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+ ## Model Architecture
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  The model leverages the BertForSequenceClassification architecture, It has been fine-tuned on the aforementioned dataset, with the following key configuration parameters:
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  Hidden size: 768