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@@ -26,7 +26,7 @@ It achieves the following results on the evaluation set:
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  ## Model description
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  This model is a BERT (bert-base-uncased) model fine-tuned using the Banking77 dataset for text classification tasks. Banking77 is a dataset designed to categorize customer support messages in the banking and finance domain into 77 distinct categories. This model is specifically tailored for classifying customer complaints and inquiries in the banking sector, helping to assign messages to the correct categories effectively.
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  | Label Index | Intent Category |
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  |-------------|--------------------------------------------------|
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  | 0 | activate_my_card |
 
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  ## Model description
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  This model is a BERT (bert-base-uncased) model fine-tuned using the Banking77 dataset for text classification tasks. Banking77 is a dataset designed to categorize customer support messages in the banking and finance domain into 77 distinct categories. This model is specifically tailored for classifying customer complaints and inquiries in the banking sector, helping to assign messages to the correct categories effectively.
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+ Fine-Tuning Process : https://github.com/saribasmetehan/bank_administrative_assistant/blob/main/BERT_BankingClassifier.ipynb
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  | Label Index | Intent Category |
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  |-------------|--------------------------------------------------|
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  | 0 | activate_my_card |