djangodevloper/bert-base-uncased-product-review-classification

Model Card for Model ID

A fine-tuned 5-class classifier for understanding product reviews, from 0 (Bad) to 5 (Excellent).

Model Details

This fine-tuned model specializes in analyzing product reviews written by customers. It is designed as a 5-class classification model, where ratings range from 0 (Bad) to 5 (Excellent). The primary goal of the model is to evaluate and interpret customer sentiments regarding the products they have purchased.

Key Features:

Customer Sentiment Analysis: The model accurately classifies reviews into one of five categories, reflecting the sentiment intensity from negative to positive. Business Insights: By categorizing feedback, businesses can identify areas for improvement, track customer satisfaction, and make data-driven decisions. Versatile Applications: Suitable for e-commerce platforms, product quality assessment, and understanding customer behavior. This tool provides a comprehensive approach to gauging customer satisfaction, enabling businesses to enhance product offerings and improve overall user experience.

• Developed by: Deepak shriwastawa
• Model type: bert Multicalss calssification
• Language(s) (NLP): Engilsh
• Finetuned from model [optional]: bert-base-uncased

Model Sources [optional]

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Uses

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

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Training Details

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Training Procedure

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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