Nicolettem/bert-sentiment-nic

✈️ BERT Airline Sentiment Classifier

A DistilBERT-based model fine-tuned for sentiment analysis on airline-related tweets. It classifies input text into positive, neutral, or negative sentiment categories.

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🧠 Model Details

Model Description

This model uses distilbert-base-uncased as a base and is fine-tuned on a cleaned dataset of airline tweets. It performs multi-class classification with 3 sentiment labels.

• Developed by: Nicolettem
• Model type: Transformer-based (DistilBERT)
• Language(s): English (en)
• License: MIT
• Fine-tuned from: distilbert-base-uncased

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📦 Model Sources

• Repository: https://huggingface.co/Nicolettem/bert-sentiment-nic
• Demo Space: Gradio Demo
• Dataset: Chidvi201/Twitter_Data.csv

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💡 Uses

Direct Use

You can use this model to classify sentiment of customer reviews or tweets — especially in the airline or travel domain.

Downstream Use

It can serve as a base for training more domain-specific sentiment models, or be integrated into social media monitoring tools.

Out-of-Scope Use

• The model was not trained on non-English tweets or formal customer service chat.
• It may reflect dataset biases and perform poorly on sarcastic or ambiguous text.

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⚠️ Bias, Risks, and Limitations

• May reflect biases in public Tweets