✈️ 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.


🧠 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

πŸ“¦ Model Sources


πŸ’‘ Uses

Direct Use

You can use this model to classify sentiment of customer reviews or tweets β€” 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.

⚠️ Bias, Risks, and Limitations

  • May reflect biases in public Tweets
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