βοΈ 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.
π§ 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
π¦ Model Sources
- Repository: https://huggingface.co/Nicolettem/bert-sentiment-nic
- Demo Space: Gradio Demo
- Dataset: Chidvi201/Twitter_Data.csv
π‘ 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.
β οΈ Bias, Risks, and Limitations
- May reflect biases in public Tweets
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Base model
distilbert/distilbert-base-uncased