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  # 🛫 Big Bird Flight
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- Big Bird Flight is a fine-tuned version of Google’s BigBird model, optimised for long-text sentiment analysis in the context of airline passenger experiences. It was trained on 2,598 flight review texts, each annotated with a 10-point ordinal sentiment rating ranging from 1 (extremely negative) to 10 (extremely positive).
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  Big Bird Flight captures nuanced emotional gradients in text, offering richer sentiment analysis than conventional binary classification (e.g., positive vs. negative). This makes it particularly useful for applications requiring fine-grained sentiment understanding from lengthy or detailed customer feedback.
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  - Use case: text classification
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  # 📚 Citation
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  If you use this model in your research or applications, appreciate if you could cite as follow.
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- Mat Roni, S. (2025). Big Bird Flight: Fine-tuned BigBird for Ordinal Sentiment Analysis of Airline Reviews. Hugging Face. https://huggingface.co/pvaluedotone/bigbird-flight
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  ## Validation metrics
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  The validation metrics reflects the inherent complexity in the fine granularity of the 10-point scale.
 
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  # 🛫 Big Bird Flight
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+ Big Bird Flight is a fine-tuned version of Google’s BigBird model, optimised for long-text sentiment analysis. It was trained on 2,598 flight review texts, each annotated with a 10-point ordinal sentiment rating ranging from 1 (extremely negative) to 10 (extremely positive).
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  Big Bird Flight captures nuanced emotional gradients in text, offering richer sentiment analysis than conventional binary classification (e.g., positive vs. negative). This makes it particularly useful for applications requiring fine-grained sentiment understanding from lengthy or detailed customer feedback.
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  - Use case: text classification
 
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  # 📚 Citation
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  If you use this model in your research or applications, appreciate if you could cite as follow.
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+ Mat Roni, S. (2025). Big Bird Flight for ordinal sentiment analysis. Hugging Face. https://huggingface.co/pvaluedotone/bigbird-flight
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  ## Validation metrics
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  The validation metrics reflects the inherent complexity in the fine granularity of the 10-point scale.