metadata
library_name: transformers
tags:
- autotrain
- text-classification
base_model: google/bigbird-roberta-base
widget:
- text: I love AutoTrain
license: mit
language:
- en
metrics:
- accuracy
- bertscore
pipeline_tag: text-classification
Model description
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).
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.
- Use case: text classification
- Sentiment class: 1 (extremely negative) to 10 (extremely positive)
Validation metrics
The validation metrics reflects the inherent complexity in the fine granularity of the 10-point scale.
- loss: 1.7985
- f1_macro: 0.2275
- f1_micro: 0.2665
- f1_weighted: 0.2347
- precision_macro: 0.2676
- precision_micro: 0.2665
- precision_weighted: 0.2777
- recall_macro: 0.2595
- recall_micro: 0.2665
- recall_weighted: 0.2665
- accuracy: 0.2665