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movieReview_analysis_model
hibbariz/movieReview_analysis_model
movieReview_analysis_model is a text classification model from hibbariz. Use it when you need a label for a piece of text. The card lists the license as mit.
This model analyzes movie reviews and classify them as "Negative", "Positive", or "Neutral". It is fine-tuned from "cardiffnlp/twitter-roberta-base-sentiment-latest". Scraped 742 custom movie reviews from Rotten Tomat…
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At a glance
- Task
- Text Classification
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jul 3, 2026
- Updated
- Jul 3, 2026
- SHA
- 25463687
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Base models
Model card
From the Hugging Face model README
🎬 Movie Reviews Sentiment Analysis Model
This model analyzes movie reviews and classify them as "Negative", "Positive", or "Neutral".
Base Model
It is fine-tuned from "cardiffnlp/twitter-roberta-base-sentiment-latest".
Dataset Used
Scraped 742 custom movie reviews from Rotten Tomatoes, augmented the data to 974 reviews to resolve class imbalance, and fine-tuned the final dataset on "cardiffnlp/twitter-roberta-base-sentiment-latest".
How to Use
from transformers import pipeline
classifier = pipeline(
"text-classification",
model="hibbariz/movieReview_analysis_model"
)
result = classifier("This movie was absolutely amazing!")
print(result)
Performance
Accuracy : 84%
F1 score : Negative: 81%, Neutral: 68%, Positive: 90%
Classification Report
- Task
- Text Classification
- Type
- roberta
- License
- mit
- Languages
- en
- Created
- Jul 3, 2026
- Updated
- Jul 3, 2026