stanford-sentiment-model

Sentiment classifier (positive / negative) fine-tuned from distilbert-base-uncased.

Group members: Raidah and Nawe Dataset: stanfordnlp/imdb

Results on the test set

Metric	Score
Accuracy	0.912
F1	0.9106

Example predictions

I love this movie like no other. It was great to see some of my favorite stars of 30 years ago Today I found "They All Laughed" on VHS on sale in a rental

Limitations

This model is primarily trained on English movie reviews. As a result, it may not generalize well to other domains (e.g. medical, technical, or financial text) or other languages. Additionally, because it is based on DistilBERT, it may struggle to properly interpret nuanced sentiments such as sarcasm, double negations, or mixed languages like Luganda-English slang.