metadata
license: mit
language:
- en
tags:
- sentiment-analysis
- imdb
- roberta
- text-classification
pipeline_tag: text-classification
base_model: textattack/roberta-base-imdb
IMDB Sentiment RoBERTa
This repository contains a high-accuracy IMDB sentiment classifier for the 2026 machine learning course task.
The model is based on textattack/roberta-base-imdb, a RoBERTa sequence-classification model fine-tuned for IMDB sentiment analysis.
Evaluation
- Dataset:
imdb_top_500.csv - Accuracy: 98.40%
- Correct: 492 / 500
- Required minimum accuracy: 0.92
- Labels:
0 = negative,1 = positive
Usage
from transformers import pipeline
classifier = pipeline(
"sentiment-analysis",
model="ceilf6/imdb-sentiment-roberta",
tokenizer="ceilf6/imdb-sentiment-roberta",
)
print(classifier("This movie is great and deeply moving."))
CI/CD
GitHub Actions evaluates the model and uploads this repository only when accuracy is at least 0.92.