RoshaanT1/taha-finetuned-final

Student Feedback Sentiment Analysis (Fine-Tuned)

This model is fine-tuned on top of the Taha base model (roberta architecture) using professional university student feedback. It accurately classifies educational feedback into Positive, Neutral, and Negative sentiments.

Model Information

• Base Model: Taha model (roberta)
• Task: Text Classification / Sentiment Analysis
• Domain: Higher education, course evaluations, and student feedback

Label Mapping (Verify ID alignment in your model's config.json)

• LABEL_0: Negative
• LABEL_1: Neutral
• LABEL_2: Positive

Usage via Transformers

from transformers import pipeline

classifier = pipeline("text-classification", model="RoshaanT1/taha-finetuned-final")
result = classifier("The professor covered advanced topics well, but assignments were long.")
print(result)