aryanbabar170205/smart-mcq-roberta-base

RoBERTa-base — Smart MCQ Solver Challenge

Fine-tuned roberta-base on the Smart MCQ Solver Challenge dataset using the AutoModelForMultipleChoice cross-encoder formulation: each of the 5 options is scored as a separate (question, option) pair through one shared encoder, then softmaxed into a ranking.

• Base model: roberta-base (125M params)
• Trained on: 2,000 rows, full-data deployment regime, 6 epochs
• Final training-set fit accuracy: 1.0000
• Part of: DL & GenAI Project [BSDA2001P], Smart MCQ Solver Challenge

See the project repository for the full notebook, EDA and report.