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Running on Zero
Running on Zero
| title: Smart MCQ Solver | |
| emoji: 🔥 | |
| colorFrom: red | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 6.22.0 | |
| python_version: '3.12' | |
| app_file: app.py | |
| pinned: false | |
| # Smart MCQ Solver | |
| A fine-tuned **DeBERTa-v3-small** model that ranks the top-3 most likely answers for multiple-choice questions. | |
| ## How It Works | |
| 1. Enter a question prompt and five answer options (A–E). | |
| 2. The model tokenizes each (prompt, option) pair and runs a forward pass. | |
| 3. It returns a ranked list of the top-3 most likely answer letters. | |
| ## Model Details | |
| | Property | Value | | |
| |---|---| | |
| | Base Model | `microsoft/deberta-v3-small` | | |
| | Task | Multiple Choice QA | | |
| | Fine-Tuned On | IITM DL & GenAI Kaggle Competition Dataset | | |
| | Kaggle MAP@3 | **0.75353** | | |
| | Training Epochs | 5 | | |
| | Optimizer | AdamW (lr=1e-5) | | |
| ## Project | |
| This is the deployment component of the IITM Deep Learning & Generative AI project. | |
| - 🔗 **Main Project Repo:** [dl-genai-project-26-t2](https://github.com/soham-zero/dl-genai-project-26-t2) | |