767065a7-998c-4f77-bc46-60d1a5b5ada3
You are investigating the double descent phenomenon in neural networks. A synthetic classification dataset has been generated — GET /info for the exact dimensions and noise level. **Your goal**: Beat the baseline test accuracy (~82%) by modifying the model architecture and training procedure. Map the double descent curve by sweeping model width and observing how test accuracy changes across under-parameterized, interpolation threshold, and over-parameterized regimes. 1. **GET /baseline** to retrieve the baseline training code and dataset description 2. **POST /run** with your modified code to train real MLPs on the dataset 3. Sweep widths, test regularization strategies, and characterize the double descent curve You have a maximum of 40 runs and 3 hours. Explore systematically. Submit: { best_code, experiment_log, methodology }
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