Results. Like other hybrid models we utilize the hyperparameters, α and ρ, to determine the relative contribution of each loss objective. Figure shows the performance of 19 models trained with variably weighted objectives on both distribution (NUV) and chemical metrics (QED and synthetic accessibility). Full scores are reported in the appendices. In general, high performance models are clustered towards the center of the left edge in the low adversarial training regime. We select the best performing model, across both distribution and chemical metrics, with α = 0.1 and ρ = 0.42 for subsequent experiments.