The moth Macroglossum stellatarum can learn the color and sometimes the odor of a rewarding food source. We present data from 20 different experiments with different combinations of blue and yellow artificial flowers and the two odors, honeysuckle and lavender. The experiments show that learning about the odors depends on the color used. By training on different color—odor combinations and testing on others, it becomes possible to investigate the exact relation between the two modalities during learning. Three computational models were tested in the same experimental situations as the real moths and their predictions were compared with the experimental data. The average error over all experiments as well as the largest deviation from the experimental data were calculated. Neither the Rescorla—Wagner model nor a learning model with independent learning for each stimulus component were able to explain the experimental data. We present the new hawkmoth learning model, which assumes that the moth learns a template for the sensory attributes of the rewarding stimulus. This model produces behavior that closely matches that of the real moth in all 20 experiments.