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The moth Macroglossum stellatarum can learn the colour and sometimes the odour of a rewarding food source. We present data from 20 different experiments with different combinations of blue and yellow artificial flowers and the two odours honeysuckle and lavender. The experiments show that learning about the odours depends on the colour used. By training on different colour-odour 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 to 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 or a learning model with independent learning for each stimulus component were able to explain the experimental data. We present the new categorisation model, which assumes that the moth learns a template for the sensory attributes of the rewarding stimulus. This model produces behaviour that closely matches that of the real moth in all 20 experiments. [ABSTRACT FROM AUTHOR]