Performance metrics for the validation dataset for models trained with all modifications except for over-sampling (Combined changes) and with just the rotation modification (Rotate).

The Std Dev Diff represents the standard deviation over validation sections of the differences of the metrics to the default rotate augmentation and the Avg Diff is the overall average differences compared to the default model. All models had a background weight of 1.0, all layers fully trainable, and a 0.001 learning rate.