Performance metrics on the test datasets for the best model, which is trained with 1.0 background weights and rotation augmentations, compared with the original model without fine-tuning.

The Std Dev Diff represents the standard deviation of the differences of the metrics with the original model and the Avg Diff is the average differences compared to the original model. The trained model had a 1.0 background weight, all the layers trainable, 0.001 learning rate, and rotation augmentation (Rotate).