Optical Character Recognition (OCR) systems frequently encounter difficulties when processing rare or ancient scripts, especially when they occur in historical contexts involving multiple writing systems. These challenges often constrain researchers to fine-tune or to train new OCR models tailored to their specific needs. To support these efforts, we introduce a synthetic dataset comprising 6.2 million lines, specifically geared towards mixed polytonic Greek and Latin scripts. Being augmented with artificially degraded lines, the dataset bolsters strong results when used to train historical OCR models. This resource can be used both for training and testing purposes, and is particularly valuable for researchers working with ancient Greek and limited annotated data. The software used to generate this datasets is linked to below on our Git. This is a sample, but please contact us if you would like access to the whole dataset.