Abstract: A synthetic document generator that obtains a configuration for a synthetic document derived from real-world documents. The configuration specifies element templates to be included in the synthetic document and weights for the specified element templates. The system generates synthetic documents based on the configuration; the synthetic documents include diversified versions of the element templates specified in the configuration. Annotation documents are generated for the synthetic documents that include information describing the respective synthetic documents. A machine learning model for analyzing real-world documents can then be trained using the synthetic and annotation documents. Feedback from the analysis of real-world documents by the machine learning model can be used to generate a new configuration for generating additional synthetic and annotation documents which are used to further train the model.