--- language: - en - es license: mit task_categories: - token-classification - image-to-text dataset_info: - config_name: en-digital-line-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 1528452363.5 num_examples: 7324 - name: test num_bytes: 660277381.375 num_examples: 4349 - name: validation num_bytes: 380001163.125 num_examples: 1831 download_size: 2439152560 dataset_size: 2568730908.0 - config_name: en-digital-line-degradation-token-class features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 1308204410.5 num_examples: 7324 - name: test num_bytes: 667860812.375 num_examples: 4349 - name: validation num_bytes: 328648972.125 num_examples: 1831 download_size: 1939598688 dataset_size: 2304714195.0 - config_name: en-digital-noisy-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 9285315096.204 num_examples: 7324 - name: test num_bytes: 5354978035.979 num_examples: 4349 - name: validation num_bytes: 2314801961.801 num_examples: 1831 download_size: 16949790450 dataset_size: 16955095093.984001 - config_name: en-digital-paragraph-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 2229537140.5 num_examples: 7324 - name: test num_bytes: 1082553772.375 num_examples: 4349 - name: validation num_bytes: 562015994.125 num_examples: 1831 download_size: 3780901541 dataset_size: 3874106907.0 - config_name: en-digital-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 3422825072.42 num_examples: 7324 - name: test num_bytes: 1800300619.069 num_examples: 4349 - name: validation num_bytes: 867013113.894 num_examples: 1831 download_size: 6044707011 dataset_size: 6090138805.383 - config_name: en-digital-token-class features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 3589429586.092 num_examples: 7324 - name: test num_bytes: 1865825239.069 num_examples: 4349 - name: validation num_bytes: 900934318.573 num_examples: 1831 download_size: 6105490832 dataset_size: 6356189143.734 - config_name: en-digital-water-mark-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 9493898414.204 num_examples: 7324 - name: test num_bytes: 5445631949.979 num_examples: 4349 - name: validation num_bytes: 2345257044.801 num_examples: 1831 download_size: 17266354391 dataset_size: 17284787408.984 - config_name: en-render-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 19131026017.588 num_examples: 7324 - name: test num_bytes: 11101342722.574 num_examples: 4349 - name: validation num_bytes: 4749558423.85 num_examples: 1831 download_size: 34947880371 dataset_size: 34981927164.012 - config_name: en-render-token-class features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 19310797485.304 num_examples: 7324 - name: test num_bytes: 11186335750.574 num_examples: 4349 - name: validation num_bytes: 4823864845.204 num_examples: 1831 download_size: 35049028878 dataset_size: 35320998081.082 - config_name: es-digital-id-pictures-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 38645127357.518 num_examples: 68958 - name: test num_bytes: 23144152543.612 num_examples: 37572 - name: validation num_bytes: 9673770789.694 num_examples: 17214 download_size: 15872441928 dataset_size: 71463050690.824 - config_name: es-digital-line-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 1420327224.625 num_examples: 8115 - name: test num_bytes: 840561310.75 num_examples: 4426 - name: validation num_bytes: 354456927.5 num_examples: 2028 download_size: 2484806404 dataset_size: 2615345462.875 - config_name: es-digital-noisy-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 10077770681.165 num_examples: 8115 - name: test num_bytes: 5506645799.046 num_examples: 4426 - name: validation num_bytes: 2515230390.388 num_examples: 2028 download_size: 18091878184 dataset_size: 18099646870.599 - config_name: es-digital-paragraph-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 2112885586.625 num_examples: 8115 - name: test num_bytes: 1291718016.75 num_examples: 4426 - name: validation num_bytes: 527436571.5 num_examples: 2028 download_size: 3821261507 dataset_size: 3932040174.875 - config_name: es-digital-rotation-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 4929470926.625 num_examples: 8115 - name: test num_bytes: 2848655347.75 num_examples: 4426 - name: validation num_bytes: 1234699474.5 num_examples: 2028 download_size: 8989933249 dataset_size: 9012825748.875 - config_name: es-digital-rotation-zoom-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 4379022537.625 num_examples: 8115 - name: test num_bytes: 2413011874.75 num_examples: 4426 - name: validation num_bytes: 1072557318.5 num_examples: 2028 download_size: 7775701141 dataset_size: 7864591730.875 - config_name: es-digital-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 3515604711.065 num_examples: 8115 - name: test num_bytes: 2068684395.052 num_examples: 4426 - name: validation num_bytes: 880373678.928 num_examples: 2028 download_size: 6392517545 dataset_size: 6464662785.045 - config_name: es-digital-token-class features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 3660686914.385 num_examples: 8115 - name: test num_bytes: 2144109186.052 num_examples: 4426 - name: validation num_bytes: 911001647.288 num_examples: 2028 download_size: 6450619089 dataset_size: 6715797747.725 - config_name: es-digital-water-mark-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 8313141873.165 num_examples: 8115 - name: test num_bytes: 3754006058.046 num_examples: 4426 - name: validation num_bytes: 2089740478.388 num_examples: 2028 download_size: 14128389199 dataset_size: 14156888409.599 - config_name: es-digital-zoom-0.25-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 506348327.625 num_examples: 8115 - name: test num_bytes: 289091190.75 num_examples: 4426 - name: validation num_bytes: 126715497.5 num_examples: 2028 download_size: 792005831 dataset_size: 922155015.875 - config_name: es-digital-zoom-0.5-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 1367086119.625 num_examples: 8115 - name: test num_bytes: 800981398.75 num_examples: 4426 - name: validation num_bytes: 342193004.5 num_examples: 2028 download_size: 2409127866 dataset_size: 2510260522.875 - config_name: es-digital-zoom-0.625-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 2317680243.625 num_examples: 8115 - name: test num_bytes: 1362390239.75 num_examples: 4426 - name: validation num_bytes: 580195971.5 num_examples: 2028 download_size: 4168274084 dataset_size: 4260266454.875 - config_name: es-digital-zoom-0.7-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 2802494365.625 num_examples: 8115 - name: test num_bytes: 1646572325.75 num_examples: 4426 - name: validation num_bytes: 701742911.5 num_examples: 2028 download_size: 5069331399 dataset_size: 5150809602.875 - config_name: es-digital-zoom-0.75-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 3021265561.625 num_examples: 8115 - name: test num_bytes: 1779209852.75 num_examples: 4426 - name: validation num_bytes: 756387213.5 num_examples: 2028 download_size: 5479755776 dataset_size: 5556862627.875 - config_name: es-digital-zoom-degradation-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 2683259660.625 num_examples: 8115 - name: test num_bytes: 1559658742.75 num_examples: 4426 - name: validation num_bytes: 666851737.5 num_examples: 2028 download_size: 8639660041 dataset_size: 4909770140.875 - config_name: es-render-seq features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 20956369016.935 num_examples: 8115 - name: test num_bytes: 11530001568.862 num_examples: 4426 - name: validation num_bytes: 5264019060.636 num_examples: 2028 download_size: 37775576850 dataset_size: 37750389646.433 - config_name: es-render-token-class features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 21158864973.565 num_examples: 8115 - name: test num_bytes: 11627401262.862 num_examples: 4426 - name: validation num_bytes: 5282897644.0 num_examples: 2028 download_size: 37873172957 dataset_size: 38069163880.427 configs: - config_name: en-digital-line-degradation-seq data_files: - split: train path: en-digital-line-degradation-seq/train-* - split: test path: en-digital-line-degradation-seq/test-* - split: validation path: en-digital-line-degradation-seq/validation-* - config_name: en-digital-line-degradation-token-class data_files: - split: train path: en-digital-line-degradation-token-class/train-* - split: test path: en-digital-line-degradation-token-class/test-* - split: validation path: en-digital-line-degradation-token-class/validation-* - config_name: en-digital-noisy-degradation-seq data_files: - split: train path: en-digital-noisy-degradation-seq/train-* - split: test path: en-digital-noisy-degradation-seq/test-* - split: validation path: en-digital-noisy-degradation-seq/validation-* - config_name: en-digital-paragraph-degradation-seq data_files: - split: train path: en-digital-paragraph-degradation-seq/train-* - split: test path: en-digital-paragraph-degradation-seq/test-* - split: validation path: en-digital-paragraph-degradation-seq/validation-* - config_name: en-digital-seq data_files: - split: train path: en-digital-seq/train-* - split: test path: en-digital-seq/test-* - split: validation path: en-digital-seq/validation-* - config_name: en-digital-token-class data_files: - split: train path: en-digital-token-class/train-* - split: test path: en-digital-token-class/test-* - split: validation path: en-digital-token-class/validation-* - config_name: en-digital-water-mark-degradation-seq data_files: - split: train path: en-digital-water-mark-degradation-seq/train-* - split: test path: en-digital-water-mark-degradation-seq/test-* - split: validation path: en-digital-water-mark-degradation-seq/validation-* - config_name: en-render-seq data_files: - split: train path: en-render-seq/train-* - split: test path: en-render-seq/test-* - split: validation path: en-render-seq/validation-* - config_name: en-render-token-class data_files: - split: train path: en-render-token-class/train-* - split: test path: en-render-token-class/test-* - split: validation path: en-render-token-class/validation-* - config_name: es-digital-id-pictures-degradation-seq data_files: - split: train path: es-digital-id-pictures-degradation-seq/train-* - split: test path: es-digital-id-pictures-degradation-seq/test-* - split: validation path: es-digital-id-pictures-degradation-seq/validation-* - config_name: es-digital-line-degradation-seq data_files: - split: train path: es-digital-line-degradation-seq/train-* - split: test path: es-digital-line-degradation-seq/test-* - split: validation path: es-digital-line-degradation-seq/validation-* - config_name: es-digital-noisy-degradation-seq data_files: - split: train path: es-digital-noisy-degradation-seq/train-* - split: test path: es-digital-noisy-degradation-seq/test-* - split: validation path: es-digital-noisy-degradation-seq/validation-* - config_name: es-digital-paragraph-degradation-seq data_files: - split: train path: es-digital-paragraph-degradation-seq/train-* - split: test path: es-digital-paragraph-degradation-seq/test-* - split: validation path: es-digital-paragraph-degradation-seq/validation-* - config_name: es-digital-rotation-degradation-seq data_files: - split: train path: es-digital-rotation-degradation-seq/train-* - split: test path: es-digital-rotation-degradation-seq/test-* - split: validation path: es-digital-rotation-degradation-seq/validation-* - config_name: es-digital-rotation-zoom-degradation-seq data_files: - split: train path: es-digital-rotation-zoom-degradation-seq/train-* - split: test path: es-digital-rotation-zoom-degradation-seq/test-* - split: validation path: es-digital-rotation-zoom-degradation-seq/validation-* - config_name: es-digital-seq data_files: - split: train path: es-digital-seq/train-* - split: test path: es-digital-seq/test-* - split: validation path: es-digital-seq/validation-* - config_name: es-digital-token-class data_files: - split: train path: es-digital-token-class/train-* - split: test path: es-digital-token-class/test-* - split: validation path: es-digital-token-class/validation-* - config_name: es-digital-water-mark-degradation-seq data_files: - split: train path: es-digital-water-mark-degradation-seq/train-* - split: test path: es-digital-water-mark-degradation-seq/test-* - split: validation path: es-digital-water-mark-degradation-seq/validation-* - config_name: es-digital-zoom-0.25-degradation-seq data_files: - split: train path: es-digital-zoom-0.25-degradation-seq/train-* - split: test path: es-digital-zoom-0.25-degradation-seq/test-* - split: validation path: es-digital-zoom-0.25-degradation-seq/validation-* - config_name: es-digital-zoom-0.5-degradation-seq data_files: - split: train path: es-digital-zoom-0.5-degradation-seq/train-* - split: test path: es-digital-zoom-0.5-degradation-seq/test-* - split: validation path: es-digital-zoom-0.5-degradation-seq/validation-* - config_name: es-digital-zoom-0.625-degradation-seq data_files: - split: train path: es-digital-zoom-0.625-degradation-seq/train-* - split: test path: es-digital-zoom-0.625-degradation-seq/test-* - split: validation path: es-digital-zoom-0.625-degradation-seq/validation-* - config_name: es-digital-zoom-0.7-degradation-seq data_files: - split: train path: es-digital-zoom-0.7-degradation-seq/train-* - split: test path: es-digital-zoom-0.7-degradation-seq/test-* - split: validation path: es-digital-zoom-0.7-degradation-seq/validation-* - config_name: es-digital-zoom-0.75-degradation-seq data_files: - split: train path: es-digital-zoom-0.75-degradation-seq/train-* - split: test path: es-digital-zoom-0.75-degradation-seq/test-* - split: validation path: es-digital-zoom-0.75-degradation-seq/validation-* - config_name: es-digital-zoom-degradation-seq data_files: - split: train path: es-digital-zoom-degradation-seq/train-* - split: test path: es-digital-zoom-degradation-seq/test-* - split: validation path: es-digital-zoom-degradation-seq/validation-* - config_name: es-render-seq data_files: - split: train path: es-render-seq/train-* - split: test path: es-render-seq/test-* - split: validation path: es-render-seq/validation-* - config_name: es-render-token-class data_files: - split: train path: es-render-token-class/train-* - split: test path: es-render-token-class/test-* - split: validation path: es-render-token-class/validation-* tags: - synthetic ---

Visual Abstract

# The MERIT Dataset 🎒📃🏆 The MERIT Dataset is a multimodal dataset (image + text + layout) designed for training and benchmarking Large Language Models (LLMs) on Visually Rich Document Understanding (VrDU) tasks. It is a fully labeled synthetic dataset generated using our opensource pipeline available on [GitHub](https://github.com/nachoDRT/MERIT-Dataset). You can explore more details about the dataset and pipeline reading our [paper](https://arxiv.org/abs/2409.00447). ## Introduction ℹī¸ AI faces some dynamic and technical issues that push end-users to create and gather their own data. In addition, multimodal LLMs are gaining more and more attention, but datasets to train them might be improved to be more complex, more flexible, and easier to gather/generate. In this research project, we identify school transcripts of records as a suitable niche to generate a synthetic challenging multimodal dataset (image + text + layout) for Token Classification or Sequence Generation.

demo

## Hardware ⚙ī¸ We ran the dataset generator on an MSI Meg Infinite X 10SF-666EU with an Intel Core i9-10900KF and an Nvidia RTX 2080 GPU, running on Ubuntu 20.04. Energy values in the table refer to 1k samples, and time values refer to one sample. | Task | Energy (kWh) | Time (s) | |------------------------------|--------------|----------| | Generate digital samples | 0.016 | 2 | | Modify samples in Blender | 0.366 | 34 | ## Benchmark đŸ’Ē We train the LayoutLM family models on Token Classification to demonstrate the suitability of our dataset. The MERIT Dataset poses a challenging scenario with more than 400 labels. We benchmark on three scenarios with an increasing presence of Blender-modified samples. + Scenario 1: We train and test on digital samples. + Scenario 2: We train with digital samples and test with Blender-modified samples. + Scenario 3: We train and test with Blender-modified samples. | | **Scenario 1** | **Scenario 2** | **Scenario 3** | **FUNSD/** | **Lang.** | **(Tr./Val./Test)** | |------------------|----------------|----------------|----------------|------------|-----------|----------------------| | | Dig./Dig. | Dig./Mod. | Mod./Mod | XFUND | | | | | F1 | F1 | F1 | F1 | | | | **LayoutLMv2** | 0.5536 | 0.3764 | 0.4984 | 0.8276 | Eng. | 7324 / 1831 / 4349 | | **LayoutLMv3** | 0.3452 | 0.2681 | 0.6370 | 0.9029 | Eng. | 7324 / 1831 / 4349 | | **LayoutXLM** | 0.5977 | 0.3295 | 0.4489 | 0.7550 | Spa. | 8115 / 2028 / 4426 | ## Citation If you find our research interesting, please cite our work. 📄✏ī¸ ```bibtex @article{de2025merit, title={The MERIT dataset: Modelling and efficiently rendering interpretable transcripts}, author={De Rodrigo, Ignacio and Sanchez-Cuadrado, Alberto and Boal, Jaime and Lopez-Lopez, Alvaro J}, journal={Pattern Recognition}, pages={112502}, year={2025}, publisher={Elsevier} } ``` ## Annex The MERIT Dataset has also been used to fine-tune models and develop the VERSE Methodology. Learn more by reading [VERSE: Visual Embedding Reduction and Space Exploration. Clustering-Guided Insights for Training Data Enhancement in Visually-Rich Document Understanding the VERSE ](https://arxiv.org/abs/2601.05125)