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{"gt_parse": {"year_11": [{"subject": "History", "grade": "F - 43"}, {"subject": "Artistic Drawing", "grade": "F - 40"}, {"subject": "Greek", "grade": "D+ - 67"}, {"subject": "Language and Literature", "grade": "F - 44"}, {"subject": "Biology", "grade": "F - 52"}, {"subject": "World Sciences", "grade": "F - 45"}, {"subject": "Civic Education", "grade": "F - 58"}, {"subject": "Robotics", "grade": "F - 50"}, {"subject": "Natural Sciences", "grade": "F - 43"}, {"subject": "French", "grade": "F - 33"}]}} |
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{"gt_parse": {"year_11": [{"subject": "Philosophy", "grade": "81"}, {"subject": "History", "grade": "76"}, {"subject": "Latin", "grade": "72"}, {"subject": "Communication", "grade": "76"}, {"subject": "Biology", "grade": "70"}, {"subject": "Visual and Plastic Arts", "grade": "62"}, {"subject": "Contemporary World History", "grade": "56"}, {"subject": "Applied Mathematics", "grade": "57"}]}} |
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{"gt_parse": {"year_11": [{"subject": "Geology", "grade": "C- - 70"}, {"subject": "Philosophy", "grade": "D - 64"}, {"subject": "Spanish as a Foreign Language", "grade": "F - 57"}, {"subject": "History", "grade": "C- - 70"}, {"subject": "Latin", "grade": "F - 53"}, {"subject": "Applied Mathematics", "grade": "B- - 80"}, {"subject": "Technical Drawing", "grade": "D- - 61"}, {"subject": "English Language", "grade": "D - 66"}, {"subject": "Christianity", "grade": "C+ - 77"}, {"subject": "Sports", "grade": "D- - 61"}]}} |
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{"gt_parse": {"year_10": [{"subject": "Biology and Geology", "grade": "50"}, {"subject": "Foreign Language: French", "grade": "43"}, {"subject": "Programming", "grade": "62"}, {"subject": "Music", "grade": "56"}, {"subject": "Natural Sciences", "grade": "44"}, {"subject": "Programming and Robotics", "grade": "60"}, {"subject": "Calculus II", "grade": "48"}, {"subject": "Visual Arts", "grade": "48"}, {"subject": "Civic Education", "grade": "53"}, {"subject": "Technical Drawing and Design", "grade": "37"}, {"subject": "Economics", "grade": "36"}], "year_11": [{"subject": "Geology", "grade": "46"}, {"subject": "Business Economics", "grade": "67"}, {"subject": "Programming", "grade": "49"}, {"subject": "Sports", "grade": "40"}, {"subject": "Artistic Drawing", "grade": "44"}, {"subject": "Drama", "grade": "71"}, {"subject": "Spanish as a Foreign Language", "grade": "57"}, {"subject": "British History", "grade": "62"}, {"subject": "Personal Development", "grade": "47"}]}} |
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{"gt_parse": {"year_9": [{"subject": "Music", "grade": "A- - 91"}, {"subject": "Religious Studies", "grade": "F - 54"}, {"subject": "World Sciences", "grade": "B- - 82"}, {"subject": "History of Philosophy", "grade": "A- - 90"}, {"subject": "Art", "grade": "C - 73"}, {"subject": "Education for Work", "grade": "C - 76"}, {"subject": "Geography", "grade": "C- - 70"}], "year_10": [{"subject": "Artistic Drawing", "grade": "C- - 71"}, {"subject": "Philosophy", "grade": "B- - 81"}, {"subject": "Social Studies", "grade": "D+ - 68"}, {"subject": "History", "grade": "C - 76"}, {"subject": "Civic Education", "grade": "B - 84"}, {"subject": "Computer Science", "grade": "B - 83"}], "year_11": [{"subject": "Programming", "grade": "F - 54"}, {"subject": "British History", "grade": "D+ - 68"}, {"subject": "Economic Sciences", "grade": "D - 65"}, {"subject": "Religious Studies", "grade": "D - 63"}, {"subject": "Civic Education", "grade": "F - 53"}, {"subject": "Geology", "grade": "C - 75"}, {"subject": "Spanish", "grade": "C - 76"}, {"subject": "Tutoring", "grade": "B - 86"}]}} |
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{"gt_parse": {"year_11": [{"subject": "Chemistry", "grade": "53"}, {"subject": "Spanish as a Foreign Language", "grade": "60"}, {"subject": "Literature", "grade": "62"}, {"subject": "Latin", "grade": "62"}, {"subject": "Computer Science", "grade": "53"}, {"subject": "Ethics", "grade": "56"}, {"subject": "History", "grade": "43"}, {"subject": "Greek", "grade": "37"}]}} |
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{"gt_parse": {"year_9": [{"subject": "Natural Sciences", "grade": "C - 74"}, {"subject": "Programming", "grade": "C- - 70"}, {"subject": "Music", "grade": "D- - 60"}, {"subject": "Geology", "grade": "D+ - 68"}, {"subject": "Calculus", "grade": "D+ - 69"}, {"subject": "Spanish", "grade": "F - 59"}, {"subject": "Philosophy", "grade": "C- - 71"}, {"subject": "World Sciences", "grade": "B- - 82"}, {"subject": "Economics", "grade": "F - 51"}, {"subject": "French", "grade": "F - 47"}], "year_10": [{"subject": "Greek", "grade": "D - 63"}, {"subject": "Visual and Audiovisual Arts", "grade": "A - 96"}, {"subject": "Physics and Chemistry", "grade": "B - 86"}, {"subject": "Biology and Geology", "grade": "B- - 80"}, {"subject": "Religious Studies", "grade": "A- - 91"}, {"subject": "Technical Drawing and Design", "grade": "C - 76"}, {"subject": "History", "grade": "C - 73"}, {"subject": "Programming", "grade": "F - 58"}, {"subject": "Natural Sciences", "grade": "F - 57"}, {"subject": "Sports", "grade": "B- - 80"}]}} |
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{"gt_parse": {"year_11": [{"subject": "Geology", "grade": "D- - 62"}, {"subject": "Programming and Robotics", "grade": "F - 51"}, {"subject": "Religious Studies", "grade": "C - 73"}, {"subject": "Algebra II", "grade": "F - 51"}, {"subject": "Biology", "grade": "D - 64"}, {"subject": "History", "grade": "B+ - 89"}, {"subject": "Latin", "grade": "F - 57"}, {"subject": "English Language", "grade": "F - 57"}, {"subject": "Classical Culture", "grade": "C+ - 77"}, {"subject": "Chemistry", "grade": "C - 73"}]}} |
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{"gt_parse": {"year_9": [{"subject": "Science and Technology", "grade": "58"}, {"subject": "Scientific Culture", "grade": "66"}, {"subject": "Geography and History", "grade": "61"}, {"subject": "English Language", "grade": "67"}, {"subject": "Sports", "grade": "63"}, {"subject": "Music", "grade": "82"}, {"subject": "World History", "grade": "70"}, {"subject": "Biology and Geology", "grade": "47"}]}} |
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{"gt_parse": {"year_9": [{"subject": "Natural Sciences", "grade": "D+ - 67"}, {"subject": "French", "grade": "F - 51"}, {"subject": "Music", "grade": "F - 57"}, {"subject": "Classical Culture", "grade": "C - 76"}, {"subject": "Biology", "grade": "B - 83"}, {"subject": "Spanish", "grade": "D - 64"}, {"subject": "Geology", "grade": "B- - 80"}]}} |
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{"gt_parse": {"year_10": [{"subject": "Programming", "grade": "56"}, {"subject": "Greek", "grade": "84"}, {"subject": "Economics", "grade": "69"}, {"subject": "French", "grade": "69"}, {"subject": "Social Sciences", "grade": "66"}, {"subject": "Language and Literature", "grade": "61"}, {"subject": "Biology", "grade": "44"}, {"subject": "Biology and Geology", "grade": "85"}, {"subject": "Spanish as a Foreign Language", "grade": "60"}, {"subject": "Christianity", "grade": "73"}, {"subject": "Technical Drawing and Design", "grade": "64"}], "year_11": [{"subject": "Chemistry", "grade": "84"}, {"subject": "Programming", "grade": "65"}, {"subject": "Robotics", "grade": "79"}, {"subject": "Religion", "grade": "80"}, {"subject": "Music", "grade": "67"}, {"subject": "Language and Literature", "grade": "67"}, {"subject": "Geography", "grade": "54"}, {"subject": "Biology", "grade": "81"}, {"subject": "History of Philosophy", "grade": "53"}]}} |
|
{"gt_parse": {"year_11": [{"subject": "Biology", "grade": "69"}, {"subject": "Biology and Geology", "grade": "86"}, {"subject": "Programming", "grade": "58"}, {"subject": "Economic Sciences", "grade": "83"}, {"subject": "Classical Culture", "grade": "82"}, {"subject": "Latin", "grade": "90"}, {"subject": "Technical Drawing and Design", "grade": "63"}, {"subject": "Chemistry", "grade": "57"}]}} |
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{"gt_parse": {"year_9": [{"subject": "Latin", "grade": "F - 38"}, {"subject": "Visual and Audiovisual Arts", "grade": "F - 47"}, {"subject": "Physics", "grade": "F - 43"}, {"subject": "Computer Science", "grade": "F - 44"}, {"subject": "Foreign Language: French", "grade": "F - 56"}, {"subject": "Values", "grade": "F - 25"}, {"subject": "Artistic Drawing", "grade": "F - 42"}], "year_10": [{"subject": "Greek", "grade": "F - 55"}, {"subject": "Technical Drawing", "grade": "F - 59"}, {"subject": "French", "grade": "F - 55"}, {"subject": "Geology", "grade": "F - 52"}, {"subject": "Personal Development", "grade": "F - 52"}, {"subject": "Calculus I", "grade": "F - 37"}], "year_11": [{"subject": "History", "grade": "F - 58"}, {"subject": "Physics", "grade": "F - 46"}, {"subject": "Programming", "grade": "F - 41"}, {"subject": "Sports", "grade": "F - 39"}, {"subject": "History of Philosophy", "grade": "F - 56"}, {"subject": "Economics", "grade": "F - 37"}, {"subject": "Ethics", "grade": "C- - 71"}, {"subject": "Visual and Plastic Arts", "grade": "F - 35"}]}} |
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{"gt_parse": {"year_10": [{"subject": "Greek", "grade": "57"}, {"subject": "Sports", "grade": "86"}, {"subject": "Physics", "grade": "77"}, {"subject": "Biology and Geology", "grade": "65"}, {"subject": "Music", "grade": "63"}, {"subject": "Christianity", "grade": "57"}, {"subject": "Technical Drawing and Design", "grade": "74"}]}} |
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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 and you can access the generation pipeline on GitHub.
Introduction ℹ️
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.
Hardware ⚙️
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 💪
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 |
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