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Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
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Michele Dolfi
2025-09-10 08:43:29 +02:00
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tests/data/groundtruth/docling_v2/2305.03393v1-pg9.md vendored
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@@ -6,13 +6,12 @@ We have chosen the PubTabNet data set to perform HPO, since it includes a highly
Table 1. HPO performed in OTSL and HTML representation on the same transformer-based TableFormer [9] architecture, trained only on PubTabNet [22]. Effects of reducing the # of layers in encoder and decoder stages of the model show that smaller models trained on OTSL perform better, especially in recognizing complex table structures, and maintain a much higher mAP score than the HTML counterpart.
| # enc-layers | # dec-layers | Language | TEDs | TEDs | TEDs | mAP (0.75) | Inference time (secs) |
|----------------|----------------|------------|-------------|-------------|-------------|--------------|-------------------------|
| # enc-layers | # dec-layers | Language | simple | complex | all | mAP (0.75) | Inference time (secs) |
| 6 | 6 | OTSL HTML | 0.965 0.969 | 0.934 0.927 | 0.955 0.955 | 0.88 0.857 | 2.73 5.39 |
| 4 | 4 | OTSL HTML | 0.938 0.952 | 0.904 0.909 | 0.927 0.938 | 0.853 0.843 | 1.97 3.77 |
| 2 | 4 | OTSL HTML | 0.923 0.945 | 0.897 0.901 | 0.915 0.931 | 0.859 0.834 | 1.91 3.81 |
| 4 | 2 | OTSL HTML | 0.952 0.944 | 0.92 0.903 | 0.942 0.931 | 0.857 0.824 | 1.22 2 |
| #enc-layers | #dec-layers | Language | TEDs | TEDs | TEDs | mAP(0.75) | Inferencetime (secs) |
|---------------|---------------|------------|-------------|-------------|-------------|-------------|------------------------|
| 6 | 6 | OTSL HTML | 0.965 0.969 | 0.934 0.927 | 0.955 0.955 | 0.88 0.857 | 2.73 5.39 |
| 4 | 4 | OTSL HTML | 0.938 0.952 | 0.904 0.909 | 0.927 0.938 | 0.853 0.843 | 1.97 3.77 |
| 2 | 4 | OTSL HTML | 0.923 0.945 | 0.897 0.901 | 0.915 0.931 | 0.859 0.834 | 1.91 3.81 |
| 4 | 2 | OTSL HTML | 0.952 0.944 | 0.92 0.903 | 0.942 0.931 | 0.857 0.824 | 1.22 2 |
## 5.2 Quantitative Results