table-transformer-structure-recognition-v1.1-all-finetuned

sumitD/table-transformer-structure-recognition-v1.1-all-finetuned

table-transformer-structure-recognition-v1.1-all-finetuned is a object detection model from sumitD. Use it when you need objects located in an image. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Object Detection
Library: transformers
License: mit
Model type: table-transformer
Access: Public
Created: Feb 6, 2025
Updated: Feb 8, 2025
SHA: 97807ea2

Model card

From the Hugging Face model README

table-transformer-structure-recognition-v1.1-all-finetuned

This model is a fine-tuned version of sumitD/table-transformer-structure-recognition-v1.1-all-finetuned on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1419
Map: 0.9219
Map 50: 0.966
Map 75: 0.9496
Map Small: -1.0
Map Medium: 0.8782
Map Large: 0.921
Mar 1: 0.5537
Mar 10: 0.9407
Mar 100: 0.9694
Mar Small: -1.0
Mar Medium: 0.9079
Mar Large: 0.9693
Map Table: 0.9882
Mar 100 Table: 0.9964
Map Table column: 0.9732
Mar 100 Table column: 0.9892
Map Table column header: 0.9543
Mar 100 Table column header: 0.9847
Map Table projected row header: 0.8673
Mar 100 Table projected row header: 0.964
Map Table row: 0.9584
Mar 100 Table row: 0.9838
Map Table spanning cell: 0.7903
Mar 100 Table spanning cell: 0.8983

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Map 50	Map 75	Map Small	Map Medium	Map Large	Mar 1	Mar 10	Mar 100	Mar Small	Mar Medium	Mar Large	Map Table	Mar 100 Table	Map Table column	Mar 100 Table column	Map Table column header	Mar 100 Table column header	Map Table projected row header	Mar 100 Table projected row header	Map Table row	Mar 100 Table row	Map Table spanning cell	Mar 100 Table spanning cell
0.2338	1.0	23715	0.1991	0.8756	0.9505	0.9307	-1.0	0.7912	0.8748	0.5395	0.9175	0.9471	-1.0	0.8518	0.947	0.9844	0.9935	0.9582	0.981	0.9111	0.9647	0.7701	0.9364	0.9147	0.9577	0.7149	0.8496
0.2048	2.0	47430	0.1915	0.8827	0.9567	0.9384	-1.0	0.8103	0.8823	0.54	0.9197	0.9498	-1.0	0.8538	0.9499	0.9855	0.9944	0.9564	0.9819	0.9047	0.9527	0.7905	0.9437	0.9222	0.9651	0.7371	0.8607
0.1841	3.0	71145	0.1605	0.9087	0.9636	0.9467	-1.0	0.8373	0.9077	0.548	0.933	0.9616	-1.0	0.8868	0.9613	0.9836	0.9935	0.9703	0.9888	0.94	0.9771	0.8468	0.9545	0.9466	0.9781	0.765	0.8778
0.1914	4.0	94860	0.1496	0.9181	0.9652	0.9496	-1.0	0.8741	0.917	0.552	0.9387	0.9678	-1.0	0.9024	0.9676	0.9886	0.9968	0.9724	0.9886	0.9508	0.9824	0.8561	0.9628	0.9574	0.9829	0.7836	0.8934
0.1739	5.0	118575	0.1419	0.9219	0.966	0.9496	-1.0	0.8782	0.921	0.5537	0.9407	0.9694	-1.0	0.9079	0.9693	0.9882	0.9964	0.9732	0.9892	0.9543	0.9847	0.8673	0.964	0.9584	0.9838	0.7903	0.8983

Framework versions

Transformers 4.48.2
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0

Task: Object Detection
Library: transformers
Type: table-transformer
License: mit
Created: Feb 6, 2025
Updated: Feb 8, 2025