metadata

tags:
  - generated_from_trainer
model-index:
  - name: icdar23-entrydetector_plaintext_breaks_indents_left_diff
    results: []

icdar23-entrydetector_plaintext_breaks_indents_left_diff

This model is a fine-tuned version of HueyNemud/das22-10-camembert_pretrained on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0072
Ebegin: {'precision': 0.9935508345978755, 'recall': 0.9849567506581421, 'f1': 0.9892351274787535, 'number': 2659}
Eend: {'precision': 0.9980857580398163, 'recall': 0.9742152466367713, 'f1': 0.9860060514372163, 'number': 2676}
Overall Precision: 0.9958
Overall Recall: 0.9796
Overall F1: 0.9876
Overall Accuracy: 0.9980

Model description

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.07	300	0.0309	0.9593	0.9879	0.9734	0.9955
0.161	0.14	600	0.0126	0.9890	0.9911	0.9900	0.9982
0.161	0.21	900	0.0116	0.9730	0.9894	0.9811	0.9971
0.0165	0.29	1200	0.0087	0.9938	0.9918	0.9928	0.9987
0.0119	0.36	1500	0.0093	0.9851	0.9937	0.9894	0.9981
0.0119	0.43	1800	0.0055	0.9942	0.9913	0.9928	0.9987
0.0091	0.5	2100	0.0057	0.9951	0.9904	0.9928	0.9987
0.0091	0.57	2400	0.0058	0.9920	0.9936	0.9928	0.9987
0.0083	0.64	2700	0.0059	0.9896	0.9918	0.9907	0.9983
0.0065	0.72	3000	0.0045	0.9968	0.9917	0.9942	0.9990
0.0065	0.79	3300	0.0047	0.9920	0.9937	0.9929	0.9987
0.0054	0.86	3600	0.0050	0.9945	0.9909	0.9926	0.9987
0.0054	0.93	3900	0.0064	0.9838	0.9968	0.9903	0.9983
0.0056	1.0	4200	0.0046	0.9971	0.9920	0.9946	0.9990
0.0034	1.07	4500	0.0037	0.9959	0.9936	0.9948	0.9990
0.0034	1.14	4800	0.0047	0.9983	0.9900	0.9941	0.9989
0.0035	1.22	5100	0.0043	0.9936	0.9951	0.9944	0.9990
0.0035	1.29	5400	0.0061	0.9892	0.9957	0.9925	0.9986
0.002	1.36	5700	0.0057	0.9898	0.9947	0.9923	0.9986
0.0048	1.43	6000	0.0042	0.9954	0.9933	0.9944	0.9990