metadata

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

icdar23-entrydetector_plaintext_breaks_indents_left_ref_right_ref

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: 0.0033
Ebegin: {'precision': 0.9935849056603774, 'recall': 0.9902218879277924, 'f1': 0.9919005462422301, 'number': 2659}
Eend: {'precision': 0.996606334841629, 'recall': 0.9876681614349776, 'f1': 0.9921171171171171, 'number': 2676}
Overall Precision: 0.9951
Overall Recall: 0.9889
Overall F1: 0.9920
Overall Accuracy: 0.9989

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	0.0262	0.9758	0.9906	0.9832	0.9973
0.1599	0.14	600	0.0116	0.9866	0.9919	0.9892	0.9982
0.1599	0.21	900	0.0111	0.9907	0.9856	0.9882	0.9980
0.0162	0.29	1200	0.0096	0.9813	0.9966	0.9889	0.9981
0.0099	0.36	1500	0.0060	0.9820	0.9955	0.9887	0.9982
0.0099	0.43	1800	0.0046	0.9925	0.9934	0.9929	0.9988
0.0074	0.5	2100	0.0057	0.9961	0.9880	0.9920	0.9987
0.0074	0.57	2400	0.0039	0.9911	0.9953	0.9932	0.9988
0.0072	0.64	2700	0.0075	0.9842	0.9949	0.9895	0.9982
0.0061	0.72	3000	0.0040	0.9906	0.9963	0.9934	0.9989
0.0061	0.79	3300	0.0034	0.9955	0.9936	0.9946	0.9991
0.005	0.86	3600	0.0034	0.9933	0.9946	0.9939	0.9990
0.005	0.93	3900	0.0047	0.9847	0.9976	0.9911	0.9985
0.0041	1.0	4200	0.0031	0.9972	0.9936	0.9954	0.9992
0.0031	1.07	4500	0.0030	0.9967	0.9945	0.9956	0.9992
0.0031	1.14	4800	0.0032	0.9966	0.9938	0.9952	0.9992
0.003	1.22	5100	0.0029	0.9960	0.9939	0.9949	0.9991
0.003	1.29	5400	0.0030	0.9935	0.9947	0.9941	0.9990
0.0023	1.36	5700	0.0028	0.9973	0.9933	0.9953	0.9992
0.0027	1.43	6000	0.0029	0.9968	0.9936	0.9952	0.9992