LayoutLMv3_5_entities_filtred_20

This model is a fine-tuned version of microsoft/layoutlmv3-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0001
• Precision: 1.0
• Recall: 1.0
• F1: 1.0
• Accuracy: 1.0

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: 1e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	14.29	100	0.0032	1.0	1.0	1.0	1.0
No log	28.57	200	0.0008	1.0	1.0	1.0	1.0
No log	42.86	300	0.0005	1.0	1.0	1.0	1.0
No log	57.14	400	0.0003	1.0	1.0	1.0	1.0
0.0474	71.43	500	0.0002	1.0	1.0	1.0	1.0
0.0474	85.71	600	0.0002	1.0	1.0	1.0	1.0
0.0474	100.0	700	0.0002	1.0	1.0	1.0	1.0
0.0474	114.29	800	0.0001	1.0	1.0	1.0	1.0
0.0474	128.57	900	0.0001	1.0	1.0	1.0	1.0
0.0004	142.86	1000	0.0001	1.0	1.0	1.0	1.0
0.0004	157.14	1100	0.0001	1.0	1.0	1.0	1.0
0.0004	171.43	1200	0.0001	1.0	1.0	1.0	1.0
0.0004	185.71	1300	0.0001	1.0	1.0	1.0	1.0
0.0004	200.0	1400	0.0001	1.0	1.0	1.0	1.0
0.0002	214.29	1500	0.0001	1.0	1.0	1.0	1.0
0.0002	228.57	1600	0.0001	1.0	1.0	1.0	1.0
0.0002	242.86	1700	0.0001	1.0	1.0	1.0	1.0
0.0002	257.14	1800	0.0001	1.0	1.0	1.0	1.0
0.0002	271.43	1900	0.0001	1.0	1.0	1.0	1.0
0.0002	285.71	2000	0.0001	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.29.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.13.3