layoutlmv3-finetuned-UsingAlgoDataset_427Images

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0022
• Precision: 0.9892
• Recall: 0.9880
• F1: 0.9886
• Accuracy: 0.9997

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.62	50	0.0349	0.7521	0.6300	0.6857	0.9926
No log	1.25	100	0.0080	0.9538	0.9405	0.9471	0.9985
No log	1.88	150	0.0044	0.9750	0.9723	0.9736	0.9992
No log	2.5	200	0.0032	0.9834	0.9827	0.9831	0.9995
No log	3.12	250	0.0037	0.9710	0.9784	0.9747	0.9992
No log	3.75	300	0.0026	0.9861	0.9852	0.9857	0.9996
No log	4.38	350	0.0023	0.9880	0.9871	0.9875	0.9996
No log	5.0	400	0.0022	0.9883	0.9871	0.9877	0.9997
No log	5.62	450	0.0022	0.9892	0.9880	0.9886	0.9997
0.029	6.25	500	0.0022	0.9892	0.9880	0.9886	0.9997

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3