pasha

This model is a fine-tuned version of microsoft/layoutlmv3-base on the nielsr/funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0585
• Precision: 0.9867
• Recall: 0.9892
• F1: 0.9879
• Accuracy: 0.9906

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.13	100	0.2664	0.9534	0.9438	0.9486	0.9571
No log	4.26	200	0.1044	0.9756	0.9802	0.9779	0.9838
No log	6.38	300	0.0672	0.9853	0.9899	0.9876	0.9904
No log	8.51	400	0.0634	0.9824	0.9860	0.9842	0.9884
0.2958	10.64	500	0.0585	0.9867	0.9892	0.9879	0.9906
0.2958	12.77	600	0.0511	0.9889	0.9928	0.9908	0.9928
0.2958	14.89	700	0.0503	0.9871	0.9921	0.9896	0.9925
0.2958	17.02	800	0.0529	0.9860	0.9903	0.9881	0.9913
0.2958	19.15	900	0.0581	0.9842	0.9892	0.9867	0.9904
0.0256	21.28	1000	0.0571	0.9849	0.9888	0.9869	0.9901

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.12.1
• Datasets 2.6.1
• Tokenizers 0.13.2