layoutlmv3-finetuned-invoice

ronak1998/layoutlmv3-finetuned-invoice

layoutlmv3-finetuned-invoice is a token classification model from ronak1998. Use it when you need labels on individual words, such as names. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
Model type: layoutlmv3
Access: Public
Created: Jun 10, 2022
Updated: Jun 10, 2022
SHA: c64094e3

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Datasets

sroie

Model card

From the Hugging Face model README

layoutlmv3-finetuned-invoice

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

Loss: 0.0030
Precision: 1.0
Recall: 0.9980
F1: 0.9990
Accuracy: 0.9998

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	2.0	100	0.0715	0.972	0.9858	0.9789	0.9971
No log	4.0	200	0.0228	0.972	0.9858	0.9789	0.9971
No log	6.0	300	0.0174	0.972	0.9858	0.9789	0.9971
No log	8.0	400	0.0137	0.972	0.9858	0.9789	0.9971
0.1189	10.0	500	0.0122	0.972	0.9858	0.9789	0.9971
0.1189	12.0	600	0.0112	0.972	0.9858	0.9789	0.9971
0.1189	14.0	700	0.0080	0.972	0.9858	0.9789	0.9971
0.1189	16.0	800	0.0100	0.972	0.9858	0.9789	0.9971
0.1189	18.0	900	0.0040	0.9960	0.9980	0.9970	0.9996
0.0097	20.0	1000	0.0030	1.0	0.9980	0.9990	0.9998
0.0097	22.0	1100	0.0028	0.9980	0.9959	0.9970	0.9996
0.0097	24.0	1200	0.0016	1.0	1.0	1.0	1.0
0.0097	26.0	1300	0.0015	1.0	1.0	1.0	1.0
0.0097	28.0	1400	0.0015	0.9980	0.9980	0.9980	0.9998
0.0029	30.0	1500	0.0017	0.9980	0.9980	0.9980	0.9998
0.0029	32.0	1600	0.0026	0.9960	0.9980	0.9970	0.9996
0.0029	34.0	1700	0.0026	0.9960	0.9980	0.9970	0.9996
0.0029	36.0	1800	0.0026	0.9960	0.9980	0.9970	0.9996
0.0029	38.0	1900	0.0025	0.9960	0.9980	0.9970	0.9996
0.002	40.0	2000	0.0026	0.9960	0.9980	0.9970	0.9996

Framework versions

Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

Task: Token Classification
Library: transformers
Type: layoutlmv3
Created: Jun 10, 2022
Updated: Jun 10, 2022