Output_LayoutLMv3_v3

Noureddinesa/Output_LayoutLMv3_v3

Output_LayoutLMv3_v3 is a token classification model from Noureddinesa. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-nc-sa-4.0.

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

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At a glance

Task: Token Classification
Library: transformers
License: cc-by-nc-sa-4.0
Model type: layoutlmv3
Access: Public
Created: Apr 4, 2024
Updated: Apr 4, 2024
SHA: 02c2c916

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Base models

microsoft/layoutlmv3-large

Model card

From the Hugging Face model README

Output_LayoutLMv3_v3

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: 0.1344
Precision: 0.7699
Recall: 0.8142
F1: 0.7914
Accuracy: 0.9695

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: 3e-07
train_batch_size: 4
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	4.55	100	0.5786	0.0	0.0	0.0	0.8867
No log	9.09	200	0.4032	0.0	0.0	0.0	0.8867
No log	13.64	300	0.2908	0.4091	0.1593	0.2293	0.9067
No log	18.18	400	0.2300	0.5858	0.4381	0.5013	0.9267
0.5251	22.73	500	0.1981	0.685	0.6062	0.6432	0.9438
0.5251	27.27	600	0.1790	0.7130	0.6814	0.6968	0.9505
0.5251	31.82	700	0.1689	0.7249	0.7345	0.7297	0.9581
0.5251	36.36	800	0.1593	0.7478	0.7478	0.7478	0.9619
0.5251	40.91	900	0.1582	0.75	0.7832	0.7662	0.9638
0.129	45.45	1000	0.1527	0.7306	0.7920	0.7601	0.9619
0.129	50.0	1100	0.1470	0.7429	0.8053	0.7728	0.9638
0.129	54.55	1200	0.1418	0.7552	0.8053	0.7794	0.9657
0.129	59.09	1300	0.1404	0.7657	0.8097	0.7871	0.9667
0.129	63.64	1400	0.1368	0.7741	0.8186	0.7957	0.9695
0.0799	68.18	1500	0.1316	0.7741	0.8186	0.7957	0.9705
0.0799	72.73	1600	0.1301	0.7764	0.8142	0.7948	0.9705
0.0799	77.27	1700	0.1326	0.7699	0.8142	0.7914	0.9695
0.0799	81.82	1800	0.1357	0.7552	0.8053	0.7794	0.9676
0.0799	86.36	1900	0.1304	0.7699	0.8142	0.7914	0.9695
0.0561	90.91	2000	0.1326	0.7699	0.8142	0.7914	0.9695
0.0561	95.45	2100	0.1340	0.7689	0.8097	0.7888	0.9695
0.0561	100.0	2200	0.1371	0.7635	0.8142	0.7880	0.9686
0.0561	104.55	2300	0.1337	0.7764	0.8142	0.7948	0.9705
0.0561	109.09	2400	0.1310	0.7764	0.8142	0.7948	0.9705
0.0451	113.64	2500	0.1353	0.7657	0.8097	0.7871	0.9686
0.0451	118.18	2600	0.1357	0.7657	0.8097	0.7871	0.9686
0.0451	122.73	2700	0.1361	0.7699	0.8142	0.7914	0.9695
0.0451	127.27	2800	0.1358	0.7667	0.8142	0.7897	0.9686
0.0451	131.82	2900	0.1347	0.7699	0.8142	0.7914	0.9695
0.0414	136.36	3000	0.1344	0.7699	0.8142	0.7914	0.9695

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Token Classification
Library: transformers
Type: layoutlmv3
License: cc-by-nc-sa-4.0
Created: Apr 4, 2024
Updated: Apr 4, 2024