Output_LayoutLMv3_v6

Noureddinesa/Output_LayoutLMv3_v6

Output_LayoutLMv3_v6 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 10, 2024
Updated: Apr 11, 2024
SHA: 3eb4c296

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Datasets

Noureddinesa/LayoutLmv3_v1

Model card

From the Hugging Face model README

Output_LayoutLMv3_v6

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: 0.1308
Precision: 0.7788
Recall: 0.8
F1: 0.7892
Accuracy: 0.9637

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: 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: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.61	100	0.5057	0.0	0.0	0.0	0.8962
No log	3.23	200	0.3746	0.0	0.0	0.0	0.8962
No log	4.84	300	0.2979	0.2143	0.0273	0.0484	0.9014
No log	6.45	400	0.2474	0.4444	0.1455	0.2192	0.9135
0.4794	8.06	500	0.2189	0.5	0.3	0.3750	0.9291
0.4794	9.68	600	0.2031	0.5301	0.4	0.4560	0.9325
0.4794	11.29	700	0.1916	0.6	0.4636	0.5231	0.9377
0.4794	12.9	800	0.1788	0.6364	0.5727	0.6029	0.9412
0.4794	14.52	900	0.1728	0.6796	0.6364	0.6573	0.9464
0.184	16.13	1000	0.1644	0.7010	0.6182	0.6570	0.9481
0.184	17.74	1100	0.1593	0.75	0.7091	0.7290	0.9567
0.184	19.35	1200	0.1520	0.7714	0.7364	0.7535	0.9602
0.184	20.97	1300	0.1420	0.7778	0.7636	0.7706	0.9619
0.184	22.58	1400	0.1427	0.7925	0.7636	0.7778	0.9637
0.1278	24.19	1500	0.1361	0.7727	0.7727	0.7727	0.9619
0.1278	25.81	1600	0.1342	0.8019	0.7727	0.7870	0.9654
0.1278	27.42	1700	0.1310	0.8056	0.7909	0.7982	0.9671
0.1278	29.03	1800	0.1290	0.7857	0.8	0.7928	0.9654
0.1278	30.65	1900	0.1268	0.7946	0.8091	0.8018	0.9671
0.0999	32.26	2000	0.1229	0.7768	0.7909	0.7838	0.9637
0.0999	33.87	2100	0.1305	0.8056	0.7909	0.7982	0.9654
0.0999	35.48	2200	0.1349	0.8241	0.8091	0.8165	0.9689
0.0999	37.1	2300	0.1327	0.8018	0.8091	0.8054	0.9654
0.0999	38.71	2400	0.1289	0.8018	0.8091	0.8054	0.9654
0.0833	40.32	2500	0.1274	0.8018	0.8091	0.8054	0.9654
0.0833	41.94	2600	0.1279	0.8018	0.8091	0.8054	0.9654
0.0833	43.55	2700	0.1295	0.8018	0.8091	0.8054	0.9654
0.0833	45.16	2800	0.1306	0.7788	0.8	0.7892	0.9637
0.0833	46.77	2900	0.1312	0.7788	0.8	0.7892	0.9637
0.0749	48.39	3000	0.1308	0.7788	0.8	0.7892	0.9637

Framework versions

Transformers 4.29.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: layoutlmv3
License: cc-by-nc-sa-4.0
Created: Apr 10, 2024
Updated: Apr 11, 2024