LayoutLMv3-wildreceipt – AI Model by fahmiaziz | AlphaNeural AI

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fahmiaziz/
LayoutLMv3-wildreceipt

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token-classification

generated_from_trainer

microsoft/layoutlmv3-base

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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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: 0.3388
Precision: 0.8871
Recall: 0.8800
F1: 0.8835
Accuracy: 0.9465

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: 5e-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
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.6119	1.0	684	0.2890	0.8515	0.7911	0.8202	0.9172
0.2969	2.0	1368	0.2478	0.8720	0.8279	0.8494	0.9302
0.1876	3.0	2052	0.2418	0.8354	0.8737	0.8541	0.9332
0.1476	4.0	2736	0.2480	0.8697	0.8620	0.8658	0.9378
0.1302	5.0	3420	0.2707	0.8692	0.8697	0.8694	0.9405
0.0798	6.0	4104	0.2641	0.8755	0.8798	0.8776	0.9434
0.0642	7.0	4788	0.2694	0.8897	0.8661	0.8777	0.9449
0.0502	8.0	5472	0.3050	0.8878	0.8741	0.8809	0.9462
0.0267	9.0	6156	0.3379	0.8888	0.8750	0.8818	0.9453
0.0273	10.0	6840	0.3388	0.8871	0.8800	0.8835	0.9465

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3