layoutlmv3-finetuned-funsd – AI Model by Saed2023 | AlphaNeural AI

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Saed2023/
layoutlmv3-finetuned-funsd

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token-classification

generated_from_trainer

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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layoutlmv3-finetuned-funsd

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

Loss: 1.0068
Precision: 0.7998
Recall: 0.8376
F1: 0.8182
Accuracy: 0.8261

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: 2500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	3.33	250	0.5828	0.7015	0.8033	0.7490	0.8022
0.6702	6.67	500	0.5765	0.7499	0.8073	0.7775	0.8253
0.6702	10.0	750	0.7082	0.7755	0.8236	0.7988	0.8160
0.1797	13.33	1000	0.7819	0.7807	0.8366	0.8077	0.8256
0.1797	16.67	1250	0.8199	0.7997	0.8311	0.8151	0.8227
0.0745	20.0	1500	0.9025	0.7943	0.8286	0.8111	0.8231
0.0745	23.33	1750	0.9159	0.7941	0.8470	0.8197	0.8248
0.041	26.67	2000	1.0012	0.7989	0.8385	0.8182	0.8210
0.041	30.0	2250	0.9852	0.8024	0.8450	0.8231	0.8301
0.0246	33.33	2500	1.0068	0.7998	0.8376	0.8182	0.8261

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3