layoutlmv3-finetuned-cordv2 – AI Model by functionX86 | AlphaNeural AI

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functionX86/
layoutlmv3-finetuned-cordv2

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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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layoutlmv3-finetuned-cordv2

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

Loss: 0.1800
Precision: 0.9519
Recall: 0.9568
F1: 0.9544
Accuracy: 0.9656

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: 5
eval_batch_size: 5
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	1.5625	250	0.7355	0.7503	0.7595	0.7549	0.8216
1.0406	3.125	500	0.4019	0.8576	0.8787	0.8680	0.9006
1.0406	4.6875	750	0.2671	0.9028	0.9260	0.9143	0.9384
0.2814	6.25	1000	0.2293	0.9380	0.9332	0.9356	0.9473
0.2814	7.8125	1250	0.1763	0.9426	0.9445	0.9435	0.9622
0.1349	9.375	1500	0.1926	0.9437	0.9476	0.9456	0.9613
0.1349	10.9375	1750	0.1848	0.9481	0.9579	0.9530	0.9647
0.082	12.5	2000	0.2028	0.9490	0.9558	0.9524	0.9626
0.082	14.0625	2250	0.1878	0.9510	0.9579	0.9544	0.9652
0.0584	15.625	2500	0.1800	0.9519	0.9568	0.9544	0.9656

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1