layoutlmv3-finetuned-cord – AI Model by ikmalalfaozi | AlphaNeural AI

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ikmalalfaozi/
layoutlmv3-finetuned-cord

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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-cord_100

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: 0.1687
Precision: 0.9382
Recall: 0.9574
F1: 0.9477
Accuracy: 0.9597

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	1.56	250	0.3730	0.8662	0.8708	0.8685	0.9042
0.3943	3.12	500	0.2683	0.8939	0.9027	0.8983	0.9279
0.3943	4.69	750	0.2232	0.9248	0.9339	0.9293	0.9474
0.1559	6.25	1000	0.2129	0.9301	0.9407	0.9354	0.9504
0.1559	7.81	1250	0.1782	0.9289	0.9529	0.9407	0.9563
0.082	9.38	1500	0.1876	0.9327	0.9483	0.9405	0.9555
0.082	10.94	1750	0.1746	0.9416	0.9559	0.9487	0.9606
0.0486	12.5	2000	0.1848	0.9349	0.9498	0.9423	0.9550
0.0486	14.06	2250	0.1739	0.9439	0.9590	0.9514	0.9623
0.0351	15.62	2500	0.1687	0.9382	0.9574	0.9477	0.9597

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2