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

Loss: 0.4878
Precision: 0.8762
Recall: 0.8762
F1: 0.8762
Accuracy: 0.8762

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.1244	2.9070	250	0.7630	0.7337	0.7337	0.7337	0.7337
0.2934	5.8140	500	0.4878	0.8762	0.8762	0.8762	0.8762
0.1028	8.7209	750	0.5626	0.8752	0.8752	0.8752	0.8752
0.0539	11.6279	1000	0.6090	0.8719	0.8719	0.8719	0.8719

Framework versions

Transformers 4.45.2
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1

Abinaya/layoutlmv3-finetuned-DocLayNet

layoutlmv3-finetuned-DocLayNet

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Abinaya/
layoutlmv3-finetuned-DocLayNet