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: 0.8293
Precision: 0.6648
Recall: 0.6763
F1: 0.6705
Accuracy: 0.8583

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
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
1.5039	0.3660	250	1.1856	0.1597	0.2785	0.2030	0.5852
0.8176	0.7321	500	0.6027	0.4143	0.5506	0.4728	0.8651
0.5533	1.0981	750	0.6755	0.5946	0.6266	0.6102	0.8649
0.4021	1.4641	1000	0.6233	0.6017	0.6646	0.6316	0.8804

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

ritutweets46/Layoutlmv3-finetuned-DocLayNet-test

Layoutlmv3-finetuned-DocLayNet-test

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ritutweets46/
Layoutlmv3-finetuned-DocLayNet-test