This model is a fine-tuned version of microsoft/layoutlmv3-base on the invoice_layoutlmv3 dataset. It achieves the following results on the evaluation set:

Loss: 0.3645
Precision: 0.7054
Recall: 0.8541
F1: 0.7726
Accuracy: 0.9625

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: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.79	50	1.7979	0.0228	0.0541	0.0321	0.1410
No log	1.59	100	1.2400	0.0863	0.4216	0.1433	0.2616
No log	2.38	150	0.8691	0.1279	0.6919	0.2159	0.4495
No log	3.17	200	0.6001	0.2323	0.8162	0.3617	0.7570
No log	3.97	250	0.4709	0.4660	0.7784	0.5830	0.9093
No log	4.76	300	0.3986	0.5977	0.8270	0.6939	0.9472
No log	5.56	350	0.3762	0.5714	0.8216	0.6741	0.9454
No log	6.35	400	0.3763	0.7048	0.8649	0.7767	0.9636
No log	7.14	450	0.3696	0.6639	0.8541	0.7470	0.9570
0.71	7.94	500	0.3645	0.7054	0.8541	0.7726	0.9625

Framework versions

Transformers 4.27.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

nitesh-sawadia/layoutlmv3-finetuned-intellectai

layoutlmv3-finetuned-intellectai

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nitesh-sawadia/
layoutlmv3-finetuned-intellectai