This model is a fine-tuned version of microsoft/layoutlmv3-base on the data_registros_layoutv3 dataset. It achieves the following results on the evaluation set:

Loss: 0.1730
Precision: 0.8168
Recall: 0.8803
F1: 0.8474
Accuracy: 0.9726

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: 5e-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	10.87	250	0.4505	0.2272	0.2460	0.2362	0.8929
0.641	21.74	500	0.2718	0.6121	0.6715	0.6404	0.9374
0.641	32.61	750	0.1971	0.7854	0.8528	0.8177	0.9669
0.2206	43.48	1000	0.1730	0.8168	0.8803	0.8474	0.9726

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

jpino/layoutlmv3-finetuned-registros_v3

layoutlmv3-finetuned-registros_v3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jpino/
layoutlmv3-finetuned-registros_v3