This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the main dataset. It achieves the following results on the evaluation set:

Loss: 1.5136
Precision: 0.5783
Recall: 0.6135
F1: 0.5954
Accuracy: 0.7671

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: 2e-05
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
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.7447	1.0	5905	0.7678	0.4966	0.5209	0.5085	0.7409
0.6153	2.0	11810	0.7378	0.5628	0.5600	0.5614	0.7624
0.4623	3.0	17715	0.7959	0.5449	0.5836	0.5636	0.7573
0.3629	4.0	23620	0.8921	0.5679	0.6017	0.5843	0.7631
0.246	5.0	29525	1.0286	0.5878	0.5955	0.5916	0.7685
0.1923	6.0	35430	1.2142	0.5926	0.5957	0.5941	0.7689
0.1477	7.0	41335	1.3019	0.5681	0.6091	0.5879	0.7591
0.1214	8.0	47240	1.4101	0.5834	0.6110	0.5969	0.7659
0.0793	9.0	53145	1.4745	0.5848	0.6136	0.5989	0.7688
0.0733	10.0	59050	1.5136	0.5783	0.6135	0.5954	0.7671

Framework versions

Transformers 4.36.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.15.0

erickrribeiro/ner_model

ner_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

erickrribeiro/
ner_model