distilbert-base-uncased-finetuned-ner-lenerBr

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the lener_br dataset. It achieves the following results on the evaluation set:

Loss: 0.1555
Precision: 0.7846
Recall: 0.7810
F1: 0.7828
Accuracy: 0.9672

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: 16
eval_batch_size: 16
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
No log	1.0	490	0.1861	0.6380	0.6661	0.6518	0.9446
0.2629	2.0	980	0.1618	0.7063	0.7303	0.7181	0.9537
0.0756	3.0	1470	0.1299	0.7299	0.8010	0.7638	0.9645
0.0443	4.0	1960	0.1422	0.7634	0.7708	0.7671	0.9643
0.0279	5.0	2450	0.1508	0.7870	0.7679	0.7773	0.9648
0.0203	6.0	2940	0.1457	0.7693	0.7815	0.7753	0.9681
0.0143	7.0	3430	0.1508	0.7767	0.7714	0.7740	0.9663
0.0105	8.0	3920	0.1537	0.7812	0.7669	0.7739	0.9671
0.0085	9.0	4410	0.1564	0.7809	0.7681	0.7745	0.9669
0.0064	10.0	4900	0.1555	0.7846	0.7810	0.7828	0.9672

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1

GuiTap
/

distilbert-base-uncased-finetuned-ner-lenerBr

distilbert-base-uncased-finetuned-ner-lenerBr

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for GuiTap/distilbert-base-uncased-finetuned-ner-lenerBr

Dataset used to train GuiTap/distilbert-base-uncased-finetuned-ner-lenerBr

Evaluation results