Este modelo fue afinado sobre el modelo BSC-LT/roberta-base-bne-capitel-ner sobre conll2002 dataset con un batch_size de 16 logrando la siguiente precisión.

Loss: 0.1071
Precision: 0.8628
Recall: 0.8826
F1: 0.8726
Accuracy: 0.9785

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0681	1.0	521	0.0818	0.8645	0.8842	0.8742	0.9789
0.0313	2.0	1042	0.0841	0.8516	0.8768	0.8640	0.9779
0.0179	3.0	1563	0.0979	0.8584	0.8773	0.8677	0.9781
0.0091	4.0	2084	0.0996	0.8600	0.8819	0.8708	0.9784
0.0068	5.0	2605	0.1071	0.8628	0.8826	0.8726	0.9785

Framework versions

Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

raulgdp/Plant-gob-roberta-base-bne-capitel-ner

Plant-gob-roberta-base-bne-capitel-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

raulgdp/
Plant-gob-roberta-base-bne-capitel-ner