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

Loss: 0.4102
Accuracy: 0.8547
F1: 0.8549
Precision: 0.8669
Recall: 0.8547

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: 3.255788747459486e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1993
optimizer: Adam with betas=(0.8445637934160373,0.8338816842140165) and epsilon=2.527092625455385e-08
lr_scheduler_type: linear
num_epochs: 30
label_smoothing_factor: 0.07158711257743958

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4465	1.0	1408	0.4102	0.8547	0.8549	0.8669	0.8547
0.3839	2.0	2816	0.4814	0.8509	0.8497	0.8532	0.8509
0.3945	3.0	4224	0.6362	0.8002	0.7918	0.8258	0.8002
0.3643	4.0	5632	0.4961	0.8248	0.8211	0.8349	0.8248
0.3345	5.0	7040	0.5267	0.8528	0.8532	0.8570	0.8528
0.3053	6.0	8448	0.5902	0.8002	0.7911	0.8292	0.8002

Framework versions

Transformers 4.26.1
Pytorch 1.10.2+cu113
Datasets 2.9.0
Tokenizers 0.13.2