Edit model card

xlm-roberta-base-finetuned-lener-br

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

  • Loss: nan
  • Precision: 0.8443
  • Recall: 0.8845
  • F1: 0.8639
  • Accuracy: 0.9752

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: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0832 1.0 1957 nan 0.6752 0.8625 0.7575 0.9578
0.0477 2.0 3914 nan 0.8391 0.8839 0.8609 0.9704
0.029 3.0 5871 nan 0.7530 0.9059 0.8224 0.9648
0.0223 4.0 7828 nan 0.7488 0.8744 0.8067 0.9659
0.0234 5.0 9785 nan 0.7216 0.8783 0.7923 0.9644
0.0171 6.0 11742 nan 0.7072 0.8969 0.7908 0.9642
0.0121 7.0 13699 nan 0.7769 0.8775 0.8241 0.9681
0.0093 8.0 15656 nan 0.7218 0.8772 0.7920 0.9621
0.0074 9.0 17613 nan 0.8241 0.8767 0.8496 0.9739
0.0055 10.0 19570 nan 0.7369 0.8801 0.8021 0.9638
0.0055 11.0 21527 nan 0.8443 0.8845 0.8639 0.9752
0.0029 12.0 23484 nan 0.8338 0.8935 0.8626 0.9753
0.0026 13.0 25441 nan 0.7721 0.8992 0.8308 0.9694
0.004 14.0 27398 nan 0.7466 0.8886 0.8114 0.9672
0.0006 15.0 29355 nan 0.7518 0.8995 0.8190 0.9686

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
Downloads last month
5

Dataset used to train Luciano/xlm-roberta-base-finetuned-lener-br

Evaluation results