dmargutierrez / roberta-base-mapa_fine-ner

huggingface.co
Total runs: 10
24-hour runs: 2
7-day runs: 4
30-day runs: 7
Model's Last Updated: March 21 2023
token-classification

Introduction of roberta-base-mapa_fine-ner

Model Details of roberta-base-mapa_fine-ner

roberta-base-mapa_fine-ner

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

  • Loss: 0.0401
  • Precision: 0.7395
  • Recall: 0.8237
  • F1: 0.7793
  • Accuracy: 0.9917
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
0.0877 1.0 1739 0.0495 0.6861 0.7595 0.7209 0.9903
0.0661 2.0 3478 0.0432 0.7278 0.8092 0.7663 0.9914
0.0633 3.0 5217 0.0403 0.7469 0.8128 0.7785 0.9919
0.059 4.0 6956 0.0401 0.7412 0.8196 0.7784 0.9918
0.063 5.0 8695 0.0400 0.7425 0.8200 0.7793 0.9918
0.0593 6.0 10434 0.0405 0.7332 0.8244 0.7761 0.9916
0.0595 7.0 12173 0.0400 0.7389 0.8222 0.7783 0.9917
0.0593 8.0 13912 0.0401 0.7390 0.8229 0.7787 0.9917
0.0594 9.0 15651 0.0402 0.7374 0.8240 0.7783 0.9917
0.0597 10.0 17390 0.0401 0.7395 0.8237 0.7793 0.9917
Framework versions
  • Transformers 4.26.0
  • Pytorch 1.13.1+cu117
  • Datasets 2.9.0
  • Tokenizers 0.13.2

Runs of dmargutierrez roberta-base-mapa_fine-ner on huggingface.co

10
Total runs
2
24-hour runs
2
3-day runs
4
7-day runs
7
30-day runs

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