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beto-finetuned-ner-1

Este es modelo resultado de un finetuning de NazaGara/NER-fine-tuned-BETO sobre el conll2002 dataset. Los siguientes son los resultados sobre el conjunto de evaluación:

  • Loss: 0.002421
  • Precision: 0.861199
  • Recall: 0.871094
  • F1: 0.8851
  • Accuracy: 0,972756

Model description

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
  • weight_decay: 0.001
  • num_epochs: 8

Training results

Epoch Training Loss Validation Loss Precision Recall F1 Accuracy
1 0.004500 0.271499 0.854365 0.868107 0.861181 0.971268
2 0.004000 0.283811 0.839605 0.840763 0.840184 0.966170
3 0.003900 0.261076 0.849651 0.867417 0.858442 0.970664
4 0.002600 0.277270 0.858379 0.866268 0.862306 0.971702
5 0.002000 0.270548 0.859149 0.871783 0.865420 0.971563
6 0.001800 0.279797 0.857305 0.868336 0.862785 0.971609
7 0.001800 0.281091 0.857467 0.868107 0.862754 0.971966
8 0.001100 0.284128 0.861199 0.871094 0.866118 0.972756
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109M params
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F32
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Finetuned from

Dataset used to train PLN-T4-J-D-W/beto-finetuned-ner-1

Evaluation results