electra-srb-ner

This model was trained from scratch on the wikiann dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3406
  • Precision: 0.8934
  • Recall: 0.9087
  • F1: 0.9010
  • Accuracy: 0.9568

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.3686 1.0 625 0.2108 0.8326 0.8494 0.8409 0.9335
0.1886 2.0 1250 0.1784 0.8737 0.8713 0.8725 0.9456
0.1323 3.0 1875 0.1805 0.8654 0.8870 0.8760 0.9468
0.0675 4.0 2500 0.2018 0.8736 0.8880 0.8807 0.9502
0.0425 5.0 3125 0.2162 0.8818 0.8945 0.8881 0.9512
0.0343 6.0 3750 0.2492 0.8790 0.8928 0.8859 0.9513
0.0253 7.0 4375 0.2562 0.8821 0.9006 0.8912 0.9525
0.0142 8.0 5000 0.2788 0.8807 0.9013 0.8909 0.9524
0.0114 9.0 5625 0.2793 0.8861 0.9002 0.8931 0.9534
0.0095 10.0 6250 0.2967 0.8887 0.9034 0.8960 0.9550
0.008 11.0 6875 0.2993 0.8899 0.9067 0.8982 0.9556
0.0048 12.0 7500 0.3215 0.8887 0.9038 0.8962 0.9545
0.0034 13.0 8125 0.3242 0.8897 0.9068 0.8982 0.9554
0.003 14.0 8750 0.3311 0.8884 0.9085 0.8983 0.9559
0.0025 15.0 9375 0.3383 0.8943 0.9062 0.9002 0.9562
0.0011 16.0 10000 0.3346 0.8941 0.9112 0.9026 0.9574
0.0015 17.0 10625 0.3362 0.8944 0.9081 0.9012 0.9567
0.001 18.0 11250 0.3464 0.8877 0.9100 0.8987 0.9559
0.0012 19.0 11875 0.3415 0.8944 0.9089 0.9016 0.9568
0.0005 20.0 12500 0.3406 0.8934 0.9087 0.9010 0.9568

Framework versions

  • Transformers 4.9.2
  • Pytorch 1.9.0
  • Datasets 1.11.0
  • Tokenizers 0.10.1
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