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tajberto-ner

This model is a fine-tuned version of muhtasham/TajBERTo on the wikiann dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6129
  • Precision: 0.576
  • Recall: 0.6923
  • F1: 0.6288
  • Accuracy: 0.8934

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 200

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 2.0 50 0.6171 0.1667 0.2885 0.2113 0.7646
No log 4.0 100 0.4733 0.2824 0.4615 0.3504 0.8344
No log 6.0 150 0.3857 0.3372 0.5577 0.4203 0.8589
No log 8.0 200 0.4523 0.4519 0.5865 0.5105 0.8765
No log 10.0 250 0.3870 0.44 0.6346 0.5197 0.8834
No log 12.0 300 0.4512 0.5267 0.6635 0.5872 0.8865
No log 14.0 350 0.4934 0.4789 0.6538 0.5528 0.8819
No log 16.0 400 0.4924 0.4783 0.6346 0.5455 0.8842
No log 18.0 450 0.5355 0.4595 0.6538 0.5397 0.8788
0.1682 20.0 500 0.5440 0.5547 0.6827 0.6121 0.8942
0.1682 22.0 550 0.5299 0.5794 0.7019 0.6348 0.9003
0.1682 24.0 600 0.5735 0.5691 0.6731 0.6167 0.8926
0.1682 26.0 650 0.6027 0.5833 0.6731 0.6250 0.8796
0.1682 28.0 700 0.6119 0.568 0.6827 0.6201 0.8934
0.1682 30.0 750 0.6098 0.5635 0.6827 0.6174 0.8911
0.1682 32.0 800 0.6237 0.5469 0.6731 0.6034 0.8834
0.1682 34.0 850 0.6215 0.5530 0.7019 0.6186 0.8842
0.1682 36.0 900 0.6179 0.5802 0.7308 0.6468 0.8888
0.1682 38.0 950 0.6201 0.5373 0.6923 0.6050 0.8873
0.0007 40.0 1000 0.6114 0.5952 0.7212 0.6522 0.8911
0.0007 42.0 1050 0.6073 0.5625 0.6923 0.6207 0.8896
0.0007 44.0 1100 0.6327 0.5620 0.6538 0.6044 0.8896
0.0007 46.0 1150 0.6129 0.576 0.6923 0.6288 0.8934

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train muhtasham/tajberto-ner

Evaluation results