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KIPBERT

This model is a fine-tuned version of indolem/indobert-base-uncased on the id_nergrit_corpus dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1731
  • Precision: 0.8058
  • Recall: 0.8325
  • F1: 0.8189
  • Accuracy: 0.9503

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: 2

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.4926 1.0 784 0.1810 0.7860 0.8172 0.8013 0.9450
0.1627 2.0 1568 0.1731 0.8058 0.8325 0.8189 0.9503

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train kiipliwooke/KIPBERT

Evaluation results