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indobert-base-uncased-finetuned-nergrit

Token Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
Inference Endpoints
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indobert-base-uncased-finetuned-nergrit / README.md
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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: apwic/indobert-base-uncased-finetuned-nergrit
    results: []

apwic/indobert-base-uncased-finetuned-nergrit

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

  • Train Loss: 0.1176
  • Validation Loss: 0.1784
  • Train Accuracy: 0.9483
  • Epoch: 15

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2352, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
0.4507 0.1933 0.9437 0
0.1708 0.1795 0.9471 1
0.1295 0.1784 0.9483 2
0.1169 0.1784 0.9483 3
0.1172 0.1784 0.9483 4
0.1180 0.1784 0.9483 5
0.1176 0.1784 0.9483 6
0.1172 0.1784 0.9483 7
0.1168 0.1784 0.9483 8
0.1174 0.1784 0.9483 9
0.1174 0.1784 0.9483 10
0.1178 0.1784 0.9483 11
0.1175 0.1784 0.9483 12
0.1175 0.1784 0.9483 13
0.1179 0.1784 0.9483 14
0.1176 0.1784 0.9483 15

Framework versions

  • Transformers 4.33.0
  • TensorFlow 2.12.0
  • Datasets 2.14.6
  • Tokenizers 0.13.3