aadhistii/indobert-ner-model

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

• Train Loss: 0.1471
• Validation Loss: 0.1801
• Train Precision: 0.8077
• Train Recall: 0.8437
• Train F1: 0.8253
• Train Accuracy: 0.9471
• Epoch: 2

Model description

Dataset Entities:

• 'CRD': Cardinal
• 'DAT': Date
• 'EVT': Event
• 'FAC': Facility
• 'GPE': Geopolitical Entity
• 'LAW': Law Entity (such as Undang-Undang)
• 'LOC': Location
• 'MON': Money
• 'NOR': Political Organization
• 'ORD': Ordinal
• 'ORG': Organization
• 'PER': Person
• 'PRC': Percent
• 'PRD': Product
• 'QTY': Quantity
• 'REG': Religion
• 'TIM': Time
• 'WOA': Work of Art
• 'LAN': Language

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2349, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.5182	0.2042	0.7770	0.8146	0.7954	0.9395	0
0.1907	0.1810	0.8020	0.8344	0.8179	0.9469	1
0.1471	0.1801	0.8077	0.8437	0.8253	0.9471	2

Framework versions

• Transformers 4.41.1
• TensorFlow 2.15.0
• Datasets 2.19.1
• Tokenizers 0.19.1