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