--- 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](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.1174 - Validation Loss: 0.1784 - Train Accuracy: 0.9483 - Epoch: 23 ## 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 | | 0.1165 | 0.1784 | 0.9483 | 16 | | 0.1179 | 0.1784 | 0.9483 | 17 | | 0.1169 | 0.1784 | 0.9483 | 18 | | 0.1170 | 0.1784 | 0.9483 | 19 | | 0.1175 | 0.1784 | 0.9483 | 20 | | 0.1177 | 0.1784 | 0.9483 | 21 | | 0.1161 | 0.1784 | 0.9483 | 22 | | 0.1174 | 0.1784 | 0.9483 | 23 | ### Framework versions - Transformers 4.33.0 - TensorFlow 2.12.0 - Datasets 2.14.6 - Tokenizers 0.13.3