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: 0.1167
• Validation Loss: 0.1784
• Train Accuracy: 0.9483
• Epoch: 24

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
0.1167	0.1784	0.9483	24

Framework versions

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