--- license: mit base_model: cahya/bert-base-indonesian-522M tags: - generated_from_keras_callback model-index: - name: racheilla/bert-base-indonesian-522M-finetuned-pemilu results: [] --- # racheilla/bert-base-indonesian-522M-finetuned-pemilu This model is a fine-tuned version of [cahya/bert-base-indonesian-522M](https://huggingface.co/cahya/bert-base-indonesian-522M) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 3.2729 - Validation Loss: 3.4132 - Epoch: 18 ## 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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -950, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: mixed_float16 ### Training results | Train Loss | Validation Loss | Epoch | |:----------:|:---------------:|:-----:| | 3.2847 | 3.4266 | 0 | | 3.3000 | 3.4116 | 1 | | 3.2702 | 3.3975 | 2 | | 3.2675 | 3.4689 | 3 | | 3.2982 | 3.3540 | 4 | | 3.3109 | 3.4127 | 5 | | 3.2698 | 3.4126 | 6 | | 3.2852 | 3.4165 | 7 | | 3.2977 | 3.3816 | 8 | | 3.2749 | 3.3923 | 9 | | 3.2777 | 3.3841 | 10 | | 3.2555 | 3.4534 | 11 | | 3.2940 | 3.4194 | 12 | | 3.2860 | 3.3810 | 13 | | 3.2585 | 3.3328 | 14 | | 3.2979 | 3.4310 | 15 | | 3.2844 | 3.4374 | 16 | | 3.2961 | 3.3630 | 17 | | 3.2729 | 3.4132 | 18 | ### Framework versions - Transformers 4.35.2 - TensorFlow 2.15.0 - Datasets 2.15.0 - Tokenizers 0.15.0