aadhistii/tsel-finetune-indobert-base-p1-formal

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0095
• Validation Loss: 1.0054
• Train Precision: 0.7633
• Train Recall: 0.7633
• Train F1: 0.7633
• Epoch: 9

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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 940, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Epoch
0.8009	0.7030	0.7128	0.7128	0.7128	0
0.4891	0.5644	0.7739	0.7739	0.7739	1
0.2392	0.7856	0.7340	0.7340	0.7340	2
0.1000	0.7443	0.7633	0.7633	0.7633	3
0.0576	0.9280	0.7314	0.7314	0.7314	4
0.0307	0.9033	0.7739	0.7739	0.7739	5
0.0185	0.9377	0.7660	0.7660	0.7660	6
0.0088	1.0061	0.7580	0.7580	0.7580	7
0.0079	1.0007	0.7660	0.7660	0.7660	8
0.0095	1.0054	0.7633	0.7633	0.7633	9

Framework versions

• Transformers 4.42.3
• TensorFlow 2.15.0
• Datasets 2.20.0
• Tokenizers 0.19.1