aadhistii/smsa-tsel-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: 0.0770
• Validation Loss: 0.7057
• Train Precision: 0.7275
• Train Recall: 0.7282
• Train F1: 0.7278
• Train Accuracy: 0.7282
• Epoch: 8

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': 245, '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	Train Accuracy	Epoch
0.0805	0.7057	0.7275	0.7282	0.7278	0.7282	0
0.0776	0.7057	0.7275	0.7282	0.7278	0.7282	1
0.0828	0.7057	0.7275	0.7282	0.7278	0.7282	2
0.0786	0.7057	0.7275	0.7282	0.7278	0.7282	3
0.0824	0.7057	0.7275	0.7282	0.7278	0.7282	4
0.0787	0.7057	0.7275	0.7282	0.7278	0.7282	5
0.0817	0.7057	0.7275	0.7282	0.7278	0.7282	6
0.0811	0.7057	0.7275	0.7282	0.7278	0.7282	7
0.0770	0.7057	0.7275	0.7282	0.7278	0.7282	8

Framework versions

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