aadhistii/tsel-finetune-indobert-base-p1-2k-formal-v2

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

• Train Loss: 0.0086
• Validation Loss: 1.0372
• Train Precision: 0.7580
• Train Recall: 0.7580
• Train F1: 0.7580
• 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
0.7881	0.5850	0.7660	0.7660	0.7660	0
0.4468	0.6147	0.7447	0.7447	0.7447	1
0.2292	0.7075	0.7633	0.7633	0.7633	2
0.1116	0.8423	0.7473	0.7473	0.7473	3
0.0603	0.8702	0.7793	0.7793	0.7793	4
0.0273	0.9224	0.7606	0.7606	0.7606	5
0.0152	1.0343	0.7394	0.7394	0.7394	6
0.0149	1.0186	0.7473	0.7473	0.7473	7
0.0105	1.0450	0.7633	0.7633	0.7633	8
0.0086	1.0372	0.7580	0.7580	0.7580	9

Framework versions

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