aditnnda/gacoan_reviewer

This model is a fine-tuned version of indobenchmark/indobert-large-p1 on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0001
• Validation Loss: 0.4435
• Train Accuracy: 0.9386
• 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': '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': 3550, '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 Accuracy	Epoch
0.2553	0.1732	0.9331	0
0.0938	0.1571	0.9400	1
0.0310	0.2345	0.9386	2
0.0138	0.3288	0.9358	3
0.0140	0.3345	0.9177	4
0.0033	0.3502	0.9386	5
0.0118	0.3387	0.9344	6
0.0269	0.4487	0.9024	7
0.0188	0.3228	0.9331	8
0.0017	0.3581	0.9372	9
0.0020	0.4125	0.9233	10
0.0021	0.4143	0.9247	11
0.0011	0.4353	0.9303	12
0.0002	0.4285	0.9344	13
0.0005	0.4350	0.9344	14
0.0002	0.4340	0.9344	15
0.0002	0.4026	0.9400	16
0.0001	0.4123	0.9414	17
0.0001	0.4228	0.9414	18
0.0001	0.4294	0.9386	19
0.0001	0.4385	0.9386	20
0.0001	0.4411	0.9386	21
0.0001	0.4423	0.9386	22
0.0001	0.4431	0.9386	23
0.0001	0.4435	0.9386	24

Framework versions

• Transformers 4.35.2
• TensorFlow 2.15.0
• Datasets 2.16.0
• Tokenizers 0.15.0