learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 15

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3106	1.0	659	0.2504	0.6779	0.7832	0.5978
0.2235	2.0	1318	0.2113	0.7466	0.8392	0.6441
0.1722	3.0	1977	0.2283	0.7511	0.8493	0.6581
0.097	4.0	2636	0.2421	0.7626	0.8490	0.6874
0.0643	5.0	3295	0.2727	0.7584	0.8417	0.6938
0.0572	6.0	3954	0.2817	0.7662	0.8662	0.6737
0.0304	7.0	4613	0.3075	0.7606	0.8475	0.6879
0.021	8.0	5272	0.3195	0.7697	0.8626	0.6932
0.0157	9.0	5931	0.3347	0.7663	0.8477	0.7052
0.0095	10.0	6590	0.3353	0.7759	0.8598	0.7118
0.0086	11.0	7249	0.3467	0.7768	0.8590	0.7136
0.0063	12.0	7908	0.3503	0.7795	0.8644	0.7128
0.0046	13.0	8567	0.3577	0.7797	0.8613	0.7153
0.0037	14.0	9226	0.3622	0.7801	0.8674	0.7115
0.0046	15.0	9885	0.3641	0.7802	0.8639	0.7156

PaceKW/bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-new

bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-new