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
0.2277	1.0	1317	0.1909	0.7771	0.8519	0.6659
0.1552	2.0	2634	0.1908	0.7910	0.8718	0.6735
0.0983	3.0	3951	0.2215	0.7898	0.8681	0.7183
0.0579	4.0	5268	0.2368	0.8123	0.8828	0.7396
0.0389	5.0	6585	0.2813	0.8039	0.8815	0.7327
0.0264	6.0	7902	0.3052	0.7992	0.8788	0.7396
0.0191	7.0	9219	0.3389	0.7976	0.8791	0.7365
0.0122	8.0	10536	0.3407	0.8041	0.8797	0.7373
0.0076	9.0	11853	0.3596	0.8014	0.8821	0.7373
0.007	10.0	13170	0.3688	0.8086	0.8861	0.7456
0.0049	11.0	14487	0.3850	0.8006	0.8743	0.7487
0.0039	12.0	15804	0.3863	0.8085	0.8850	0.7472
0.003	13.0	17121	0.3884	0.8080	0.8766	0.7555
0.0016	14.0	18438	0.3909	0.8102	0.8872	0.7509
0.0019	15.0	19755	0.3929	0.8083	0.8819	0.7509

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

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