learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4552	1.0	76	0.2917	0.0	0.5	0.4630
0.3135	2.0	152	0.2906	0.0	0.5	0.4630
0.3096	3.0	228	0.2922	0.0	0.5	0.4630
0.2912	4.0	304	0.2767	0.0	0.5	0.4630
0.273	5.0	380	0.2541	0.0810	0.5280	0.5175
0.2233	6.0	456	0.2442	0.2428	0.5900	0.5370
0.2068	7.0	532	0.2295	0.3091	0.6230	0.5837
0.1729	8.0	608	0.2393	0.3528	0.6278	0.5642
0.1378	9.0	684	0.2414	0.3785	0.6455	0.5486
0.1181	10.0	760	0.2366	0.4141	0.6686	0.5720
0.1032	11.0	836	0.2529	0.3994	0.6621	0.5681
0.0869	12.0	912	0.2515	0.3791	0.6465	0.5681
0.0766	13.0	988	0.2594	0.3863	0.6584	0.5720
0.0697	14.0	1064	0.2551	0.3926	0.6547	0.5798

Kuongan/xlm-roberta-base-ptmz-finetuned

xlm-roberta-base-ptmz-finetuned