learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
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: 30

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.5738	1.0	139	0.5473	0.1947	0.5461	0.1751
0.4173	2.0	278	0.4194	0.5997	0.7189	0.3736
0.3402	3.0	417	0.3829	0.6887	0.7809	0.4314
0.1937	4.0	556	0.3563	0.7213	0.7914	0.4747
0.1756	5.0	695	0.3888	0.7271	0.7883	0.4856
0.1307	6.0	834	0.4043	0.7351	0.7959	0.4964
0.0963	7.0	973	0.4520	0.7434	0.8055	0.4982
0.0645	8.0	1112	0.4992	0.7259	0.7935	0.4892
0.0396	9.0	1251	0.5118	0.7570	0.8209	0.4964
0.0298	10.0	1390	0.5700	0.7516	0.8107	0.4892
0.0403	11.0	1529	0.6019	0.7440	0.8071	0.4892
0.014	12.0	1668	0.6476	0.7355	0.8008	0.4964
0.0095	13.0	1807	0.6871	0.7364	0.8007	0.4477
0.0127	14.0	1946	0.6843	0.7489	0.8097	0.4928
0.0098	15.0	2085	0.7105	0.7504	0.8082	0.4928
0.0039	16.0	2224	0.7187	0.7512	0.8119	0.4928
0.0044	17.0	2363	0.7415	0.7580	0.8223	0.4964
0.0035	18.0	2502	0.7614	0.7419	0.8051	0.4874
0.0033	19.0	2641	0.7527	0.7460	0.8137	0.4874
0.0027	20.0	2780	0.7640	0.7491	0.8113	0.5036
0.0014	21.0	2919	0.7682	0.7490	0.8113	0.4964
0.0014	22.0	3058	0.7804	0.7514	0.8124	0.5018
0.002	23.0	3197	0.7642	0.7567	0.8197	0.5072
0.0018	24.0	3336	0.7774	0.7537	0.8159	0.5018
0.0016	25.0	3475	0.7758	0.7545	0.8165	0.5054
0.0016	26.0	3614	0.7811	0.7580	0.8195	0.5108
0.0017	27.0	3753	0.7819	0.7558	0.8167	0.5108
0.0015	28.0	3892	0.7833	0.7574	0.8180	0.5126
0.0014	29.0	4031	0.7844	0.7565	0.8169	0.5126
0.001	30.0	4170	0.7846	0.7562	0.8165	0.5108

sercetexam9/UIT-NO-PREdeberta-v3-base-finetuned

UIT-NO-PREdeberta-v3-base-finetuned