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
0.4684	1.0	139	0.4204	0.5966	0.7123	0.3736
0.4025	2.0	278	0.3654	0.6855	0.7572	0.4170
0.294	3.0	417	0.3667	0.6847	0.7556	0.4422
0.1918	4.0	556	0.3991	0.6904	0.7583	0.4368
0.1612	5.0	695	0.3956	0.7051	0.7696	0.4549
0.1231	6.0	834	0.4398	0.6869	0.7518	0.4278
0.0931	7.0	973	0.4745	0.7143	0.7814	0.4477
0.0628	8.0	1112	0.4545	0.7327	0.7990	0.4675
0.0494	9.0	1251	0.4986	0.6965	0.7653	0.4567
0.0549	10.0	1390	0.5357	0.7155	0.7819	0.4422
0.0307	11.0	1529	0.5767	0.7245	0.7862	0.4585
0.0216	12.0	1668	0.5965	0.7129	0.7772	0.4621
0.0164	13.0	1807	0.6145	0.7206	0.7814	0.4477
0.0137	14.0	1946	0.6378	0.7236	0.7904	0.4495
0.0102	15.0	2085	0.6641	0.7133	0.7814	0.4458
0.0084	16.0	2224	0.6668	0.7157	0.7832	0.4440
0.0063	17.0	2363	0.6920	0.7171	0.7842	0.4531
0.0098	18.0	2502	0.6977	0.6989	0.7698	0.4350
0.0039	19.0	2641	0.7074	0.7087	0.7782	0.4495
0.0041	20.0	2780	0.7103	0.7240	0.7889	0.4621
0.0031	21.0	2919	0.7077	0.7299	0.7941	0.4657
0.003	22.0	3058	0.7196	0.7196	0.7865	0.4531
0.0032	23.0	3197	0.7227	0.7220	0.7885	0.4639
0.0027	24.0	3336	0.7324	0.7194	0.7853	0.4567
0.0027	25.0	3475	0.7337	0.7212	0.7864	0.4549
0.0029	26.0	3614	0.7363	0.7229	0.7875	0.4585
0.0026	27.0	3753	0.7365	0.7224	0.7880	0.4567
0.0028	28.0	3892	0.7374	0.7212	0.7865	0.4585
0.0027	29.0	4031	0.7375	0.7216	0.7867	0.4567
0.0024	30.0	4170	0.7378	0.7216	0.7867	0.4567

sercetexam9/UIT-roberta-base-finetuned

UIT-roberta-base-finetuned