Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4603	1.0	144	0.4533	0.0933	0.5307	0.1916
0.4368	2.0	288	0.4219	0.1953	0.5812	0.2003
0.3826	3.0	432	0.3880	0.3288	0.6189	0.2787
0.3535	4.0	576	0.3562	0.5208	0.6918	0.3833
0.3018	5.0	720	0.3511	0.5697	0.7308	0.4007
0.2543	6.0	864	0.3593	0.6030	0.7492	0.4338
0.2549	7.0	1008	0.3463	0.6063	0.7436	0.4460
0.2183	8.0	1152	0.3425	0.6112	0.7484	0.4477
0.195	9.0	1296	0.3502	0.6004	0.7432	0.4355
0.1842	10.0	1440	0.3358	0.6223	0.7506	0.4686
0.151	11.0	1584	0.3451	0.6245	0.7578	0.4669
0.1385	12.0	1728	0.3383	0.6313	0.7584	0.4669
0.1286	13.0	1872	0.3492	0.6445	0.7692	0.4739
0.115	14.0	2016	0.3502	0.6553	0.7753	0.4913
0.1031	15.0	2160	0.3516	0.6529	0.7771	0.4826
0.1068	16.0	2304	0.3529	0.6448	0.7685	0.4808
0.0818	17.0	2448	0.3522	0.6542	0.7741	0.4895
0.0906	18.0	2592	0.3543	0.6620	0.7803	0.4983
0.0878	19.0	2736	0.3541	0.6595	0.7780	0.4948
0.0872	20.0	2880	0.3545	0.6584	0.7777	0.4948

sercetexam9/xlm-roberta-base-hau-finetuned-augmentation-LUNAR

xlm-roberta-base-hau-finetuned-augmentation-LUNAR