Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4179	1.0	238	0.4173	0.0	0.5	0.1735
0.3969	2.0	476	0.3760	0.2222	0.5646	0.2808
0.3427	3.0	714	0.3236	0.4125	0.6565	0.3922
0.2814	4.0	952	0.2987	0.5339	0.7071	0.4448
0.2655	5.0	1190	0.2953	0.5704	0.7415	0.4658
0.2185	6.0	1428	0.3105	0.5699	0.7519	0.4448
0.2206	7.0	1666	0.3094	0.5764	0.7509	0.4669
0.161	8.0	1904	0.3088	0.5871	0.7524	0.4879
0.1473	9.0	2142	0.3198	0.6278	0.7683	0.4921
0.1237	10.0	2380	0.3405	0.6264	0.7680	0.4774
0.1032	11.0	2618	0.3341	0.6362	0.7720	0.5079
0.0857	12.0	2856	0.3452	0.6521	0.7771	0.5058
0.0695	13.0	3094	0.3604	0.6552	0.7872	0.5058
0.0626	14.0	3332	0.3686	0.6472	0.7815	0.5089
0.0481	15.0	3570	0.3666	0.6477	0.7763	0.5121
0.0516	16.0	3808	0.3820	0.6576	0.7940	0.5110
0.0469	17.0	4046	0.3752	0.6493	0.7846	0.5121
0.0473	18.0	4284	0.3817	0.6448	0.7821	0.5100
0.0405	19.0	4522	0.3830	0.6529	0.7871	0.5110
0.0474	20.0	4760	0.3827	0.6519	0.7874	0.5100

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

xlm-roberta-base-amh-finetuned-augmentation-LUNAR