Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6594	1.0	23	0.6523	0.95
0.6979	2.0	46	0.6400	0.95
0.6407	3.0	69	0.6331	0.95
0.7082	4.0	92	0.6360	0.95
0.6493	5.0	115	0.6258	0.95
0.6827	6.0	138	0.6239	0.95
0.6511	7.0	161	0.6399	0.95
0.6459	8.0	184	0.6279	0.95
0.6623	9.0	207	0.6247	0.95
0.6583	10.0	230	0.6307	0.95
0.6613	11.0	253	0.6269	0.95
0.6223	12.0	276	0.6270	0.95
0.6375	13.0	299	0.6284	0.95
0.7009	14.0	322	0.6309	0.95
0.6705	15.0	345	0.6299	0.95
0.6503	16.0	368	0.6396	0.95
0.7073	17.0	391	0.6305	0.95
0.614	18.0	414	0.6308	0.95
0.6512	19.0	437	0.6305	0.95
0.7055	20.0	460	0.6308	0.95
0.5702	21.0	483	0.6304	0.95
0.6654	22.0	506	0.6305	0.95
0.6129	23.0	529	0.6308	0.95
0.6477	24.0	552	0.6310	0.95
0.6178	25.0	575	0.6312	0.95
0.6562	26.0	598	0.6312	0.95
0.5972	27.0	621	0.6317	0.95
0.6324	28.0	644	0.6312	0.95
0.6064	29.0	667	0.6312	0.95
0.5833	30.0	690	0.6312	0.95
0.6916	31.0	713	0.6312	0.95
0.5591	32.0	736	0.6312	0.95
0.6477	33.0	759	0.6312	0.95
0.6483	34.0	782	0.6311	0.95
0.5563	35.0	805	0.6310	0.95
0.6061	36.0	828	0.6310	0.95
0.6043	37.0	851	0.6310	0.95
0.6274	38.0	874	0.6310	0.95
0.6115	39.0	897	0.6310	0.95
0.7107	40.0	920	0.6310	0.95
0.6703	41.0	943	0.6310	0.95
0.6052	42.0	966	0.6310	0.95
0.6228	43.0	989	0.6310	0.95
0.6629	44.0	1012	0.6310	0.95
0.5804	45.0	1035	0.6310	0.95
0.6194	46.0	1058	0.6310	0.95
0.6529	47.0	1081	0.6310	0.95
0.5779	48.0	1104	0.6310	0.95
0.6652	49.0	1127	0.6310	0.95
0.6163	50.0	1150	0.6310	0.95
0.6873	51.0	1173	0.6310	0.95
0.5608	52.0	1196	0.6310	0.95
0.6646	53.0	1219	0.6310	0.95
0.6222	54.0	1242	0.6310	0.95
0.6629	55.0	1265	0.6310	0.95
0.592	56.0	1288	0.6310	0.95
0.6047	57.0	1311	0.6310	0.95
0.5668	58.0	1334	0.6310	0.95
0.6358	59.0	1357	0.6310	0.95
0.648	60.0	1380	0.6310	0.95

bimoadiparwa/roberta-mc-6

roberta-mc-6