Training Loss	Epoch	Step	Accuracy	Validation Loss
4.5743	0.46	200	0.3185	3.6252
4.0617	0.91	400	0.3300	3.5165
3.7835	1.37	600	0.3238	nan
3.7415	1.82	800	0.3733	nan
3.6084	2.28	1000	0.3711	3.4266
3.5224	2.73	1200	0.3966	nan
3.4781	3.19	1400	0.4110	3.0491
3.2402	3.64	1600	0.4381	3.3243
3.1612	4.1	1800	0.4764	nan
3.0672	4.56	2000	0.4293	2.6114
3.0975	5.01	2200	0.4415	nan
3.0579	5.47	2400	0.4760	2.6061
3.0349	5.92	2600	0.5012	2.6430
2.9009	6.38	2800	0.5101	2.6843
3.0346	6.83	3000	0.4803	2.7765
2.7554	7.29	3200	0.4866	nan
2.6926	7.74	3400	0.5105	2.8698
2.8284	8.2	3600	0.5038	2.5535
2.8385	8.66	3800	0.5465	2.5647
2.731	9.11	4000	0.5355	nan
2.6252	9.57	4200	0.5062	2.7420
2.5493	10.02	4400	0.5570	2.4540
2.649	10.48	4600	0.5495	2.4343
2.6669	10.93	4800	0.5365	2.2657
2.4549	11.39	5000	0.5508	2.4005
2.5627	11.85	5200	0.6057	nan
2.5328	12.3	5400	0.5943	2.0599
2.6162	12.76	5600	0.5167	nan
2.5906	13.21	5800	0.5518	2.1281
2.542	13.67	6000	0.5847	nan
2.4217	14.12	6200	0.5498	nan
2.4402	14.58	6400	0.5884	nan

soBeauty/V3_20230929-1-xlm-roberta-base-new

V3_20230929-1-xlm-roberta-base-new