Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.0	50	0.6171	0.1667	0.2885	0.2113	0.7646
No log	4.0	100	0.4733	0.2824	0.4615	0.3504	0.8344
No log	6.0	150	0.3857	0.3372	0.5577	0.4203	0.8589
No log	8.0	200	0.4523	0.4519	0.5865	0.5105	0.8765
No log	10.0	250	0.3870	0.44	0.6346	0.5197	0.8834
No log	12.0	300	0.4512	0.5267	0.6635	0.5872	0.8865
No log	14.0	350	0.4934	0.4789	0.6538	0.5528	0.8819
No log	16.0	400	0.4924	0.4783	0.6346	0.5455	0.8842
No log	18.0	450	0.5355	0.4595	0.6538	0.5397	0.8788
0.1682	20.0	500	0.5440	0.5547	0.6827	0.6121	0.8942
0.1682	22.0	550	0.5299	0.5794	0.7019	0.6348	0.9003
0.1682	24.0	600	0.5735	0.5691	0.6731	0.6167	0.8926
0.1682	26.0	650	0.6027	0.5833	0.6731	0.6250	0.8796
0.1682	28.0	700	0.6119	0.568	0.6827	0.6201	0.8934
0.1682	30.0	750	0.6098	0.5635	0.6827	0.6174	0.8911
0.1682	32.0	800	0.6237	0.5469	0.6731	0.6034	0.8834
0.1682	34.0	850	0.6215	0.5530	0.7019	0.6186	0.8842
0.1682	36.0	900	0.6179	0.5802	0.7308	0.6468	0.8888
0.1682	38.0	950	0.6201	0.5373	0.6923	0.6050	0.8873
0.0007	40.0	1000	0.6114	0.5952	0.7212	0.6522	0.8911
0.0007	42.0	1050	0.6073	0.5625	0.6923	0.6207	0.8896
0.0007	44.0	1100	0.6327	0.5620	0.6538	0.6044	0.8896
0.0007	46.0	1150	0.6129	0.576	0.6923	0.6288	0.8934

muhtasham/tajberto-ner

tajberto-ner