Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.37	0.51	1000	0.3241	0.7491	0.7745	0.7616	0.8951
0.3118	1.03	2000	0.3120	0.7631	0.7862	0.7745	0.8998
0.2877	1.54	3000	0.2994	0.7679	0.7918	0.7797	0.9027
0.284	2.06	4000	0.2977	0.7643	0.7960	0.7798	0.9026
0.2631	2.57	5000	0.2900	0.7716	0.8001	0.7856	0.9040
0.259	3.08	6000	0.2958	0.7739	0.8058	0.7895	0.9050
0.2426	3.6	7000	0.2850	0.7795	0.8042	0.7917	0.9072
0.2378	4.11	8000	0.2910	0.7740	0.8069	0.7901	0.9059
0.2231	4.63	9000	0.2878	0.7788	0.8106	0.7944	0.9077
0.2188	5.14	10000	0.2941	0.7752	0.8101	0.7923	0.9087
0.2066	5.66	11000	0.2928	0.7721	0.8147	0.7928	0.9079
0.2008	6.17	12000	0.3048	0.7798	0.8141	0.7966	0.9088
0.1902	6.68	13000	0.2987	0.7834	0.8108	0.7969	0.9099
0.1843	7.2	14000	0.3055	0.7784	0.8137	0.7957	0.9101
0.1775	7.71	15000	0.2991	0.7762	0.8155	0.7953	0.9096
0.1694	8.23	16000	0.3117	0.7876	0.8137	0.8004	0.9120
0.1631	8.74	17000	0.3085	0.7761	0.8210	0.7979	0.9121
0.1585	9.25	18000	0.3144	0.7851	0.8063	0.7955	0.9108
0.1528	9.77	19000	0.3086	0.7834	0.8169	0.7998	0.9124
0.1458	10.28	20000	0.3167	0.7773	0.8208	0.7985	0.9114
0.143	10.8	21000	0.3202	0.7822	0.8134	0.7975	0.9123
0.1368	11.31	22000	0.3299	0.7798	0.8176	0.7983	0.9112
0.1337	11.83	23000	0.3369	0.7857	0.8151	0.8002	0.9131
0.1289	12.34	24000	0.3366	0.7855	0.8148	0.7999	0.9128
0.1257	12.85	25000	0.3316	0.7837	0.8172	0.8001	0.9129
0.122	13.37	26000	0.3415	0.7880	0.8120	0.7998	0.9136
0.1191	13.88	27000	0.3414	0.7867	0.8182	0.8021	0.9139
0.1157	14.4	28000	0.3481	0.7863	0.8174	0.8016	0.9136
0.1153	14.91	29000	0.3466	0.7858	0.8156	0.8004	0.9134

livinNector/taNER-500-naamapdam-fine-tuned

taNER-500-naamapdam-fine-tuned