Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1562	0.25	7000	0.1457	0.9547	0.9376	0.9460	0.9407
0.1375	0.5	14000	0.1472	0.9569	0.9414	0.9491	0.9442
0.1371	0.75	21000	0.1331	0.9570	0.9480	0.9524	0.9482
0.1325	0.99	28000	0.1216	0.9603	0.9487	0.9545	0.9501
0.1176	1.24	35000	0.1307	0.9617	0.9468	0.9542	0.9496
0.1191	1.49	42000	0.1230	0.9596	0.9521	0.9558	0.9516
0.116	1.74	49000	0.1341	0.9634	0.9510	0.9572	0.9528
0.1136	1.99	56000	0.1179	0.9582	0.9560	0.9571	0.9527
0.0947	2.24	63000	0.1426	0.9560	0.9544	0.9552	0.9512
0.1009	2.49	70000	0.1155	0.9644	0.9549	0.9596	0.9556
0.0972	2.73	77000	0.1282	0.9654	0.9543	0.9598	0.9556
0.0959	2.98	84000	0.1216	0.9642	0.9566	0.9603	0.9564
0.0847	3.23	91000	0.1222	0.9645	0.9580	0.9612	0.9573
0.0817	3.48	98000	0.1275	0.9648	0.9575	0.9611	0.9571
0.089	3.73	105000	0.1260	0.9661	0.9577	0.9619	0.9580
0.0826	3.98	112000	0.1188	0.9641	0.9593	0.9617	0.9577
0.072	4.23	119000	0.1361	0.9645	0.9598	0.9621	0.9581
0.0648	4.47	126000	0.1377	0.9640	0.9601	0.9620	0.9581
0.0665	4.72	133000	0.1352	0.9655	0.9596	0.9625	0.9586
0.0692	4.97	140000	0.1392	0.9668	0.9593	0.9631	0.9593
0.0545	5.22	147000	0.1470	0.9663	0.9602	0.9633	0.9595
0.0549	5.47	154000	0.1442	0.9652	0.9611	0.9631	0.9593
0.0563	5.72	161000	0.1454	0.9657	0.9609	0.9633	0.9594
0.0647	5.97	168000	0.1424	0.9657	0.9608	0.9633	0.9594

Sevixdd/roberta-base-finetuned-ner

roberta-base-finetuned-ner