Training Loss	Epoch	Step	Validation Loss	Exact Match	F1	Precision	Recall
6.2602	0.5	38	4.9592	0.5236	11.0968	11.1980	26.6188
5.556	0.99	76	3.0406	12.7400	25.1945	25.6795	39.6592
3.3395	1.5	114	2.4880	21.1169	34.7076	32.9184	52.2869
2.4731	1.99	152	2.2257	27.3997	40.0066	39.3514	53.5252
2.4731	2.5	190	2.0431	32.6353	44.5789	44.7211	55.0020
2.162	2.99	228	1.8362	38.9180	50.4876	50.7087	59.7434
1.8755	3.5	266	1.6441	43.9791	56.8266	57.4538	65.5751
1.5888	3.99	304	1.4664	52.0070	63.9616	65.2046	70.0798
1.5888	4.5	342	1.3509	54.4503	68.6979	70.2140	76.0813
1.333	4.99	380	1.2571	54.7993	68.9857	70.8728	75.8745
1.2051	5.5	418	1.2440	56.5445	70.2921	72.4571	75.9313
1.0522	5.99	456	1.1808	57.5916	72.1230	73.6246	78.8092
1.0522	6.5	494	1.1575	58.9878	73.1594	74.9064	79.2545
0.9584	6.99	532	1.1553	58.9878	73.5139	75.2615	79.3901
0.9006	7.5	570	1.1112	60.0349	74.5273	75.8170	81.1555
0.8102	7.99	608	1.1164	59.8604	74.5013	76.2748	80.2875
0.8102	8.5	646	1.1371	60.0349	74.2469	75.9082	79.9186
0.773	8.99	684	1.1410	60.7330	74.9095	76.7045	80.9178
0.7482	9.5	722	1.1307	60.3839	74.7594	76.8954	80.6364
0.6878	9.99	760	1.1219	61.0820	74.9064	76.4266	81.4087
0.6878	10.5	798	1.1362	62.1291	76.5097	77.5924	82.8049
0.6401	10.99	836	1.1266	61.0820	75.8874	77.0263	81.7467
0.634	11.5	874	1.1570	61.7801	75.9638	77.5661	80.8536
0.5856	11.99	912	1.1675	61.4311	76.0013	77.2642	81.7278

afaji/fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05

fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05