Training Loss	Epoch	Step	Validation Loss	Exact Match	F1	Precision	Recall
5.7583	0.49	73	3.4717	48.6911	48.7120	48.7565	48.7036
3.8675	0.99	146	2.0063	49.8691	49.8691	49.8691	49.8691
2.1019	1.49	219	1.7934	43.5864	48.7113	47.9108	55.2027
1.9506	1.98	292	1.5978	52.4869	55.5648	55.8810	58.4501
1.582	2.48	365	1.4043	56.5445	61.2297	61.9432	64.9738
1.5478	2.98	438	1.2214	61.6492	66.1051	66.6829	69.1297
1.2069	3.47	511	1.1363	62.1728	67.2788	68.1474	70.3092
1.2033	3.97	584	1.0647	64.1361	69.5232	70.4180	72.9446
1.0169	4.47	657	1.0578	66.4921	72.1170	73.7120	74.5930
0.9691	4.96	730	1.0995	63.4817	69.3250	70.7996	71.9125
0.8492	5.46	803	1.0184	67.2775	72.1515	73.4105	75.0396
0.8327	5.96	876	1.1143	65.5759	71.0294	72.7764	73.1126
0.8248	6.45	949	1.0151	68.3246	73.9214	75.4324	76.0018
0.7498	6.95	1022	1.0034	68.8482	74.2840	76.1810	75.9452
0.6847	7.45	1095	1.0601	68.0628	73.5761	75.3716	75.4001
0.7117	7.94	1168	1.0448	68.0628	74.0368	75.6591	75.9829
0.6365	8.44	1241	1.0444	67.9319	73.5776	75.1324	76.1210

afaji/fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05

fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05