Step:	Training Loss:	Validation Loss:	Precision:	Recall:	F1:	Accuracy:
100	No log	1.603663	0.395480	0.192837	0.259259	0.695220
200	No log	1.075776	0.638381	0.449036	0.527224	0.801603
300	No log	0.803760	0.648889	0.536272	0.587230	0.833103
400	No log	0.638516	0.736383	0.620753	0.673642	0.867090
500	1.200600	0.532104	0.785193	0.691460	0.735352	0.892235
600	1.200600	0.459440	0.746919	0.723600	0.735075	0.909091
700	1.200600	0.394753	0.766603	0.741965	0.754083	0.919038
800	1.200600	0.338639	0.814021	0.767677	0.790170	0.932302
900	1.200600	0.295805	0.815414	0.786961	0.800935	0.938104
1000	0.382900	0.277535	0.842207	0.798898	0.819981	0.938933
1100	0.382900	0.242293	0.846736	0.821855	0.834110	0.948328
1200	0.382900	0.224486	0.868297	0.847567	0.857807	0.955513
1300	0.382900	0.223093	0.875349	0.864096	0.869686	0.956342
1400	0.382900	0.189809	0.881151	0.871442	0.876270	0.962421
1500	0.184100	0.191570	0.885397	0.879706	0.882543	0.962973
1600	0.184100	0.178507	0.878591	0.870523	0.874539	0.962144
1700	0.184100	0.156512	0.897363	0.875115	0.886099	0.968223
1800	0.184100	0.155516	0.907735	0.894399	0.901018	0.968500
1900	0.184100	0.151979	0.914099	0.898990	0.906481	0.969881
2000	0.102600	0.149688	0.909851	0.898990	0.904388	0.969052
2100	0.102600	0.150848	0.910185	0.902663	0.906408	0.969329
2200	0.102600	0.145248	0.914099	0.898990	0.906481	0.969329
2300	0.102600	0.135254	0.907847	0.913682	0.910755	0.972644
2400	0.102600	0.139054	0.912118	0.905418	0.908756	0.970710
2500	0.071300	0.138957	0.913603	0.912764	0.913183	0.970710
2600	0.071300	0.138527	0.915441	0.914601	0.915021	0.972644
2700	0.071300	0.138344	0.916360	0.915519	0.915939	0.972921
2800	0.071300	0.133588	0.913321	0.919192	0.916247	0.973750
2900	0.071300	0.140994	0.914048	0.908173	0.911101	0.971815
3000	0.056600	0.140511	0.914443	0.912764	0.913603	0.971263