Following this workflow. topTable contains these data-

topTable(fit2, coef=1)

        logFC  AveExpr          t      P.Value    adj.P.Val         B
XYZ_11111 -0.5288943 3.348961 -31.490438 1.904000e-20 7.676928e-17 33.060675
XYZ_54843 -0.6151814 3.428361 -29.101503 1.123788e-19 2.265557e-16 31.893729
XYZ_23653 -0.4490212 3.365806 -21.482090 9.636024e-17 1.295082e-13 26.893025
XYZ_01465 -0.3953170 3.361865 -20.340465 3.192614e-16 3.218155e-13 25.923750
XYZ_15443 -0.2702862 3.298451 -19.267538 1.041336e-15 8.397331e-13 24.946045
XYZ_01657 -0.2676272 3.379435 -11.980717 2.222413e-11 1.493462e-08 16.041592
XYZ_08574  0.2843810 3.856233  10.898633 1.437526e-10 8.280150e-08 14.276416
XYZ_03652  0.1510402 3.307498   7.752358 7.225878e-08 3.237193e-05  8.266920
XYZ_01968  0.1993020 3.379461   7.560026 1.101854e-07 4.442677e-05  7.854332

decideTests(fit2)
table(decideTests(fit2))
aw <- arrayWeights(exprs(gse),design)
aw
fit <- lmFit(exprs(gse), design, weights = aw)
fit
contrasts <- makeContrasts(Group1 - Group2, Group2 - Group3,levels=design)
contrasts
fit2 <- contrasts.fit(fit, contrasts)
fit2
fit2 <- eBayes(fit2)
anno <- fData(gse)
anno
anno <- select(anno,ID,Symbol, ORF)
fit2$genes <- anno

But here topTable doesn't have LogFc and B columns. tops table contains these columns only-

topTable(fit2)

    ID  Symbol  ORF AveExpr F   P.Value adj.P.Val