i am using vglm for multiple logistic regression.
i have 1 response variable (total 4 category)
and 5 predictor.

Call:
vglm(formula = class ~ PC1 + PC2 + PC3 + PC4 + PC5, family = multinomial(),
    na.action = na.pass)

Coefficients:
(Intercept):1 (Intercept):2         PC1:1         PC1:2         PC2:1
   -0.5480417    -1.0716498     0.5146799     0.1578941    -0.3111874
        PC2:2         PC3:1         PC3:2         PC4:1         PC4:2
    0.5213314    -0.9584294    -0.9889684     0.8510812     1.2110904
        PC5:1         PC5:2
    0.5832257     0.5126038

Degrees of Freedom: 330 Total; 318 Residual
Residual Deviance: 216.9244
Log-likelihood: -108.4622


i am not understanding whether this model is good or not.
what log likelihood value says ? whether it should be low or high ?

because i used this model to predict the 4 category of response variable by
choosing those datapoint which were used to fit the model.

i get 72% of training data ( those which were used to fit model) correctly
predicted.

please help

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