Class prediction of unlabeled data using WEKA

I am using WEKA GUI (3.8.5) for my classification task. I have built several classification models that classify each instance to 0 or 1.

The training set consists of 791 instances for class 1 and 18939 instances for class 0.
The test set consists of 993 instances for class 1 and 3939 instances for class 0.
MCC values of training and test set are above 0.95 for all classification models.

After saving the models, I have loaded them to make predictions for unlabeled data with 84656 instances.

I followed the steps below:

1. prepare unlabeled test data with notepad: insert '?' in class labels
2. load train data in preprocess window
3. load a saved model in result list in classify window
4. load unlabeled test data on supplied test set
5. click 'more options' and choose 'Plaintext' for the output predictions
6. click 're-evaluate model on current test set'

However, as the result, all models predicted all instances in unlabeled test data as class 1. 
In summary section, all instances were positioned in 'ignored class unknown instances.
Is the model simply overfitted to the training data? or is it due to some kind of mistakes in my workflow?
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