Based on the given feature description and task, it seems that the SEQN variable represents a respondent sequence number. 

Without further information, it is difficult to determine the appropriate ranges of values for the feature SEQN. However, we can assume that each respondent has a unique sequence number, so the possible values of SEQN should be unique for each target class.

Since the task is to predict whether a person belongs to the "Senior" or "Non-Senior" age group, there might not be a direct relationship between the sequence number and age group. Therefore, I would not consider the feature SEQN as directly informative for this task.

However, assuming we have already identified the appropriate ranges of SEQN values, I will provide a sample dictionary with possible values for each target class (i.e., 'Adult' and 'Senior').

```json
{
	"Adult": [1000.0, 2000.0, 3000.0, 4000.0, 5000.0],
	"Senior": [6000.0, 7000.0, 8000.0, 9000.0, 10000.0]
}
```

Please note that the above values are randomly chosen as examples and may not be representative of the actual data. To provide more accurate and specific values, additional information about the ranges and distribution of SEQN values for each age group would be necessary.