Based on the given feature description, the SEQN is a respondent sequence number, which is a numeric variable. To determine the appropriate ranges of values for the target classes 'Adult' and 'Senior', we need additional information about what age range defines each class. Without this information, it is not possible to assign specific SEQN values to each target class accurately.

However, assuming 'Adult' and 'Senior' correspond to the general age ranges, we can make some generalizations:

1. 'Adult': SEQN values for 'Adult' class would typically fall within a certain range that corresponds to young and middle-aged adults. Without specific information, it is difficult to determine the exact range. Possible SEQN values could include [10000.0, 15000.0, 20000.0, 25000.0, 30000.0].

2. 'Senior': SEQN values for 'Senior' class would typically fall within a range that corresponds to older adults. Again, without specific information, it is difficult to determine the exact range. Possible SEQN values for 'Senior' could include [35000.0, 40000.0, 45000.0, 50000.0, 55000.0].

Based on this analysis, the dictionary would be as follows:

```json
{
	"Adult": [10000.0, 15000.0, 20000.0, 25000.0, 30000.0],
	"Senior": [35000.0, 40000.0, 45000.0, 50000.0, 55000.0]
}
```