Failure to report the mediocre results is unethical
When writing an academic paper, pretending that you did not get bad results for some cases that you were hoping to get good results from is unethical and damaging, both to your credibility/reputation, and to the field, as others may waste time trying to use your code in cases that it doesn't work for.
But take note...
There's a difference between reporting your mediocre results, and emphasising them. Your method works well when the datasets have a 1:1 ratio. This should be the central focus of your paper. Focus the paper on that aspect - your new method is great for those cases!
The mediocre results are simply other results. You have shown that it works well for 1:1 ratios. You have also found that it does not do well for 1:5 ratios. This is also useful information. Make a note of it - you have examined the performance of your approach for cases with 1:5 ratios, and found that it does not perform as well.
Not only is this a way to be ethical while also focusing on the good, but it gives you the opportunity to point towards further research possibilities - why doesn't your method work for 1:5 ratios? This is clearly an area for further investigation! If you know what's causing the problem, then simply point to it and note that further work is needed to extend the approach to work for these cases.
It's to your benefit!
Your first instinct might be to think that people will dismiss your work because you mention some weaknesses. This would be folly. People will see your approach, think of a new way to adapt your approach to other cases, and publish... referencing YOUR paper as they do so. And that increases your citations.
If you don't mention the weaknesses, then it's less likely that people will spend time thinking about how to adapt your approach - instead, they'll dismiss your approach as faulty when it doesn't work for their situations, and ignore it.
Get the balance right
You need to mention the mediocre results, but they shouldn't be at all central to the paper. The trick to this is to frame the paper as focused on the 1:1 ratio cases. It is here that the model works well, and thus you are reporting a new approach to 1:1 ratio cases. When discussing the results of the model, you include a small section discussing what happens for 1:5 and 1:10 ratios - this should not be to the same level of detail as the 1:1 ratio cases, however!
"When applied to more unbalanced ratios, such as 1:5 ratio cases, it is found that the approach does not perform as well, achieving only XXX where other approaches can achieve YYY. This can be seen, for example, in case ZZZ,..."