Oh, I wrote the wrong thing about 1). Correct with 0<pos_weight <1.
The model’s prediction changes from 0. to <1 unless the value of pos_weight is less than 1.
Here is an example of learning when pos_weight is greater than 1.
0608-1349×691 2.53 KB

As you can see from the above valid loss value, there was a change in the value that increased and decreased at a certain moment.
In addition, when Icreate targets using the method you informed, I get the following error.

Is it wrong to create targets and weight each sample with samples_weights = [weights[t] for t in targets]?
Thanks!