Training issue

[snehashis1997]

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Dataset	gamma neg	highest map (after 40 epcoh)
f/m: 460/694	4	86.69
f/m: 460/694	3	87.94
f/m: 460/694	2	87.67
f/m: 460/694	5	85.66
f/m: 460/694	6	84.34
f/m: 464/1500	4	90.21
f/m: 464/1500	3	92.95
f/m: 464/1500	2	90.39
f/m: 464/1500	5	90.88
f/m: 464/1500	6	91.23
f/m: 464/1942	4	92.51
f/m: 464/1942	3	92.6
f/m: 464/1942	2	92.99
f/m: 464/1942	5	92.9
f/m: 464/1942	6	90.73

[snehashis1997]

Here are my findings about ASL training on my custom dataset, where "f/m" defines two different classes and their item numbers. In this setup, I set gamma_pos to 0. You can see that I increased the imbalance steadily, but I could not find a clear relationship between the gamma_neg value and mAP (mean Average Precision).

For the first set of data, where the imbalance is not too high, we get a better mAP with gamma_neg == 3. However, in the third set, where the imbalance is significantly higher, we achieve a better mAP with gamma_neg == 2. I think we should get a better map value at gammaneg == 6. Can you please explain if I am doing something wrong? What are your suggestions?