The P R F1-score and [email protected] are around 90% after sparse training (--s 0.001 --prune 0). Still the sparse model is not performing well on the test dataset.

[Abhishek672]

Hey @tanluren @zbyuan
I have trained yolov4-tiny model on a small dataset of size ~64 with augmentations (total size is 450) for a single class. For a given test dataset the original model is giving 89% P,R values.
Then I did the sparse training on the model with --s 0.001 and --prune 0 for 300 epochs. For the same test dataset the sparse model is giving 34% Recall, which is very low. I tried for s [0.01, 0.001, 0.0001] and the results are same.
Is it the epochs or the size of training dataset that is causing problem? Or there is any other issue?
I am stuck into this for a week now.

Any suggestions??