Precision calculations

[exodiasleftleg]

Hello @tamerthamoqa, I am using this repo on a custom dataset, but I encountered some weird behaviour, every other metric constantly changes during epochs, but Precision always stays the same at 0.5000+-0.5000. I have also defined a custom validation dataset for which I generated an equal amount of positive and negative pairs in total consisting of 422 pairs, here's an example on one of the epochs:

100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:22<00:00, 4.45it/s] Epoch 137: Number of valid training triplets in epoch: 4 Validating on LFW! ... 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:01<00:00, 2.65it/s] Accuracy on LFW: 0.8818+-0.0417 Precision 0.5000+-0.5000 Recall 0.4364+-0.4368 ROC Area Under Curve: 0.1977 Best distance threshold: 1.16+-0.03 TAR: 0.2068+-0.2145 @ FAR: 0.0000

I tried reducing the range of threshold from the default to: thresholds_roc = np.arange(0.5, 0.8, 0.1) thresholds_val = np.arange(0.5, 0.8, 0.1) But the precision stays the same. My question is what's going on with the precision calculations as far as I have reviewed the calculation logic checks out? Thank you in advance.