Below is a eval record of server. I wonder why test_total and val_total are decimals? From my understanding, this is global model evaluation. If the total number of my test set is 872, the number of test samples in each evaluation is 872 or 872/num of clients (in my case, it is 3)?
rayrayraykk
commented
6 months ago
Below is a eval record of server. I wonder why test_total and val_total are decimals? From my understanding, this is global model evaluation. If the total number of my test set is 872, the number of test samples in each evaluation is 872 or 872/num of clients (in my case, it is 3)?
{'Role': 'Server #', 'Round': 1, 'Results_weighted_avg': {'test_loss': 205.44600348516343, 'test_total': 290.6666666666667, 'test_avg_loss': 0.7068027881307339, 'test_acc': 0.5091743119266054, 'val_loss': 154.90539731894472, 'val_total': 224.66666666666666, 'val_avg_loss': 0.6894755830396885, 'val_acc': 0.5534124629080118}, 'Results_avg': {'test_loss': 205.44401041666666, 'test_total': 290.6666666666667, 'test_avg_loss': 0.7067977845605226, 'test_acc': 0.5091875024686969, 'val_loss': 154.90218098958334, 'val_total': 224.66666666666666, 'val_avg_loss': 0.6894642857142856, 'val_acc': 0.5534457671957672}, 'Results_fairness': {'test_total': 290.6666666666667, 'val_total': 224.66666666666666, 'test_loss_std': 2.7915573098698245, 'test_loss_bottom_decile': 203.2431640625, 'test_loss_top_decile': 209.3828125, 'test_loss_min': 203.2431640625, 'test_loss_max': 209.3828125, 'test_loss_bottom10%': nan, 'test_loss_top10%': 209.3828125, 'test_loss_cos1': 0.9999076969612101, 'test_loss_entropy': 1.0985202582012823, 'test_avg_loss_std': 0.009149269452723627, 'test_avg_loss_bottom_decile': 0.6984301170532646, 'test_avg_loss_top_decile': 0.7195285652920962, 'test_avg_loss_min': 0.6984301170532646, 'test_avg_loss_max': 0.7195285652920962, 'test_avg_loss_bottom10%': nan, 'test_avg_loss_top10%': 0.7195285652920962, 'test_avg_loss_cos1': 0.999916228188608, 'test_avg_loss_entropy': 1.0985287222378004, 'test_acc_std': 0.02519823611017372, 'test_acc_bottom_decile': 0.4742268041237113, 'test_acc_top_decile': 0.5326460481099656, 'test_acc_min': 0.4742268041237113, 'test_acc_max': 0.5326460481099656, 'test_acc_bottom10%': nan, 'test_acc_top10%': 0.5326460481099656, 'test_acc_cos1': 0.998777755685617, 'test_acc_entropy': 1.097375117975531, 'val_loss_std': 2.4467666521872635, 'val_loss_bottom_decile': 152.734375, 'val_loss_top_decile': 158.32177734375, 'val_loss_min': 152.734375, 'val_loss_max': 158.32177734375, 'val_loss_bottom10%': nan, 'val_loss_top10%': 158.32177734375, 'val_loss_cos1': 0.9998752734853387, 'val_loss_entropy': 1.0984879472148361, 'val_avg_loss_std': 0.010041464909396417, 'val_avg_loss_bottom_decile': 0.6818498883928571, 'val_avg_loss_top_decile': 0.70365234375, 'val_avg_loss_min': 0.6818498883928571, 'val_avg_loss_max': 0.70365234375, 'val_avg_loss_bottom10%': nan, 'val_avg_loss_top10%': 0.70365234375, 'val_avg_loss_cos1': 0.9998939595599015, 'val_avg_loss_entropy': 1.0985065869345862, 'val_acc_std': 0.026944572693224266, 'val_acc_bottom_decile': 0.5155555555555555, 'val_acc_top_decile': 0.5758928571428571, 'val_acc_min': 0.5155555555555555, 'val_acc_max': 0.5758928571428571, 'val_acc_bottom10%': nan, 'val_acc_top10%': 0.5758928571428571, 'val_acc_cos1': 0.9988169822369142, 'val_acc_entropy': 1.0974135282771185}}