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Defense without Forgetting_Continual Adversarial Defense with Anisotropic and Isotropic Pseudo Replay - Reproduction
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Mina Moshfegh
Defense without Forgetting_Continual Adversarial Defense with Anisotropic and Isotropic Pseudo Replay - Reproduction
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fbee6f95
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fbee6f95
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Mina Moshfegh
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results/CIFAR100-AIR-__FGSM____None__.log
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[2025-03-14 14:53:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] === Configuration ===
[2025-03-14 14:53:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Config(seed=42, device='cuda', epochs=50, batch_size=64, learning_rate=0.01, momentum=0.9, weight_decay=0.0005, epsilon=0.03137254901960784, alpha=0.00784313725490196, num_steps=10, random_init=True, defense_method='AIR', lambda_SD=1.0, lambda_IR=1.0, lambda_AR=1.0, lambda_Reg=1.0, alpha_range=(0.3, 0.7), use_rdrop=True, iso_noise_std=0.01, iso_clamp_min=0.0, iso_clamp_max=1.0, iso_p_flip=0.5, iso_flip_dim=3, iso_p_rotation=0.5, iso_max_rotation=10, iso_p_crop=0.5, iso_p_erase=0.5, dataset='CIFAR100', data_root='./data', num_workers=2, lambda_lfl=1.0, feature_lambda=1.0, freeze_classifier=True, joint_lambda=0.5, adv_lambda=0.8, feat_lambda=1.0, lambda_ewc=100.0, attack_sequence=('FGSM', 'None'))
[2025-03-14 14:53:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] --- Task 1 / 2: Attack = FGSM ---
[2025-03-14 14:53:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Using AIR Defense...
[2025-03-14 14:53:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 4.6510
[2025-03-14 14:57:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.6109
[2025-03-14 15:01:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 4.6244
[2025-03-14 15:04:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 4.1877
[2025-03-14 15:08:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 4.3611
[2025-03-14 15:12:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 4.1772
[2025-03-14 15:16:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 4.2274
[2025-03-14 15:20:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 4.6236
[2025-03-14 15:23:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [1/50] - Train Loss: 4.3797
[2025-03-14 15:23:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 9.40%
[2025-03-14 15:23:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 4.0727
[2025-03-14 15:27:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.0231
[2025-03-14 15:31:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 4.1109
[2025-03-14 15:35:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 4.0461
[2025-03-14 15:39:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 4.7163
[2025-03-14 15:42:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.4583
[2025-03-14 15:46:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 4.0849
[2025-03-14 15:50:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 4.1267
[2025-03-14 15:53:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [2/50] - Train Loss: 3.9555
[2025-03-14 15:54:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 11.22%
[2025-03-14 15:54:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 4.0292
[2025-03-14 15:57:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.5642
[2025-03-14 16:01:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.8450
[2025-03-14 16:05:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.3694
[2025-03-14 16:09:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 3.0969
[2025-03-14 16:13:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.0256
[2025-03-14 16:17:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 3.4149
[2025-03-14 16:21:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 3.0138
[2025-03-14 16:24:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [3/50] - Train Loss: 3.5852
[2025-03-14 16:24:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 19.72%
[2025-03-14 16:24:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.2171
[2025-03-14 16:28:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 3.4302
[2025-03-14 16:32:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.8159
[2025-03-14 16:36:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.8167
[2025-03-14 16:39:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 3.9482
[2025-03-14 16:43:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.0907
[2025-03-14 16:47:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.7642
[2025-03-14 16:51:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.9206
[2025-03-14 16:54:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [4/50] - Train Loss: 3.3634
[2025-03-14 16:54:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 11.51%
[2025-03-14 16:54:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.9411
[2025-03-14 16:58:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 3.9231
[2025-03-14 17:02:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.4281
[2025-03-14 17:06:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 2.7888
[2025-03-14 17:10:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.9803
[2025-03-14 17:14:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.7907
[2025-03-14 17:17:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.8453
[2025-03-14 17:21:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 4.4357
[2025-03-14 17:24:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [5/50] - Train Loss: 3.1396
[2025-03-14 17:25:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 7.94%
[2025-03-14 17:25:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 2.7162
[2025-03-14 17:29:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.4443
[2025-03-14 17:32:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.6357
[2025-03-14 17:36:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 2.3908
[2025-03-14 17:40:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.9148
[2025-03-14 17:44:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.2614
[2025-03-14 17:48:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.5899
[2025-03-14 17:52:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.4666
[2025-03-14 17:55:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [6/50] - Train Loss: 3.0592
[2025-03-14 17:55:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 16.22%
[2025-03-14 17:55:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 2.3692
[2025-03-14 17:59:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.4475
[2025-03-14 18:03:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.1639
[2025-03-14 18:07:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 2.3687
[2025-03-14 18:11:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.6029
[2025-03-14 18:14:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.6511
[2025-03-14 18:18:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 4.2321
[2025-03-14 18:22:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.6283
[2025-03-14 18:25:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [7/50] - Train Loss: 2.8881
[2025-03-14 18:25:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 7.96%
[2025-03-14 18:25:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.7856
[2025-03-14 18:29:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 3.5653
[2025-03-14 18:33:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 2.5007
[2025-03-14 18:37:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.3837
[2025-03-14 18:41:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.1124
[2025-03-14 18:45:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.0075
[2025-03-14 18:49:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.2766
[2025-03-14 18:52:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.6210
[2025-03-14 18:55:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [8/50] - Train Loss: 2.6864
[2025-03-14 18:56:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 19.31%
[2025-03-14 18:56:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 2.0488
[2025-03-14 19:00:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.1288
[2025-03-14 19:04:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 2.3306
[2025-03-14 19:07:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.7076
[2025-03-14 19:11:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.1335
[2025-03-14 19:15:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.9349
[2025-03-14 19:19:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.5137
[2025-03-14 19:23:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.4454
[2025-03-14 19:26:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [9/50] - Train Loss: 2.5736
[2025-03-14 19:26:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 7.26%
[2025-03-14 19:26:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.8544
[2025-03-14 19:30:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.1323
[2025-03-14 19:34:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 2.5587
[2025-03-14 19:38:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 2.2631
[2025-03-14 19:42:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.3057
[2025-03-14 19:45:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.3765
[2025-03-14 19:49:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.2074
[2025-03-14 19:53:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.2307
[2025-03-14 19:56:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [10/50] - Train Loss: 2.5173
[2025-03-14 19:57:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 10.79%
[2025-03-14 19:57:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.7719
[2025-03-14 20:01:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.6257
[2025-03-14 20:05:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 2.3326
[2025-03-14 20:08:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 4.3015
[2025-03-14 20:12:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.8496
[2025-03-14 20:16:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.8237
[2025-03-14 20:20:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 3.1514
[2025-03-14 20:24:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.1827
[2025-03-14 20:27:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [11/50] - Train Loss: 2.3170
[2025-03-14 20:28:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 11.50%
[2025-03-14 20:28:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.6717
[2025-03-14 20:31:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.2556
[2025-03-14 20:35:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.7819
[2025-03-14 20:39:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.9609
[2025-03-14 20:43:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.8432
[2025-03-14 20:47:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.8590
[2025-03-14 20:51:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.2366
[2025-03-14 20:55:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.1024
[2025-03-14 20:58:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [12/50] - Train Loss: 2.2633
[2025-03-14 20:58:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 4.00%
[2025-03-14 20:58:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.8211
[2025-03-14 21:02:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.3221
[2025-03-14 21:06:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.7931
[2025-03-14 21:10:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.3440
[2025-03-14 21:14:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.7624
[2025-03-14 21:18:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.9622
[2025-03-14 21:22:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.0419
[2025-03-14 21:26:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.3207
[2025-03-14 21:29:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [13/50] - Train Loss: 2.2919
[2025-03-14 21:29:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 12.66%
[2025-03-14 21:29:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.0312
[2025-03-14 21:33:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.1814
[2025-03-14 21:37:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 2.0647
[2025-03-14 21:41:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 2.1330
[2025-03-14 21:45:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.8918
[2025-03-14 21:49:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.0625
[2025-03-14 21:53:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7439
[2025-03-14 21:56:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.7433
[2025-03-14 22:00:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [14/50] - Train Loss: 2.1040
[2025-03-14 22:00:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 9.10%
[2025-03-14 22:00:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.4799
[2025-03-14 22:04:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.7953
[2025-03-14 22:08:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.7487
[2025-03-14 22:12:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.6010
[2025-03-14 22:16:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.0048
[2025-03-14 22:19:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.3186
[2025-03-14 22:23:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7718
[2025-03-14 22:27:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 3.3802
[2025-03-14 22:30:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [15/50] - Train Loss: 2.0123
[2025-03-14 22:31:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 12.41%
[2025-03-14 22:31:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.9601
[2025-03-14 22:35:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 2.3280
[2025-03-14 22:39:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.0472
[2025-03-14 22:42:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.9314
[2025-03-14 22:46:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.5779
[2025-03-14 22:50:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 2.6712
[2025-03-14 22:54:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7359
[2025-03-14 22:58:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.7997
[2025-03-14 23:01:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [16/50] - Train Loss: 2.1155
[2025-03-14 23:01:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 12.19%
[2025-03-14 23:02:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.5159
[2025-03-14 23:05:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.6167
[2025-03-14 23:09:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.4841
[2025-03-14 23:13:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.5341
[2025-03-14 23:17:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.5796
[2025-03-14 23:21:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.2777
[2025-03-14 23:25:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7602
[2025-03-14 23:29:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 3.6832
[2025-03-14 23:32:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [17/50] - Train Loss: 1.9796
[2025-03-14 23:32:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 17.24%
[2025-03-14 23:32:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.6709
[2025-03-14 23:36:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 3.2901
[2025-03-14 23:40:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.5594
[2025-03-14 23:44:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.3779
[2025-03-14 23:48:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.5357
[2025-03-14 23:52:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.7073
[2025-03-14 23:56:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.6288
[2025-03-15 00:00:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.3870
[2025-03-15 00:03:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [18/50] - Train Loss: 1.7901
[2025-03-15 00:03:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 9.45%
[2025-03-15 00:03:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.4907
[2025-03-15 00:07:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.6892
[2025-03-15 00:11:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.3988
[2025-03-15 00:15:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.8401
[2025-03-15 00:19:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 4.3480
[2025-03-15 00:23:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.3210
[2025-03-15 00:27:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7908
[2025-03-15 00:30:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.2895
[2025-03-15 00:34:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [19/50] - Train Loss: 1.6768
[2025-03-15 00:34:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 16.96%
[2025-03-15 00:34:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.5168
[2025-03-15 00:38:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.1799
[2025-03-15 00:42:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.2300
[2025-03-15 00:46:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.3634
[2025-03-15 00:50:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.8607
[2025-03-15 00:53:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.6191
[2025-03-15 00:57:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7017
[2025-03-15 01:01:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.7221
[2025-03-15 01:04:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [20/50] - Train Loss: 1.8895
[2025-03-15 01:05:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 20.39%
[2025-03-15 01:05:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.5473
[2025-03-15 01:09:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.4432
[2025-03-15 01:13:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.5351
[2025-03-15 01:16:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 2.1113
[2025-03-15 01:20:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.4488
[2025-03-15 01:24:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.4271
[2025-03-15 01:28:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.4043
[2025-03-15 01:32:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.6713
[2025-03-15 01:35:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [21/50] - Train Loss: 1.7502
[2025-03-15 01:35:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 24.75%
[2025-03-15 01:36:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.2476
[2025-03-15 01:39:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.5813
[2025-03-15 01:43:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.4487
[2025-03-15 01:47:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.3802
[2025-03-15 01:51:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.5084
[2025-03-15 01:55:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.4075
[2025-03-15 01:59:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.3499
[2025-03-15 02:03:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.7649
[2025-03-15 02:06:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [22/50] - Train Loss: 1.6805
[2025-03-15 02:06:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 25.86%
[2025-03-15 02:06:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.1897
[2025-03-15 02:10:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.8954
[2025-03-15 02:14:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.2763
[2025-03-15 02:18:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 4.0747
[2025-03-15 02:22:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 3.8168
[2025-03-15 02:26:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.1889
[2025-03-15 02:29:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.2889
[2025-03-15 02:33:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.4182
[2025-03-15 02:36:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [23/50] - Train Loss: 1.6407
[2025-03-15 02:37:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 39.90%
[2025-03-15 02:37:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.0339
[2025-03-15 02:40:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.1168
[2025-03-15 02:44:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 4.3697
[2025-03-15 02:48:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.7540
[2025-03-15 02:52:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.1322
[2025-03-15 02:56:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.1492
[2025-03-15 03:00:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.2871
[2025-03-15 03:04:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.1050
[2025-03-15 03:07:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [24/50] - Train Loss: 1.4408
[2025-03-15 03:07:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 31.31%
[2025-03-15 03:07:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.9284
[2025-03-15 03:11:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.1539
[2025-03-15 03:15:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 3.7596
[2025-03-15 03:18:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.2220
[2025-03-15 03:22:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.3884
[2025-03-15 03:26:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.4563
[2025-03-15 03:30:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.7899
[2025-03-15 03:34:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 3.5985
[2025-03-15 03:37:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [25/50] - Train Loss: 1.6050
[2025-03-15 03:37:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 34.83%
[2025-03-15 03:37:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.4687
[2025-03-15 03:41:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.8484
[2025-03-15 03:45:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.3663
[2025-03-15 03:49:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.0489
[2025-03-15 03:53:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.8510
[2025-03-15 03:56:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.8671
[2025-03-15 04:00:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.8365
[2025-03-15 04:04:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.8889
[2025-03-15 04:07:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [26/50] - Train Loss: 1.2398
[2025-03-15 04:08:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 34.54%
[2025-03-15 04:08:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.8169
[2025-03-15 04:11:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.8832
[2025-03-15 04:15:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.0976
[2025-03-15 04:19:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.9892
[2025-03-15 04:23:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.8492
[2025-03-15 04:27:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.5533
[2025-03-15 04:31:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.8231
[2025-03-15 04:34:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.7420
[2025-03-15 04:37:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [27/50] - Train Loss: 1.1701
[2025-03-15 04:38:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 40.60%
[2025-03-15 04:38:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.3217
[2025-03-15 04:42:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.5507
[2025-03-15 04:46:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.9466
[2025-03-15 04:49:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.4510
[2025-03-15 04:53:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.0481
[2025-03-15 04:57:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.7285
[2025-03-15 05:01:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.1905
[2025-03-15 05:05:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.8290
[2025-03-15 05:08:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [28/50] - Train Loss: 1.2374
[2025-03-15 05:08:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 22.61%
[2025-03-15 05:08:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.7401
[2025-03-15 05:12:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.7130
[2025-03-15 05:16:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.5390
[2025-03-15 05:20:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.6619
[2025-03-15 05:23:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.8783
[2025-03-15 05:27:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.9131
[2025-03-15 05:31:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 3.5191
[2025-03-15 05:35:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.9235
[2025-03-15 05:38:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [29/50] - Train Loss: 1.0177
[2025-03-15 05:38:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 24.80%
[2025-03-15 05:38:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 1.4487
[2025-03-15 05:42:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.2438
[2025-03-15 05:46:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.7000
[2025-03-15 05:50:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.5920
[2025-03-15 05:54:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.5829
[2025-03-15 05:58:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.6413
[2025-03-15 06:01:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.7351
[2025-03-15 06:05:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.7652
[2025-03-15 06:08:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [30/50] - Train Loss: 0.7914
[2025-03-15 06:09:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 36.06%
[2025-03-15 06:09:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.4784
[2025-03-15 06:12:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.5616
[2025-03-15 06:16:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.8395
[2025-03-15 06:20:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.8230
[2025-03-15 06:24:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 3.0893
[2025-03-15 06:28:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.7962
[2025-03-15 06:32:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.6677
[2025-03-15 06:35:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.4382
[2025-03-15 06:39:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [31/50] - Train Loss: 1.4432
[2025-03-15 06:39:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 42.79%
[2025-03-15 06:39:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.6374
[2025-03-15 06:43:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.9448
[2025-03-15 06:47:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3421
[2025-03-15 06:50:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.6014
[2025-03-15 06:54:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.6080
[2025-03-15 06:58:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.6848
[2025-03-15 07:02:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.5595
[2025-03-15 07:06:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.8520
[2025-03-15 07:09:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [32/50] - Train Loss: 0.6533
[2025-03-15 07:09:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 47.98%
[2025-03-15 07:09:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.4611
[2025-03-15 07:13:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3648
[2025-03-15 07:17:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.4763
[2025-03-15 07:21:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.4300
[2025-03-15 07:24:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.3682
[2025-03-15 07:28:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.4759
[2025-03-15 07:32:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.5517
[2025-03-15 07:36:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.5319
[2025-03-15 07:39:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [33/50] - Train Loss: 0.4601
[2025-03-15 07:39:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 50.17%
[2025-03-15 07:39:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.5566
[2025-03-15 07:43:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3236
[2025-03-15 07:47:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3883
[2025-03-15 07:51:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.2834
[2025-03-15 07:55:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.3431
[2025-03-15 07:59:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.4448
[2025-03-15 08:02:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.4192
[2025-03-15 08:06:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.5965
[2025-03-15 08:09:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [34/50] - Train Loss: 0.4324
[2025-03-15 08:10:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 50.11%
[2025-03-15 08:10:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2396
[2025-03-15 08:14:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3026
[2025-03-15 08:17:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2191
[2025-03-15 08:21:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.4382
[2025-03-15 08:25:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.2866
[2025-03-15 08:29:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.5013
[2025-03-15 08:33:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.3554
[2025-03-15 08:36:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.4018
[2025-03-15 08:40:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [35/50] - Train Loss: 0.3993
[2025-03-15 08:40:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 46.14%
[2025-03-15 08:40:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2178
[2025-03-15 08:44:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3666
[2025-03-15 08:48:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3909
[2025-03-15 08:51:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 4.5609
[2025-03-15 08:55:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 4.5020
[2025-03-15 08:59:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.5253
[2025-03-15 09:03:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.3868
[2025-03-15 09:07:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.9603
[2025-03-15 09:10:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [36/50] - Train Loss: 2.1250
[2025-03-15 09:10:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 58.74%
[2025-03-15 09:10:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.7649
[2025-03-15 09:14:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.2664
[2025-03-15 09:18:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.1123
[2025-03-15 09:22:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.6381
[2025-03-15 09:25:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.7900
[2025-03-15 09:29:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.7720
[2025-03-15 09:33:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.8926
[2025-03-15 09:37:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.1563
[2025-03-15 09:40:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [37/50] - Train Loss: 1.0950
[2025-03-15 09:40:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 60.63%
[2025-03-15 09:40:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.4732
[2025-03-15 09:44:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3329
[2025-03-15 09:48:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 1.3241
[2025-03-15 09:52:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.6230
[2025-03-15 09:56:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 1.7321
[2025-03-15 09:59:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.5004
[2025-03-15 10:03:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 2.8034
[2025-03-15 10:07:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.6677
[2025-03-15 10:10:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [38/50] - Train Loss: 0.9856
[2025-03-15 10:10:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 58.33%
[2025-03-15 10:10:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.3232
[2025-03-15 10:14:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.7160
[2025-03-15 10:18:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.6057
[2025-03-15 10:22:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.0586
[2025-03-15 10:26:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.3511
[2025-03-15 10:29:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.3756
[2025-03-15 10:33:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.3201
[2025-03-15 10:37:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.4645
[2025-03-15 10:40:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [39/50] - Train Loss: 0.6678
[2025-03-15 10:40:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 48.88%
[2025-03-15 10:40:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2930
[2025-03-15 10:44:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 5.2936
[2025-03-15 10:48:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3854
[2025-03-15 10:52:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.4668
[2025-03-15 10:56:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.4900
[2025-03-15 11:00:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.3622
[2025-03-15 11:03:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2495
[2025-03-15 11:07:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 2.0708
[2025-03-15 11:10:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [40/50] - Train Loss: 0.9054
[2025-03-15 11:11:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 55.20%
[2025-03-15 11:11:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 2.8855
[2025-03-15 11:14:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 1.0349
[2025-03-15 11:18:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3358
[2025-03-15 11:22:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.8891
[2025-03-15 11:26:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.4475
[2025-03-15 11:30:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.4286
[2025-03-15 11:33:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 4.5848
[2025-03-15 11:37:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.9837
[2025-03-15 11:40:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [41/50] - Train Loss: 1.0837
[2025-03-15 11:41:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 60.60%
[2025-03-15 11:41:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.3054
[2025-03-15 11:45:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.5372
[2025-03-15 11:48:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.5818
[2025-03-15 11:52:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.4670
[2025-03-15 11:56:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.7865
[2025-03-15 12:00:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.5141
[2025-03-15 12:04:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.5060
[2025-03-15 12:07:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.5580
[2025-03-15 12:11:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [42/50] - Train Loss: 0.8354
[2025-03-15 12:11:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 60.62%
[2025-03-15 12:11:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.4896
[2025-03-15 12:15:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1708
[2025-03-15 12:19:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2503
[2025-03-15 12:22:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.3275
[2025-03-15 12:26:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.4800
[2025-03-15 12:30:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.2237
[2025-03-15 12:34:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2578
[2025-03-15 12:38:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2801
[2025-03-15 12:41:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [43/50] - Train Loss: 0.2714
[2025-03-15 12:41:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 52.11%
[2025-03-15 12:41:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1921
[2025-03-15 12:45:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0791
[2025-03-15 12:49:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2395
[2025-03-15 12:53:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.2268
[2025-03-15 12:57:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1815
[2025-03-15 13:01:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.2434
[2025-03-15 13:05:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.5069
[2025-03-15 13:09:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 5.2422
[2025-03-15 13:12:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [44/50] - Train Loss: 0.4985
[2025-03-15 13:12:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 58.06%
[2025-03-15 13:12:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.5507
[2025-03-15 13:16:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.4840
[2025-03-15 13:20:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.4772
[2025-03-15 13:24:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.8989
[2025-03-15 13:28:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.3163
[2025-03-15 13:32:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.3494
[2025-03-15 13:35:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2304
[2025-03-15 13:39:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.4421
[2025-03-15 13:42:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [45/50] - Train Loss: 0.7016
[2025-03-15 13:43:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 56.32%
[2025-03-15 13:43:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1680
[2025-03-15 13:47:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.2011
[2025-03-15 13:50:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3349
[2025-03-15 13:54:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1668
[2025-03-15 13:58:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1393
[2025-03-15 14:02:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.3964
[2025-03-15 14:06:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2270
[2025-03-15 14:10:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2141
[2025-03-15 14:13:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [46/50] - Train Loss: 0.2375
[2025-03-15 14:13:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 49.88%
[2025-03-15 14:13:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2274
[2025-03-15 14:17:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1154
[2025-03-15 14:21:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.6864
[2025-03-15 14:25:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 3.5275
[2025-03-15 14:29:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 2.6358
[2025-03-15 14:33:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.9395
[2025-03-15 14:37:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 1.6566
[2025-03-15 14:40:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.5398
[2025-03-15 14:44:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [47/50] - Train Loss: 1.1760
[2025-03-15 14:44:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 58.58%
[2025-03-15 14:44:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.6563
[2025-03-15 14:48:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.2441
[2025-03-15 14:52:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2758
[2025-03-15 14:56:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1867
[2025-03-15 14:59:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1757
[2025-03-15 15:03:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1598
[2025-03-15 15:07:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2724
[2025-03-15 15:11:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.4068
[2025-03-15 15:14:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [48/50] - Train Loss: 0.4472
[2025-03-15 15:15:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 55.02%
[2025-03-15 15:15:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2041
[2025-03-15 15:18:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.2911
[2025-03-15 15:22:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.3162
[2025-03-15 15:26:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1988
[2025-03-15 15:30:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1335
[2025-03-15 15:34:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.2396
[2025-03-15 15:38:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2251
[2025-03-15 15:42:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.3650
[2025-03-15 15:45:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [49/50] - Train Loss: 0.2325
[2025-03-15 15:45:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 56.43%
[2025-03-15 15:45:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2433
[2025-03-15 15:49:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1751
[2025-03-15 15:53:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2170
[2025-03-15 15:57:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.2309
[2025-03-15 16:01:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.2216
[2025-03-15 16:04:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1802
[2025-03-15 16:08:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.3380
[2025-03-15 16:12:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2668
[2025-03-15 16:15:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [50/50] - Train Loss: 0.2553
[2025-03-15 16:16:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 56.09%
[2025-03-15 16:16:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Model saved at: ./models/CIFAR100_AIR_FGSM_task0.pt
[2025-03-15 16:16:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Accuracy after Task 1, Attack=FGSM: 56.09%
[2025-03-15 16:17:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Robust Accuracy on FGSM after Task 1: 34.87%
[2025-03-15 16:17:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Robust Accuracy on None after Task 1: 56.09%
[2025-03-15 16:17:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] --- Task 2 / 2: Attack = None ---
[2025-03-15 16:17:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Using AIR Defense...
[2025-03-15 16:17:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 3.9821
[2025-03-15 16:21:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.5847
[2025-03-15 16:24:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 4.5077
[2025-03-15 16:27:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 4.4095
[2025-03-15 16:31:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 3.8092
[2025-03-15 16:34:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.1041
[2025-03-15 16:37:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2203
[2025-03-15 16:40:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1027
[2025-03-15 16:43:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [1/50] - Train Loss: 2.8387
[2025-03-15 16:43:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 56.07%
[2025-03-15 16:43:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1965
[2025-03-15 16:47:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.2034
[2025-03-15 16:50:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0636
[2025-03-15 16:53:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0609
[2025-03-15 16:56:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0675
[2025-03-15 17:00:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0346
[2025-03-15 17:03:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0382
[2025-03-15 17:06:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0998
[2025-03-15 17:09:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [2/50] - Train Loss: 0.1419
[2025-03-15 17:09:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 63.39%
[2025-03-15 17:09:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0452
[2025-03-15 17:13:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0449
[2025-03-15 17:16:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0258
[2025-03-15 17:19:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0250
[2025-03-15 17:22:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0400
[2025-03-15 17:26:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0476
[2025-03-15 17:29:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0100
[2025-03-15 17:32:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0158
[2025-03-15 17:35:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [3/50] - Train Loss: 0.0308
[2025-03-15 17:35:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 42.07%
[2025-03-15 17:35:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0208
[2025-03-15 17:38:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0183
[2025-03-15 17:42:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0110
[2025-03-15 17:45:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0188
[2025-03-15 17:48:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0059
[2025-03-15 17:52:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0069
[2025-03-15 17:55:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0110
[2025-03-15 17:58:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0207
[2025-03-15 18:01:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [4/50] - Train Loss: 0.0175
[2025-03-15 18:01:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 53.31%
[2025-03-15 18:01:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0127
[2025-03-15 18:04:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0065
[2025-03-15 18:08:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0216
[2025-03-15 18:11:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0063
[2025-03-15 18:14:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0089
[2025-03-15 18:17:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0046
[2025-03-15 18:21:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0069
[2025-03-15 18:24:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0718
[2025-03-15 18:27:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [5/50] - Train Loss: 0.0118
[2025-03-15 18:27:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 31.02%
[2025-03-15 18:27:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0068
[2025-03-15 18:30:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0038
[2025-03-15 18:34:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0060
[2025-03-15 18:37:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0156
[2025-03-15 18:40:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0075
[2025-03-15 18:43:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0087
[2025-03-15 18:47:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0059
[2025-03-15 18:50:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0054
[2025-03-15 18:53:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [6/50] - Train Loss: 0.0101
[2025-03-15 18:53:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 16.19%
[2025-03-15 18:53:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0058
[2025-03-15 18:56:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0056
[2025-03-15 18:59:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0067
[2025-03-15 19:03:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0043
[2025-03-15 19:06:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0283
[2025-03-15 19:09:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0110
[2025-03-15 19:13:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0140
[2025-03-15 19:16:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0105
[2025-03-15 19:19:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [7/50] - Train Loss: 0.0110
[2025-03-15 19:19:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 29.72%
[2025-03-15 19:19:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0058
[2025-03-15 19:22:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0074
[2025-03-15 19:25:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0099
[2025-03-15 19:29:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0066
[2025-03-15 19:32:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0221
[2025-03-15 19:35:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0083
[2025-03-15 19:39:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0098
[2025-03-15 19:42:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0268
[2025-03-15 19:44:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [8/50] - Train Loss: 0.0123
[2025-03-15 19:45:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 35.53%
[2025-03-15 19:45:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0088
[2025-03-15 19:48:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 4.4558
[2025-03-15 19:51:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1857
[2025-03-15 19:55:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0588
[2025-03-15 19:58:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1405
[2025-03-15 20:01:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0736
[2025-03-15 20:04:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0795
[2025-03-15 20:08:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0540
[2025-03-15 20:10:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [9/50] - Train Loss: 0.9265
[2025-03-15 20:11:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 46.07%
[2025-03-15 20:11:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0740
[2025-03-15 20:14:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0986
[2025-03-15 20:17:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0333
[2025-03-15 20:21:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0215
[2025-03-15 20:24:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0422
[2025-03-15 20:27:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0477
[2025-03-15 20:30:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0976
[2025-03-15 20:34:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0385
[2025-03-15 20:36:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [10/50] - Train Loss: 0.0605
[2025-03-15 20:37:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 27.17%
[2025-03-15 20:37:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0794
[2025-03-15 20:40:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0996
[2025-03-15 20:43:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0749
[2025-03-15 20:47:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0521
[2025-03-15 20:50:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0877
[2025-03-15 20:53:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0838
[2025-03-15 20:56:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1008
[2025-03-15 21:00:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1949
[2025-03-15 21:02:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [11/50] - Train Loss: 0.0945
[2025-03-15 21:03:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 35.92%
[2025-03-15 21:03:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0789
[2025-03-15 21:06:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.4504
[2025-03-15 21:09:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.4790
[2025-03-15 21:12:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 1.6364
[2025-03-15 21:16:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.4316
[2025-03-15 21:19:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.3742
[2025-03-15 21:22:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.3115
[2025-03-15 21:26:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.3318
[2025-03-15 21:28:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [12/50] - Train Loss: 0.6930
[2025-03-15 21:29:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 63.82%
[2025-03-15 21:29:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1649
[2025-03-15 21:32:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1908
[2025-03-15 21:35:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1417
[2025-03-15 21:38:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1560
[2025-03-15 21:42:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1389
[2025-03-15 21:45:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 4.3663
[2025-03-15 21:48:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.3113
[2025-03-15 21:52:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2244
[2025-03-15 21:54:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [13/50] - Train Loss: 0.3242
[2025-03-15 21:55:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 65.18%
[2025-03-15 21:55:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1525
[2025-03-15 21:58:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1643
[2025-03-15 22:01:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2826
[2025-03-15 22:04:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0964
[2025-03-15 22:08:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1547
[2025-03-15 22:11:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.4157
[2025-03-15 22:14:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1306
[2025-03-15 22:18:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2021
[2025-03-15 22:20:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [14/50] - Train Loss: 0.1642
[2025-03-15 22:21:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 64.54%
[2025-03-15 22:21:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1775
[2025-03-15 22:24:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0876
[2025-03-15 22:27:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0537
[2025-03-15 22:30:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0988
[2025-03-15 22:34:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1092
[2025-03-15 22:37:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0487
[2025-03-15 22:40:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0791
[2025-03-15 22:43:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1718
[2025-03-15 22:46:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [15/50] - Train Loss: 0.1440
[2025-03-15 22:46:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 65.31%
[2025-03-15 22:46:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2043
[2025-03-15 22:50:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1125
[2025-03-15 22:53:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2130
[2025-03-15 22:56:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.2465
[2025-03-15 23:00:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0810
[2025-03-15 23:03:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.8634
[2025-03-15 23:06:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2862
[2025-03-15 23:09:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.3467
[2025-03-15 23:12:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [16/50] - Train Loss: 0.2177
[2025-03-15 23:12:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 62.50%
[2025-03-15 23:12:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1475
[2025-03-15 23:16:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.2497
[2025-03-15 23:19:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1873
[2025-03-15 23:22:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.2345
[2025-03-15 23:25:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1297
[2025-03-15 23:29:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.2530
[2025-03-15 23:32:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1525
[2025-03-15 23:35:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1364
[2025-03-15 23:38:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [17/50] - Train Loss: 0.2522
[2025-03-15 23:38:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 65.36%
[2025-03-15 23:38:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1085
[2025-03-15 23:42:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0437
[2025-03-15 23:45:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1212
[2025-03-15 23:48:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1142
[2025-03-15 23:51:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 3.6265
[2025-03-15 23:55:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.8530
[2025-03-15 23:58:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1599
[2025-03-16 00:01:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 4.3602
[2025-03-16 00:04:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [18/50] - Train Loss: 0.6991
[2025-03-16 00:04:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 61.24%
[2025-03-16 00:04:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2098
[2025-03-16 00:07:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1721
[2025-03-16 00:11:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1342
[2025-03-16 00:14:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1452
[2025-03-16 00:17:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0805
[2025-03-16 00:21:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0825
[2025-03-16 00:24:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1831
[2025-03-16 00:27:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1418
[2025-03-16 00:30:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [19/50] - Train Loss: 0.2413
[2025-03-16 00:30:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 62.04%
[2025-03-16 00:30:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0932
[2025-03-16 00:33:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1156
[2025-03-16 00:37:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1361
[2025-03-16 00:40:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1812
[2025-03-16 00:43:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0988
[2025-03-16 00:46:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1250
[2025-03-16 00:50:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0961
[2025-03-16 00:53:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0982
[2025-03-16 00:56:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [20/50] - Train Loss: 0.1236
[2025-03-16 00:56:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 57.28%
[2025-03-16 00:56:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.4572
[2025-03-16 00:59:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1223
[2025-03-16 01:03:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1218
[2025-03-16 01:06:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1671
[2025-03-16 01:09:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 4.6104
[2025-03-16 01:12:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 1.1892
[2025-03-16 01:16:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2046
[2025-03-16 01:19:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2721
[2025-03-16 01:22:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [21/50] - Train Loss: 0.8578
[2025-03-16 01:22:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 59.47%
[2025-03-16 01:22:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1077
[2025-03-16 01:25:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0755
[2025-03-16 01:28:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1218
[2025-03-16 01:32:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0899
[2025-03-16 01:35:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1482
[2025-03-16 01:38:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1186
[2025-03-16 01:42:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1130
[2025-03-16 01:45:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0616
[2025-03-16 01:47:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [22/50] - Train Loss: 0.1195
[2025-03-16 01:48:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 56.40%
[2025-03-16 01:48:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0525
[2025-03-16 01:51:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0453
[2025-03-16 01:54:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0429
[2025-03-16 01:58:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1074
[2025-03-16 02:01:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1400
[2025-03-16 02:04:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0663
[2025-03-16 02:08:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0730
[2025-03-16 02:11:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1378
[2025-03-16 02:13:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [23/50] - Train Loss: 0.1022
[2025-03-16 02:14:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 54.43%
[2025-03-16 02:14:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1143
[2025-03-16 02:17:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1057
[2025-03-16 02:20:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2119
[2025-03-16 02:24:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1431
[2025-03-16 02:27:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1316
[2025-03-16 02:30:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1703
[2025-03-16 02:33:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1382
[2025-03-16 02:37:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 3.5535
[2025-03-16 02:39:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [24/50] - Train Loss: 0.3719
[2025-03-16 02:40:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 58.34%
[2025-03-16 02:40:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2414
[2025-03-16 02:43:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3029
[2025-03-16 02:46:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1406
[2025-03-16 02:50:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.3388
[2025-03-16 02:53:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1543
[2025-03-16 02:56:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1855
[2025-03-16 02:59:53] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2913
[2025-03-16 03:03:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1922
[2025-03-16 03:05:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [25/50] - Train Loss: 0.2606
[2025-03-16 03:06:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 62.62%
[2025-03-16 03:06:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1161
[2025-03-16 03:09:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0665
[2025-03-16 03:12:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0744
[2025-03-16 03:15:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0594
[2025-03-16 03:19:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1683
[2025-03-16 03:22:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0811
[2025-03-16 03:25:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1289
[2025-03-16 03:29:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1488
[2025-03-16 03:31:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [26/50] - Train Loss: 0.1186
[2025-03-16 03:32:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 57.48%
[2025-03-16 03:32:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1247
[2025-03-16 03:35:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0447
[2025-03-16 03:38:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2501
[2025-03-16 03:41:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1244
[2025-03-16 03:45:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1160
[2025-03-16 03:48:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1252
[2025-03-16 03:51:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1364
[2025-03-16 03:55:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1483
[2025-03-16 03:57:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [27/50] - Train Loss: 0.1842
[2025-03-16 03:57:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 60.40%
[2025-03-16 03:58:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0934
[2025-03-16 04:01:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1203
[2025-03-16 04:04:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1097
[2025-03-16 04:07:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0760
[2025-03-16 04:11:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.3389
[2025-03-16 04:14:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.3710
[2025-03-16 04:17:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2034
[2025-03-16 04:20:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1690
[2025-03-16 04:23:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [28/50] - Train Loss: 0.5063
[2025-03-16 04:23:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 62.35%
[2025-03-16 04:23:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1021
[2025-03-16 04:27:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0313
[2025-03-16 04:30:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0858
[2025-03-16 04:33:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0461
[2025-03-16 04:37:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1506
[2025-03-16 04:40:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0832
[2025-03-16 04:43:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 4.4619
[2025-03-16 04:46:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 1.4671
[2025-03-16 04:49:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [29/50] - Train Loss: 0.7198
[2025-03-16 04:49:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 59.96%
[2025-03-16 04:49:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.2690
[2025-03-16 04:53:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.3519
[2025-03-16 04:56:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2354
[2025-03-16 04:59:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1930
[2025-03-16 05:02:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1415
[2025-03-16 05:06:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1727
[2025-03-16 05:09:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0884
[2025-03-16 05:12:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1351
[2025-03-16 05:15:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [30/50] - Train Loss: 0.2182
[2025-03-16 05:15:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 59.79%
[2025-03-16 05:15:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0751
[2025-03-16 05:19:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0414
[2025-03-16 05:22:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0859
[2025-03-16 05:25:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0700
[2025-03-16 05:28:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1524
[2025-03-16 05:32:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0694
[2025-03-16 05:35:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2352
[2025-03-16 05:38:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1715
[2025-03-16 05:41:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [31/50] - Train Loss: 0.1030
[2025-03-16 05:41:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 59.36%
[2025-03-16 05:41:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0379
[2025-03-16 05:44:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1468
[2025-03-16 05:48:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0427
[2025-03-16 05:51:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0949
[2025-03-16 05:54:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1065
[2025-03-16 05:57:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0859
[2025-03-16 06:01:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0648
[2025-03-16 06:04:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0512
[2025-03-16 06:07:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [32/50] - Train Loss: 0.0956
[2025-03-16 06:07:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 55.08%
[2025-03-16 06:07:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0846
[2025-03-16 06:10:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0768
[2025-03-16 06:14:04] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0793
[2025-03-16 06:17:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0606
[2025-03-16 06:20:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1034
[2025-03-16 06:23:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.9817
[2025-03-16 06:27:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2721
[2025-03-16 06:30:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1673
[2025-03-16 06:33:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [33/50] - Train Loss: 0.3238
[2025-03-16 06:33:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 61.69%
[2025-03-16 06:33:25] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0845
[2025-03-16 06:36:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0634
[2025-03-16 06:39:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0791
[2025-03-16 06:43:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0395
[2025-03-16 06:46:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0720
[2025-03-16 06:49:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0940
[2025-03-16 06:53:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1225
[2025-03-16 06:56:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1649
[2025-03-16 06:58:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [34/50] - Train Loss: 0.1302
[2025-03-16 06:59:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 59.08%
[2025-03-16 06:59:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1367
[2025-03-16 07:02:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1584
[2025-03-16 07:05:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1666
[2025-03-16 07:09:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0719
[2025-03-16 07:12:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0521
[2025-03-16 07:15:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0786
[2025-03-16 07:18:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1534
[2025-03-16 07:22:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1650
[2025-03-16 07:24:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [35/50] - Train Loss: 0.1166
[2025-03-16 07:25:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 51.16%
[2025-03-16 07:25:11] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1006
[2025-03-16 07:28:27] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1062
[2025-03-16 07:31:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1490
[2025-03-16 07:35:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1259
[2025-03-16 07:38:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1415
[2025-03-16 07:41:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1939
[2025-03-16 07:44:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1488
[2025-03-16 07:48:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1794
[2025-03-16 07:50:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [36/50] - Train Loss: 0.1119
[2025-03-16 07:51:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 51.48%
[2025-03-16 07:51:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0742
[2025-03-16 07:54:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0571
[2025-03-16 07:57:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1421
[2025-03-16 08:00:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0506
[2025-03-16 08:04:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1331
[2025-03-16 08:07:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1014
[2025-03-16 08:10:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1501
[2025-03-16 08:14:03] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1203
[2025-03-16 08:16:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [37/50] - Train Loss: 0.1189
[2025-03-16 08:17:00] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 47.27%
[2025-03-16 08:17:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1193
[2025-03-16 08:20:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1766
[2025-03-16 08:23:36] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1810
[2025-03-16 08:26:52] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1809
[2025-03-16 08:30:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0688
[2025-03-16 08:33:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1121
[2025-03-16 08:36:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2937
[2025-03-16 08:39:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.4414
[2025-03-16 08:42:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [38/50] - Train Loss: 0.2879
[2025-03-16 08:42:55] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 55.63%
[2025-03-16 08:42:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1963
[2025-03-16 08:46:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1914
[2025-03-16 08:49:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0633
[2025-03-16 08:52:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0982
[2025-03-16 08:56:01] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.2473
[2025-03-16 08:59:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1162
[2025-03-16 09:02:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0699
[2025-03-16 09:05:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1657
[2025-03-16 09:08:28] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [39/50] - Train Loss: 0.1317
[2025-03-16 09:08:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 56.11%
[2025-03-16 09:08:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1261
[2025-03-16 09:12:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0809
[2025-03-16 09:15:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1312
[2025-03-16 09:18:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0361
[2025-03-16 09:21:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0998
[2025-03-16 09:25:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1175
[2025-03-16 09:28:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1964
[2025-03-16 09:31:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1358
[2025-03-16 09:34:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [40/50] - Train Loss: 0.1150
[2025-03-16 09:34:43] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 53.30%
[2025-03-16 09:34:45] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0529
[2025-03-16 09:38:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1585
[2025-03-16 09:41:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0356
[2025-03-16 09:44:35] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0576
[2025-03-16 09:47:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1209
[2025-03-16 09:51:08] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1372
[2025-03-16 09:54:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1253
[2025-03-16 09:57:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0555
[2025-03-16 10:00:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [41/50] - Train Loss: 0.0971
[2025-03-16 10:00:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 49.54%
[2025-03-16 10:00:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0900
[2025-03-16 10:03:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0484
[2025-03-16 10:07:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1014
[2025-03-16 10:10:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0598
[2025-03-16 10:13:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0861
[2025-03-16 10:17:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0770
[2025-03-16 10:20:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.0817
[2025-03-16 10:23:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0633
[2025-03-16 10:26:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [42/50] - Train Loss: 0.0974
[2025-03-16 10:26:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 42.15%
[2025-03-16 10:26:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1393
[2025-03-16 10:29:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0597
[2025-03-16 10:33:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0922
[2025-03-16 10:36:31] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1229
[2025-03-16 10:39:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.3015
[2025-03-16 10:43:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0439
[2025-03-16 10:46:21] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1111
[2025-03-16 10:49:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 4.5780
[2025-03-16 10:52:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [43/50] - Train Loss: 0.7628
[2025-03-16 10:52:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 3.78%
[2025-03-16 10:52:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 4.1708
[2025-03-16 10:55:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 3.4880
[2025-03-16 10:59:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.5042
[2025-03-16 11:02:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.2277
[2025-03-16 11:05:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0950
[2025-03-16 11:09:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.2445
[2025-03-16 11:12:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1415
[2025-03-16 11:15:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.4378
[2025-03-16 11:18:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [44/50] - Train Loss: 0.9470
[2025-03-16 11:18:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 58.47%
[2025-03-16 11:18:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1403
[2025-03-16 11:21:56] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0518
[2025-03-16 11:25:13] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1030
[2025-03-16 11:28:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0515
[2025-03-16 11:31:47] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 4.6180
[2025-03-16 11:35:05] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 3.3640
[2025-03-16 11:38:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.8935
[2025-03-16 11:41:39] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.2920
[2025-03-16 11:44:18] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [45/50] - Train Loss: 1.1593
[2025-03-16 11:44:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 59.98%
[2025-03-16 11:44:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1751
[2025-03-16 11:47:57] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.2089
[2025-03-16 11:51:14] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2350
[2025-03-16 11:54:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1236
[2025-03-16 11:57:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1677
[2025-03-16 12:01:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1512
[2025-03-16 12:04:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.2217
[2025-03-16 12:07:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.3119
[2025-03-16 12:10:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [46/50] - Train Loss: 0.2256
[2025-03-16 12:10:38] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 49.97%
[2025-03-16 12:10:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1393
[2025-03-16 12:13:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.6112
[2025-03-16 12:17:16] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2547
[2025-03-16 12:20:33] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1225
[2025-03-16 12:23:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.2147
[2025-03-16 12:27:07] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1100
[2025-03-16 12:30:24] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 3.8207
[2025-03-16 12:33:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.8647
[2025-03-16 12:36:20] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [47/50] - Train Loss: 0.8319
[2025-03-16 12:36:40] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 62.21%
[2025-03-16 12:36:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1404
[2025-03-16 12:39:59] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1474
[2025-03-16 12:43:17] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.1339
[2025-03-16 12:46:34] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.3731
[2025-03-16 12:49:51] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.1840
[2025-03-16 12:53:09] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0940
[2025-03-16 12:56:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1468
[2025-03-16 12:59:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1404
[2025-03-16 13:02:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [48/50] - Train Loss: 0.2214
[2025-03-16 13:02:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 63.57%
[2025-03-16 13:02:44] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.0770
[2025-03-16 13:06:02] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.0714
[2025-03-16 13:09:19] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.0659
[2025-03-16 13:12:37] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.0615
[2025-03-16 13:15:54] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0641
[2025-03-16 13:19:12] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.0560
[2025-03-16 13:22:30] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1403
[2025-03-16 13:25:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.0714
[2025-03-16 13:28:26] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [49/50] - Train Loss: 0.1541
[2025-03-16 13:28:46] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 57.91%
[2025-03-16 13:28:48] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 0, Loss: 0.1400
[2025-03-16 13:32:06] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 100, Loss: 0.1098
[2025-03-16 13:35:23] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 200, Loss: 0.2924
[2025-03-16 13:38:41] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 300, Loss: 0.1162
[2025-03-16 13:41:58] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 400, Loss: 0.0768
[2025-03-16 13:45:15] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 500, Loss: 0.1333
[2025-03-16 13:48:32] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 600, Loss: 0.1685
[2025-03-16 13:51:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Batch 700, Loss: 0.1414
[2025-03-16 13:54:29] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Epoch [50/50] - Train Loss: 0.2218
[2025-03-16 13:54:49] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Test Accuracy: 63.22%
[2025-03-16 13:54:50] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Model saved at: ./models/CIFAR100_AIR_None_task1.pt
[2025-03-16 13:55:10] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Clean Accuracy after Task 2, Attack=None: 63.22%
[2025-03-16 13:56:22] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Robust Accuracy on FGSM after Task 2: 20.87%
[2025-03-16 13:56:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Robust Accuracy on None after Task 2: 63.22%
[2025-03-16 13:56:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] === All tasks completed! ===
[2025-03-16 13:56:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] === Final Results ===
[2025-03-16 13:56:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] []
[2025-03-16 13:56:42] [CIFAR100-AIR-('FGSM', 'None')] [INFO] Done!
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