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outputs/logs/hyperparameter_tuning_20250424_233330.log ADDED
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1
+ 2025-04-24 23:33:30,559 - INFO - Hyperparameter tuning logs will be saved to: /Users/neecat/Desktop/Projects/trash-classification/outputs/logs/hyperparameter_tuning_20250424_233330.log
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+ 2025-04-24 23:33:30,559 - INFO - Using device: mps
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+ 2025-04-24 23:33:30,559 - INFO - Loading datasets...
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+ 2025-04-24 23:33:30,559 - INFO - Loading datasets from: /Users/neecat/Desktop/Projects/trash-classification/data
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+ 2025-04-24 23:33:30,559 - INFO - Train directory: /Users/neecat/Desktop/Projects/trash-classification/data/train
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+ 2025-04-24 23:33:30,559 - INFO - Validation directory: /Users/neecat/Desktop/Projects/trash-classification/data/val
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+ 2025-04-24 23:33:30,559 - INFO - Test directory: /Users/neecat/Desktop/Projects/trash-classification/data/test
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+ 2025-04-24 23:33:30,583 - INFO - Train dataset size: 1766
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+ 2025-04-24 23:33:30,583 - INFO - Validation dataset size: 378
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+ 2025-04-24 23:33:30,583 - INFO - Test dataset size: 383
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+ 2025-04-24 23:33:30,583 - INFO - Classes: ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']
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+ 2025-04-24 23:33:30,583 - INFO - Starting hyperparameter search...
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+ 2025-04-24 23:33:30,583 - INFO - Number of trials: 10
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+ 2025-04-24 23:33:30,583 - INFO - Learning rates to try: [1e-05, 0.0001, 0.0005, 0.001]
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+ 2025-04-24 23:33:30,583 - INFO - Weight decays to try: [1e-05, 0.0001, 0.001]
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+ 2025-04-24 23:33:30,583 - INFO -
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+ Trial 1/10
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+ 2025-04-24 23:33:30,583 - INFO - Testing lr=0.0005, weight_decay=0.001
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+ 2025-04-24 23:33:30,812 - INFO - Starting validation training with lr=0.0005, weight_decay=0.001
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+ 2025-04-24 23:33:33,746 - INFO - Epoch 1/5, Batch 0/56
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+ 2025-04-24 23:33:39,881 - INFO - Epoch 1/5, Batch 20/56
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+ 2025-04-24 23:33:44,080 - INFO - Epoch 1/5, Batch 40/56
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+ 2025-04-24 23:34:11,709 - INFO - Epoch 1/5: Train Loss=0.8108, Train Acc=0.7072, Val Loss=0.6350, Val Acc=0.8111
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+ 2025-04-24 23:34:11,711 - INFO - New best validation accuracy: 0.8111
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+ 2025-04-24 23:34:15,958 - INFO - Epoch 2/5, Batch 0/56
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+ 2025-04-24 23:34:21,349 - INFO - Epoch 2/5, Batch 20/56
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+ 2025-04-24 23:34:25,919 - INFO - Epoch 2/5, Batch 40/56
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+ 2025-04-24 23:34:52,434 - INFO - Epoch 2/5: Train Loss=0.4736, Train Acc=0.8350, Val Loss=0.5783, Val Acc=0.8121
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+ 2025-04-24 23:34:52,435 - INFO - New best validation accuracy: 0.8121
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+ 2025-04-24 23:34:56,004 - INFO - Epoch 3/5, Batch 0/56
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+ 2025-04-24 23:35:01,463 - INFO - Epoch 3/5, Batch 20/56
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+ 2025-04-24 23:35:05,992 - INFO - Epoch 3/5, Batch 40/56
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+ 2025-04-24 23:35:32,673 - INFO - Epoch 3/5: Train Loss=0.3780, Train Acc=0.8590, Val Loss=0.5501, Val Acc=0.8249
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+ 2025-04-24 23:35:32,675 - INFO - New best validation accuracy: 0.8249
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+ 2025-04-24 23:35:35,916 - INFO - Epoch 4/5, Batch 0/56
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+ 2025-04-24 23:35:40,863 - INFO - Epoch 4/5, Batch 20/56
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+ 2025-04-24 23:35:45,065 - INFO - Epoch 4/5, Batch 40/56
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+ 2025-04-24 23:36:11,019 - INFO - Epoch 4/5: Train Loss=0.3307, Train Acc=0.8880, Val Loss=0.5364, Val Acc=0.8225
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+ 2025-04-24 23:36:14,183 - INFO - Epoch 5/5, Batch 0/56
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+ 2025-04-24 23:36:19,212 - INFO - Epoch 5/5, Batch 20/56
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+ 2025-04-24 23:36:23,429 - INFO - Epoch 5/5, Batch 40/56
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+ 2025-04-24 23:36:49,636 - INFO - Epoch 5/5: Train Loss=0.3178, Train Acc=0.8968, Val Loss=0.4402, Val Acc=0.8446
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+ 2025-04-24 23:36:49,636 - INFO - New best validation accuracy: 0.8446
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+ 2025-04-24 23:36:49,637 - INFO - Trial 1 completed in 199.05s
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+ 2025-04-24 23:36:49,637 - INFO - Validation accuracy: 0.8446
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+ 2025-04-24 23:36:49,637 - INFO - New best config found!
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+ 2025-04-24 23:36:49,637 - INFO -
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+ Trial 2/10
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+ 2025-04-24 23:36:49,637 - INFO - Testing lr=1e-05, weight_decay=1e-05
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+ 2025-04-24 23:36:49,779 - INFO - Starting validation training with lr=1e-05, weight_decay=1e-05
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+ 2025-04-24 23:36:53,086 - INFO - Epoch 1/5, Batch 0/56
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+ 2025-04-24 23:36:58,049 - INFO - Epoch 1/5, Batch 20/56
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+ 2025-04-24 23:37:02,267 - INFO - Epoch 1/5, Batch 40/56
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+ 2025-04-24 23:37:29,063 - INFO - Epoch 1/5: Train Loss=1.7451, Train Acc=0.2517, Val Loss=1.5203, Val Acc=0.4407
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+ 2025-04-24 23:37:29,065 - INFO - New best validation accuracy: 0.4407
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+ 2025-04-24 23:37:32,811 - INFO - Epoch 2/5, Batch 0/56
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+ 2025-04-24 23:37:38,250 - INFO - Epoch 2/5, Batch 20/56
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+ 2025-04-24 23:37:42,806 - INFO - Epoch 2/5, Batch 40/56
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+ 2025-04-24 23:38:10,696 - INFO - Epoch 2/5: Train Loss=1.4002, Train Acc=0.5320, Val Loss=1.2148, Val Acc=0.6789
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+ 2025-04-24 23:38:10,696 - INFO - New best validation accuracy: 0.6789
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+ 2025-04-24 23:38:14,290 - INFO - Epoch 3/5, Batch 0/56
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+ 2025-04-24 23:38:21,123 - INFO - Epoch 3/5, Batch 20/56
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+ 2025-04-24 23:38:25,352 - INFO - Epoch 3/5, Batch 40/56
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+ 2025-04-24 23:38:52,663 - INFO - Epoch 3/5: Train Loss=1.1508, Train Acc=0.6670, Val Loss=0.9843, Val Acc=0.6997
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+ 2025-04-24 23:38:52,664 - INFO - New best validation accuracy: 0.6997
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+ 2025-04-24 23:38:56,144 - INFO - Epoch 4/5, Batch 0/56
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+ 2025-04-24 23:39:01,428 - INFO - Epoch 4/5, Batch 20/56
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+ 2025-04-24 23:39:06,397 - INFO - Epoch 4/5, Batch 40/56
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+ 2025-04-24 23:39:32,816 - INFO - Epoch 4/5: Train Loss=0.9643, Train Acc=0.7065, Val Loss=0.8555, Val Acc=0.7342
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+ 2025-04-24 23:39:32,818 - INFO - New best validation accuracy: 0.7342
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+ 2025-04-24 23:39:36,192 - INFO - Epoch 5/5, Batch 0/56
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+ 2025-04-24 23:39:41,339 - INFO - Epoch 5/5, Batch 20/56
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+ 2025-04-24 23:39:45,545 - INFO - Epoch 5/5, Batch 40/56
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+ 2025-04-24 23:40:13,389 - INFO - Epoch 5/5: Train Loss=0.8275, Train Acc=0.7481, Val Loss=0.7659, Val Acc=0.7472
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+ 2025-04-24 23:40:13,390 - INFO - New best validation accuracy: 0.7472
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+ 2025-04-24 23:40:13,394 - INFO - Trial 2 completed in 203.76s
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+ 2025-04-24 23:40:13,394 - INFO - Validation accuracy: 0.7472
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+ 2025-04-24 23:40:13,395 - INFO -
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+ Trial 3/10
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+ 2025-04-24 23:40:13,395 - INFO - Testing lr=0.0001, weight_decay=0.001
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+ 2025-04-24 23:40:13,601 - INFO - Starting validation training with lr=0.0001, weight_decay=0.001
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+ 2025-04-24 23:40:17,049 - INFO - Epoch 1/5, Batch 0/56
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+ 2025-04-24 23:40:22,291 - INFO - Epoch 1/5, Batch 20/56
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+ 2025-04-24 23:40:26,902 - INFO - Epoch 1/5, Batch 40/56
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+ 2025-04-24 23:40:54,227 - INFO - Epoch 1/5: Train Loss=0.9689, Train Acc=0.6484, Val Loss=0.5932, Val Acc=0.7863
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+ 2025-04-24 23:40:54,227 - INFO - New best validation accuracy: 0.7863
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+ 2025-04-24 23:40:57,786 - INFO - Epoch 2/5, Batch 0/56
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+ 2025-04-24 23:41:04,115 - INFO - Epoch 2/5, Batch 20/56
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+ 2025-04-24 23:41:10,341 - INFO - Epoch 2/5, Batch 40/56
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+ 2025-04-24 23:41:39,728 - INFO - Epoch 2/5: Train Loss=0.4835, Train Acc=0.8294, Val Loss=0.4629, Val Acc=0.8438
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+ 2025-04-24 23:41:39,728 - INFO - New best validation accuracy: 0.8438
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+ 2025-04-24 23:41:43,279 - INFO - Epoch 3/5, Batch 0/56
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+ 2025-04-24 23:41:48,471 - INFO - Epoch 3/5, Batch 20/56
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+ 2025-04-24 23:41:53,146 - INFO - Epoch 3/5, Batch 40/56
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+ 2025-04-24 23:42:22,299 - INFO - Epoch 3/5: Train Loss=0.3223, Train Acc=0.9033, Val Loss=0.4220, Val Acc=0.8423
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+ 2025-04-24 23:42:25,592 - INFO - Epoch 4/5, Batch 0/56
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+ 2025-04-24 23:42:30,930 - INFO - Epoch 4/5, Batch 20/56
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+ 2025-04-24 23:42:35,597 - INFO - Epoch 4/5, Batch 40/56
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+ 2025-04-24 23:43:03,337 - INFO - Epoch 4/5: Train Loss=0.2424, Train Acc=0.9245, Val Loss=0.4076, Val Acc=0.8423
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+ 2025-04-24 23:43:06,879 - INFO - Epoch 5/5, Batch 0/56
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+ 2025-04-24 23:43:12,166 - INFO - Epoch 5/5, Batch 20/56
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+ 2025-04-24 23:43:16,876 - INFO - Epoch 5/5, Batch 40/56
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+ 2025-04-24 23:43:44,205 - INFO - Epoch 5/5: Train Loss=0.2004, Train Acc=0.9308, Val Loss=0.3982, Val Acc=0.8638
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+ 2025-04-24 23:43:44,206 - INFO - New best validation accuracy: 0.8638
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+ 2025-04-24 23:43:44,210 - INFO - Trial 3 completed in 210.82s
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+ 2025-04-24 23:43:44,211 - INFO - Validation accuracy: 0.8638
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+ 2025-04-24 23:43:44,211 - INFO - New best config found!
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+ 2025-04-24 23:43:44,211 - INFO -
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+ Trial 4/10
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+ 2025-04-24 23:43:44,211 - INFO - Testing lr=0.0001, weight_decay=0.0001
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+ 2025-04-24 23:43:44,409 - INFO - Starting validation training with lr=0.0001, weight_decay=0.0001
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+ 2025-04-24 23:43:47,876 - INFO - Epoch 1/5, Batch 0/56
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+ 2025-04-24 23:43:53,291 - INFO - Epoch 1/5, Batch 20/56
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+ 2025-04-24 23:43:57,914 - INFO - Epoch 1/5, Batch 40/56
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+ 2025-04-24 23:44:24,659 - INFO - Epoch 1/5: Train Loss=0.9652, Train Acc=0.6693, Val Loss=0.5918, Val Acc=0.7921
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+ 2025-04-24 23:44:24,662 - INFO - New best validation accuracy: 0.7921
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+ 2025-04-24 23:44:28,131 - INFO - Epoch 2/5, Batch 0/56
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+ 2025-04-24 23:44:33,623 - INFO - Epoch 2/5, Batch 20/56
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+ 2025-04-24 23:44:38,231 - INFO - Epoch 2/5, Batch 40/56
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+ 2025-04-24 23:45:05,398 - INFO - Epoch 2/5: Train Loss=0.4619, Train Acc=0.8411, Val Loss=0.4389, Val Acc=0.8598
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+ 2025-04-24 23:45:05,401 - INFO - New best validation accuracy: 0.8598
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+ 2025-04-24 23:45:08,929 - INFO - Epoch 3/5, Batch 0/56
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+ 2025-04-24 23:45:14,679 - INFO - Epoch 3/5, Batch 20/56
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+ 2025-04-24 23:45:19,318 - INFO - Epoch 3/5, Batch 40/56
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+ 2025-04-24 23:45:46,722 - INFO - Epoch 3/5: Train Loss=0.3189, Train Acc=0.8904, Val Loss=0.3714, Val Acc=0.8728
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+ 2025-04-24 23:45:46,723 - INFO - New best validation accuracy: 0.8728
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+ 2025-04-24 23:45:49,980 - INFO - Epoch 4/5, Batch 0/56
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+ 2025-04-24 23:45:55,388 - INFO - Epoch 4/5, Batch 20/56
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+ 2025-04-24 23:46:00,036 - INFO - Epoch 4/5, Batch 40/56
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+ 2025-04-24 23:46:27,464 - INFO - Epoch 4/5: Train Loss=0.2386, Train Acc=0.9208, Val Loss=0.3581, Val Acc=0.8638
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+ 2025-04-24 23:46:30,995 - INFO - Epoch 5/5, Batch 0/56
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+ 2025-04-24 23:46:36,428 - INFO - Epoch 5/5, Batch 20/56
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+ 2025-04-24 23:46:41,031 - INFO - Epoch 5/5, Batch 40/56
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+ 2025-04-24 23:47:07,340 - INFO - Epoch 5/5: Train Loss=0.1594, Train Acc=0.9542, Val Loss=0.3120, Val Acc=0.8954
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+ 2025-04-24 23:47:07,340 - INFO - New best validation accuracy: 0.8954
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+ 2025-04-24 23:47:07,341 - INFO - Trial 4 completed in 203.13s
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+ 2025-04-24 23:47:07,341 - INFO - Validation accuracy: 0.8954
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+ 2025-04-24 23:47:07,342 - INFO - New best config found!
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+ 2025-04-24 23:47:07,342 - INFO -
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+ Trial 5/10
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+ 2025-04-24 23:47:07,342 - INFO - Testing lr=1e-05, weight_decay=0.0001
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+ 2025-04-24 23:47:07,510 - INFO - Starting validation training with lr=1e-05, weight_decay=0.0001
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+ 2025-04-24 23:47:11,012 - INFO - Epoch 1/5, Batch 0/56
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+ 2025-04-24 23:47:16,392 - INFO - Epoch 1/5, Batch 20/56
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+ 2025-04-24 23:47:21,023 - INFO - Epoch 1/5, Batch 40/56
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+ 2025-04-24 23:47:48,143 - INFO - Epoch 1/5: Train Loss=1.7077, Train Acc=0.2883, Val Loss=1.4746, Val Acc=0.4946
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+ 2025-04-24 23:47:48,144 - INFO - New best validation accuracy: 0.4946
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+ 2025-04-24 23:47:51,697 - INFO - Epoch 2/5, Batch 0/56
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+ 2025-04-24 23:47:57,188 - INFO - Epoch 2/5, Batch 20/56
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+ 2025-04-24 23:48:01,792 - INFO - Epoch 2/5, Batch 40/56
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+ 2025-04-24 23:48:28,898 - INFO - Epoch 2/5: Train Loss=1.3730, Train Acc=0.5387, Val Loss=1.1978, Val Acc=0.6404
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+ 2025-04-24 23:48:28,901 - INFO - New best validation accuracy: 0.6404
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+ 2025-04-24 23:48:32,511 - INFO - Epoch 3/5, Batch 0/56
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+ 2025-04-24 23:48:37,966 - INFO - Epoch 3/5, Batch 20/56
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+ 2025-04-24 23:48:42,589 - INFO - Epoch 3/5, Batch 40/56
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+ 2025-04-24 23:49:08,978 - INFO - Epoch 3/5: Train Loss=1.1176, Train Acc=0.6674, Val Loss=0.9873, Val Acc=0.7107
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+ 2025-04-24 23:49:08,978 - INFO - New best validation accuracy: 0.7107
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+ 2025-04-24 23:49:12,265 - INFO - Epoch 4/5, Batch 0/56
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+ 2025-04-24 23:49:17,556 - INFO - Epoch 4/5, Batch 20/56
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+ 2025-04-24 23:49:22,167 - INFO - Epoch 4/5, Batch 40/56
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+ 2025-04-24 23:49:48,929 - INFO - Epoch 4/5: Train Loss=0.9563, Train Acc=0.7124, Val Loss=0.8470, Val Acc=0.7518
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+ 2025-04-24 23:49:48,932 - INFO - New best validation accuracy: 0.7518
163
+ 2025-04-24 23:49:52,387 - INFO - Epoch 5/5, Batch 0/56
164
+ 2025-04-24 23:49:57,812 - INFO - Epoch 5/5, Batch 20/56
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+ 2025-04-24 23:50:02,460 - INFO - Epoch 5/5, Batch 40/56
166
+ 2025-04-24 23:50:29,731 - INFO - Epoch 5/5: Train Loss=0.8275, Train Acc=0.7394, Val Loss=0.7752, Val Acc=0.7602
167
+ 2025-04-24 23:50:29,732 - INFO - New best validation accuracy: 0.7602
168
+ 2025-04-24 23:50:29,734 - INFO - Trial 5 completed in 202.39s
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+ 2025-04-24 23:50:29,735 - INFO - Validation accuracy: 0.7602
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+ 2025-04-24 23:50:29,735 - INFO -
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+ Trial 6/10
172
+ 2025-04-24 23:50:29,735 - INFO - Testing lr=1e-05, weight_decay=0.001
173
+ 2025-04-24 23:50:29,909 - INFO - Starting validation training with lr=1e-05, weight_decay=0.001
174
+ 2025-04-24 23:50:33,427 - INFO - Epoch 1/5, Batch 0/56
175
+ 2025-04-24 23:50:38,891 - INFO - Epoch 1/5, Batch 20/56
176
+ 2025-04-24 23:50:43,512 - INFO - Epoch 1/5, Batch 40/56
177
+ 2025-04-24 23:51:09,913 - INFO - Epoch 1/5: Train Loss=1.6747, Train Acc=0.3065, Val Loss=1.4594, Val Acc=0.5401
178
+ 2025-04-24 23:51:09,914 - INFO - New best validation accuracy: 0.5401
179
+ 2025-04-24 23:51:13,502 - INFO - Epoch 2/5, Batch 0/56
180
+ 2025-04-24 23:51:18,907 - INFO - Epoch 2/5, Batch 20/56
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+ 2025-04-24 23:51:23,541 - INFO - Epoch 2/5, Batch 40/56
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+ 2025-04-24 23:51:50,733 - INFO - Epoch 2/5: Train Loss=1.3444, Train Acc=0.5683, Val Loss=1.1664, Val Acc=0.6775
183
+ 2025-04-24 23:51:50,734 - INFO - New best validation accuracy: 0.6775
184
+ 2025-04-24 23:51:54,234 - INFO - Epoch 3/5, Batch 0/56
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+ 2025-04-24 23:51:59,641 - INFO - Epoch 3/5, Batch 20/56
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+ 2025-04-24 23:52:04,281 - INFO - Epoch 3/5, Batch 40/56
187
+ 2025-04-24 23:52:31,578 - INFO - Epoch 3/5: Train Loss=1.1177, Train Acc=0.6419, Val Loss=0.9828, Val Acc=0.7165
188
+ 2025-04-24 23:52:31,581 - INFO - New best validation accuracy: 0.7165
189
+ 2025-04-24 23:52:35,185 - INFO - Epoch 4/5, Batch 0/56
190
+ 2025-04-24 23:52:40,634 - INFO - Epoch 4/5, Batch 20/56
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+ 2025-04-24 23:52:45,295 - INFO - Epoch 4/5, Batch 40/56
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+ 2025-04-24 23:53:13,154 - INFO - Epoch 4/5: Train Loss=0.9381, Train Acc=0.7072, Val Loss=0.8580, Val Acc=0.7348
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+ 2025-04-24 23:53:13,156 - INFO - New best validation accuracy: 0.7348
194
+ 2025-04-24 23:53:16,711 - INFO - Epoch 5/5, Batch 0/56
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+ 2025-04-24 23:53:22,214 - INFO - Epoch 5/5, Batch 20/56
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+ 2025-04-24 23:53:26,974 - INFO - Epoch 5/5, Batch 40/56
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+ 2025-04-24 23:53:54,532 - INFO - Epoch 5/5: Train Loss=0.8276, Train Acc=0.7429, Val Loss=0.7652, Val Acc=0.7634
198
+ 2025-04-24 23:53:54,533 - INFO - New best validation accuracy: 0.7634
199
+ 2025-04-24 23:53:54,535 - INFO - Trial 6 completed in 204.80s
200
+ 2025-04-24 23:53:54,535 - INFO - Validation accuracy: 0.7634
201
+ 2025-04-24 23:53:54,535 - INFO -
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+ Trial 7/10
203
+ 2025-04-24 23:53:54,535 - INFO - Testing lr=1e-05, weight_decay=0.001
204
+ 2025-04-24 23:53:54,694 - INFO - Starting validation training with lr=1e-05, weight_decay=0.001
205
+ 2025-04-24 23:53:58,563 - INFO - Epoch 1/5, Batch 0/56
206
+ 2025-04-24 23:54:05,200 - INFO - Epoch 1/5, Batch 20/56
207
+ 2025-04-24 23:54:09,494 - INFO - Epoch 1/5, Batch 40/56
208
+ 2025-04-24 23:54:37,278 - INFO - Epoch 1/5: Train Loss=1.7215, Train Acc=0.2773, Val Loss=1.5210, Val Acc=0.4425
209
+ 2025-04-24 23:54:37,279 - INFO - New best validation accuracy: 0.4425
210
+ 2025-04-24 23:54:40,293 - INFO - Epoch 2/5, Batch 0/56
211
+ 2025-04-24 23:54:44,658 - INFO - Epoch 2/5, Batch 20/56
212
+ 2025-04-24 23:54:48,932 - INFO - Epoch 2/5, Batch 40/56
213
+ 2025-04-24 23:55:15,069 - INFO - Epoch 2/5: Train Loss=1.4122, Train Acc=0.5004, Val Loss=1.2437, Val Acc=0.6228
214
+ 2025-04-24 23:55:15,070 - INFO - New best validation accuracy: 0.6228
215
+ 2025-04-24 23:55:18,136 - INFO - Epoch 3/5, Batch 0/56
216
+ 2025-04-24 23:55:22,619 - INFO - Epoch 3/5, Batch 20/56
217
+ 2025-04-24 23:55:26,884 - INFO - Epoch 3/5, Batch 40/56
218
+ 2025-04-24 23:55:53,000 - INFO - Epoch 3/5: Train Loss=1.1631, Train Acc=0.6215, Val Loss=1.0567, Val Acc=0.6821
219
+ 2025-04-24 23:55:53,001 - INFO - New best validation accuracy: 0.6821
220
+ 2025-04-24 23:55:56,004 - INFO - Epoch 4/5, Batch 0/56
221
+ 2025-04-24 23:56:00,355 - INFO - Epoch 4/5, Batch 20/56
222
+ 2025-04-24 23:56:04,615 - INFO - Epoch 4/5, Batch 40/56
223
+ 2025-04-24 23:56:31,326 - INFO - Epoch 4/5: Train Loss=0.9963, Train Acc=0.6935, Val Loss=0.9123, Val Acc=0.7107
224
+ 2025-04-24 23:56:31,327 - INFO - New best validation accuracy: 0.7107
225
+ 2025-04-24 23:56:34,445 - INFO - Epoch 5/5, Batch 0/56
226
+ 2025-04-24 23:56:39,103 - INFO - Epoch 5/5, Batch 20/56
227
+ 2025-04-24 23:56:43,389 - INFO - Epoch 5/5, Batch 40/56
228
+ 2025-04-24 23:57:10,137 - INFO - Epoch 5/5: Train Loss=0.8489, Train Acc=0.7344, Val Loss=0.8142, Val Acc=0.7316
229
+ 2025-04-24 23:57:10,138 - INFO - New best validation accuracy: 0.7316
230
+ 2025-04-24 23:57:10,139 - INFO - Trial 7 completed in 195.60s
231
+ 2025-04-24 23:57:10,139 - INFO - Validation accuracy: 0.7316
232
+ 2025-04-24 23:57:10,139 - INFO -
233
+ Trial 8/10
234
+ 2025-04-24 23:57:10,139 - INFO - Testing lr=1e-05, weight_decay=0.001
235
+ 2025-04-24 23:57:10,276 - INFO - Starting validation training with lr=1e-05, weight_decay=0.001
236
+ 2025-04-24 23:57:13,869 - INFO - Epoch 1/5, Batch 0/56
237
+ 2025-04-24 23:57:19,127 - INFO - Epoch 1/5, Batch 20/56
238
+ 2025-04-24 23:57:23,415 - INFO - Epoch 1/5, Batch 40/56
239
+ 2025-04-24 23:57:49,889 - INFO - Epoch 1/5: Train Loss=1.8413, Train Acc=0.2212, Val Loss=1.5815, Val Acc=0.3938
240
+ 2025-04-24 23:57:49,891 - INFO - New best validation accuracy: 0.3938
241
+ 2025-04-24 23:57:52,957 - INFO - Epoch 2/5, Batch 0/56
242
+ 2025-04-24 23:57:57,677 - INFO - Epoch 2/5, Batch 20/56
243
+ 2025-04-24 23:58:01,979 - INFO - Epoch 2/5, Batch 40/56
244
+ 2025-04-24 23:58:29,330 - INFO - Epoch 2/5: Train Loss=1.4585, Train Acc=0.4632, Val Loss=1.2694, Val Acc=0.6280
245
+ 2025-04-24 23:58:29,331 - INFO - New best validation accuracy: 0.6280
246
+ 2025-04-24 23:58:33,275 - INFO - Epoch 3/5, Batch 0/56
247
+ 2025-04-24 23:58:39,229 - INFO - Epoch 3/5, Batch 20/56
248
+ 2025-04-24 23:58:43,837 - INFO - Epoch 3/5, Batch 40/56
249
+ 2025-04-24 23:59:10,455 - INFO - Epoch 3/5: Train Loss=1.2088, Train Acc=0.6023, Val Loss=1.0671, Val Acc=0.6789
250
+ 2025-04-24 23:59:10,456 - INFO - New best validation accuracy: 0.6789
251
+ 2025-04-24 23:59:13,891 - INFO - Epoch 4/5, Batch 0/56
252
+ 2025-04-24 23:59:18,946 - INFO - Epoch 4/5, Batch 20/56
253
+ 2025-04-24 23:59:23,438 - INFO - Epoch 4/5, Batch 40/56
254
+ 2025-04-24 23:59:50,783 - INFO - Epoch 4/5: Train Loss=1.0027, Train Acc=0.6925, Val Loss=0.9327, Val Acc=0.7133
255
+ 2025-04-24 23:59:50,784 - INFO - New best validation accuracy: 0.7133
256
+ 2025-04-24 23:59:54,501 - INFO - Epoch 5/5, Batch 0/56
257
+ 2025-04-24 23:59:59,782 - INFO - Epoch 5/5, Batch 20/56
258
+ 2025-04-25 00:00:05,200 - INFO - Epoch 5/5, Batch 40/56
259
+ 2025-04-25 00:00:32,430 - INFO - Epoch 5/5: Train Loss=0.8815, Train Acc=0.7266, Val Loss=0.8305, Val Acc=0.7420
260
+ 2025-04-25 00:00:32,432 - INFO - New best validation accuracy: 0.7420
261
+ 2025-04-25 00:00:32,433 - INFO - Trial 8 completed in 202.29s
262
+ 2025-04-25 00:00:32,433 - INFO - Validation accuracy: 0.7420
263
+ 2025-04-25 00:00:32,434 - INFO -
264
+ Trial 9/10
265
+ 2025-04-25 00:00:32,434 - INFO - Testing lr=0.001, weight_decay=1e-05
266
+ 2025-04-25 00:00:32,585 - INFO - Starting validation training with lr=0.001, weight_decay=1e-05
267
+ 2025-04-25 00:00:36,001 - INFO - Epoch 1/5, Batch 0/56
268
+ 2025-04-25 00:00:41,094 - INFO - Epoch 1/5, Batch 20/56
269
+ 2025-04-25 00:00:46,522 - INFO - Epoch 1/5, Batch 40/56
270
+ 2025-04-25 00:01:14,464 - INFO - Epoch 1/5: Train Loss=0.9683, Train Acc=0.6421, Val Loss=0.8650, Val Acc=0.6845
271
+ 2025-04-25 00:01:14,465 - INFO - New best validation accuracy: 0.6845
272
+ 2025-04-25 00:01:17,674 - INFO - Epoch 2/5, Batch 0/56
273
+ 2025-04-25 00:01:22,906 - INFO - Epoch 2/5, Batch 20/56
274
+ 2025-04-25 00:01:27,312 - INFO - Epoch 2/5, Batch 40/56
275
+ 2025-04-25 00:01:54,111 - INFO - Epoch 2/5: Train Loss=0.6713, Train Acc=0.7481, Val Loss=0.6097, Val Acc=0.7951
276
+ 2025-04-25 00:01:54,113 - INFO - New best validation accuracy: 0.7951
277
+ 2025-04-25 00:01:57,194 - INFO - Epoch 3/5, Batch 0/56
278
+ 2025-04-25 00:02:03,365 - INFO - Epoch 3/5, Batch 20/56
279
+ 2025-04-25 00:02:08,944 - INFO - Epoch 3/5, Batch 40/56
280
+ 2025-04-25 00:02:35,658 - INFO - Epoch 3/5: Train Loss=0.5348, Train Acc=0.8216, Val Loss=0.6318, Val Acc=0.7736
281
+ 2025-04-25 00:02:39,207 - INFO - Epoch 4/5, Batch 0/56
282
+ 2025-04-25 00:02:44,713 - INFO - Epoch 4/5, Batch 20/56
283
+ 2025-04-25 00:02:49,234 - INFO - Epoch 4/5, Batch 40/56
284
+ 2025-04-25 00:03:17,136 - INFO - Epoch 4/5: Train Loss=0.6184, Train Acc=0.7779, Val Loss=0.5942, Val Acc=0.7610
285
+ 2025-04-25 00:03:20,865 - INFO - Epoch 5/5, Batch 0/56
286
+ 2025-04-25 00:03:26,239 - INFO - Epoch 5/5, Batch 20/56
287
+ 2025-04-25 00:03:31,187 - INFO - Epoch 5/5, Batch 40/56
288
+ 2025-04-25 00:03:58,738 - INFO - Epoch 5/5: Train Loss=0.4562, Train Acc=0.8419, Val Loss=0.7906, Val Acc=0.7594
289
+ 2025-04-25 00:03:58,741 - INFO - Trial 9 completed in 206.31s
290
+ 2025-04-25 00:03:58,741 - INFO - Validation accuracy: 0.7951
291
+ 2025-04-25 00:03:58,742 - INFO -
292
+ Trial 10/10
293
+ 2025-04-25 00:03:58,742 - INFO - Testing lr=0.0005, weight_decay=0.001
294
+ 2025-04-25 00:03:58,953 - INFO - Starting validation training with lr=0.0005, weight_decay=0.001
295
+ 2025-04-25 00:04:02,459 - INFO - Epoch 1/5, Batch 0/56
296
+ 2025-04-25 00:04:07,821 - INFO - Epoch 1/5, Batch 20/56
297
+ 2025-04-25 00:04:12,425 - INFO - Epoch 1/5, Batch 40/56
298
+ 2025-04-25 00:04:40,040 - INFO - Epoch 1/5: Train Loss=0.7916, Train Acc=0.7076, Val Loss=0.8343, Val Acc=0.6967
299
+ 2025-04-25 00:04:40,041 - INFO - New best validation accuracy: 0.6967
300
+ 2025-04-25 00:04:44,380 - INFO - Epoch 2/5, Batch 0/56
301
+ 2025-04-25 00:04:50,653 - INFO - Epoch 2/5, Batch 20/56
302
+ 2025-04-25 00:04:55,600 - INFO - Epoch 2/5, Batch 40/56
303
+ 2025-04-25 00:05:23,580 - INFO - Epoch 2/5: Train Loss=0.5188, Train Acc=0.8157, Val Loss=0.4541, Val Acc=0.8383
304
+ 2025-04-25 00:05:23,581 - INFO - New best validation accuracy: 0.8383
305
+ 2025-04-25 00:05:27,478 - INFO - Epoch 3/5, Batch 0/56
306
+ 2025-04-25 00:05:33,391 - INFO - Epoch 3/5, Batch 20/56
307
+ 2025-04-25 00:05:38,233 - INFO - Epoch 3/5, Batch 40/56
308
+ 2025-04-25 00:06:06,465 - INFO - Epoch 3/5: Train Loss=0.3849, Train Acc=0.8655, Val Loss=0.6678, Val Acc=0.8187
309
+ 2025-04-25 00:06:10,087 - INFO - Epoch 4/5, Batch 0/56
310
+ 2025-04-25 00:06:15,879 - INFO - Epoch 4/5, Batch 20/56
311
+ 2025-04-25 00:06:20,730 - INFO - Epoch 4/5, Batch 40/56
312
+ 2025-04-25 00:06:48,267 - INFO - Epoch 4/5: Train Loss=0.3267, Train Acc=0.8910, Val Loss=0.4948, Val Acc=0.8291
313
+ 2025-04-25 00:06:51,995 - INFO - Epoch 5/5, Batch 0/56
314
+ 2025-04-25 00:06:58,104 - INFO - Epoch 5/5, Batch 20/56
315
+ 2025-04-25 00:07:03,050 - INFO - Epoch 5/5, Batch 40/56
316
+ 2025-04-25 00:07:31,047 - INFO - Epoch 5/5: Train Loss=0.2717, Train Acc=0.8994, Val Loss=0.3833, Val Acc=0.8760
317
+ 2025-04-25 00:07:31,049 - INFO - New best validation accuracy: 0.8760
318
+ 2025-04-25 00:07:31,051 - INFO - Trial 10 completed in 212.31s
319
+ 2025-04-25 00:07:31,051 - INFO - Validation accuracy: 0.8760
320
+ 2025-04-25 00:07:31,051 - INFO -
321
+ Hyperparameter search completed in 2040.47s
322
+ 2025-04-25 00:07:31,051 - INFO - Best config: lr=0.0001, weight_decay=0.0001
323
+ 2025-04-25 00:07:31,051 - INFO - Best validation accuracy: 0.8954
324
+ 2025-04-25 00:07:31,061 - INFO - Loading datasets from: /Users/neecat/Desktop/Projects/trash-classification/data
325
+ 2025-04-25 00:07:31,061 - INFO - Train directory: /Users/neecat/Desktop/Projects/trash-classification/data/train
326
+ 2025-04-25 00:07:31,062 - INFO - Validation directory: /Users/neecat/Desktop/Projects/trash-classification/data/val
327
+ 2025-04-25 00:07:31,062 - INFO - Test directory: /Users/neecat/Desktop/Projects/trash-classification/data/test
328
+ 2025-04-25 00:07:31,091 - INFO - Train dataset size: 1766
329
+ 2025-04-25 00:07:31,091 - INFO - Validation dataset size: 378
330
+ 2025-04-25 00:07:31,091 - INFO - Test dataset size: 383
331
+ 2025-04-25 00:07:31,092 - INFO - Classes: ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']
332
+ 2025-04-25 00:07:31,173 - INFO - Training logs will be saved to: /Users/neecat/Desktop/Projects/trash-classification/outputs/logs/training_20250425_000731.log
333
+ 2025-04-25 00:07:31,173 - INFO - Training configuration:
334
+ 2025-04-25 00:07:31,173 - INFO - Epochs: 10
335
+ 2025-04-25 00:07:31,173 - INFO - Learning rate: 0.0001
336
+ 2025-04-25 00:07:31,173 - INFO - Weight decay: 0.0001
337
+ 2025-04-25 00:07:31,174 - INFO - Device: mps
338
+ 2025-04-25 00:07:31,174 - INFO - Batch size: 32
339
+ 2025-04-25 00:07:31,174 - INFO - Image size: 224
340
+ 2025-04-25 00:07:31,300 - INFO - Training on: MPS
341
+
342
+ 2025-04-25 00:07:31,300 - INFO - Epoch 1/10 started
343
+ 2025-04-25 00:07:31,302 - INFO - Training on 56 batches
344
+ 2025-04-25 00:07:35,200 - INFO - Batch 0/56
345
+ 2025-04-25 00:07:39,708 - INFO - Batch 10/56
346
+ 2025-04-25 00:07:42,240 - INFO - Batch 20/56
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+ 2025-04-25 00:07:44,828 - INFO - Batch 30/56
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+ 2025-04-25 00:07:47,276 - INFO - Batch 40/56
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+ 2025-04-25 00:07:49,899 - INFO - Batch 50/56
350
+ 2025-04-25 00:08:01,330 - INFO - Validating...
351
+ 2025-04-25 00:08:15,086 - INFO - Epoch 1/10 completed in 43.79s
352
+ 2025-04-25 00:08:15,087 - INFO - Train Loss: 0.9510 | Train Acc: 65.55%
353
+ 2025-04-25 00:08:15,087 - INFO - Val Loss: 0.5424 | Val Acc: 79.79%
354
+ 2025-04-25 00:08:15,277 - INFO - Model saved!
355
+ 2025-04-25 00:08:15,278 - INFO - Epoch 2/10 started
356
+ 2025-04-25 00:08:15,278 - INFO - Training on 56 batches
357
+ 2025-04-25 00:08:19,104 - INFO - Batch 0/56
358
+ 2025-04-25 00:08:22,899 - INFO - Batch 10/56
359
+ 2025-04-25 00:08:25,416 - INFO - Batch 20/56
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+ 2025-04-25 00:08:27,962 - INFO - Batch 30/56
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+ 2025-04-25 00:08:30,428 - INFO - Batch 40/56
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+ 2025-04-25 00:08:33,065 - INFO - Batch 50/56
363
+ 2025-04-25 00:08:44,415 - INFO - Validating...
364
+ 2025-04-25 00:08:58,631 - INFO - Epoch 2/10 completed in 43.35s
365
+ 2025-04-25 00:08:58,632 - INFO - Train Loss: 0.4660 | Train Acc: 84.39%
366
+ 2025-04-25 00:08:58,632 - INFO - Val Loss: 0.4135 | Val Acc: 86.12%
367
+ 2025-04-25 00:08:58,806 - INFO - Model saved!
368
+ 2025-04-25 00:08:58,806 - INFO - Epoch 3/10 started
369
+ 2025-04-25 00:08:58,806 - INFO - Training on 56 batches
370
+ 2025-04-25 00:09:02,651 - INFO - Batch 0/56
371
+ 2025-04-25 00:09:06,301 - INFO - Batch 10/56
372
+ 2025-04-25 00:09:08,789 - INFO - Batch 20/56
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+ 2025-04-25 00:09:12,016 - INFO - Batch 30/56
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+ 2025-04-25 00:09:14,600 - INFO - Batch 40/56
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+ 2025-04-25 00:09:17,047 - INFO - Batch 50/56
376
+ 2025-04-25 00:09:28,404 - INFO - Validating...
377
+ 2025-04-25 00:09:42,413 - INFO - Epoch 3/10 completed in 43.61s
378
+ 2025-04-25 00:09:42,413 - INFO - Train Loss: 0.3071 | Train Acc: 89.83%
379
+ 2025-04-25 00:09:42,414 - INFO - Val Loss: 0.3719 | Val Acc: 85.54%
380
+ 2025-04-25 00:09:42,415 - INFO - Epoch 4/10 started
381
+ 2025-04-25 00:09:42,417 - INFO - Training on 56 batches
382
+ 2025-04-25 00:09:45,607 - INFO - Batch 0/56
383
+ 2025-04-25 00:09:48,681 - INFO - Batch 10/56
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+ 2025-04-25 00:09:51,124 - INFO - Batch 20/56
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+ 2025-04-25 00:09:55,279 - INFO - Batch 30/56
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+ 2025-04-25 00:09:58,283 - INFO - Batch 40/56
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+ 2025-04-25 00:10:01,359 - INFO - Batch 50/56
388
+ 2025-04-25 00:10:13,434 - INFO - Validating...
389
+ 2025-04-25 00:10:28,041 - INFO - Epoch 4/10 completed in 45.63s
390
+ 2025-04-25 00:10:28,041 - INFO - Train Loss: 0.2060 | Train Acc: 93.58%
391
+ 2025-04-25 00:10:28,041 - INFO - Val Loss: 0.3651 | Val Acc: 86.62%
392
+ 2025-04-25 00:10:28,184 - INFO - Model saved!
393
+ 2025-04-25 00:10:28,184 - INFO - Epoch 5/10 started
394
+ 2025-04-25 00:10:28,185 - INFO - Training on 56 batches
395
+ 2025-04-25 00:10:31,928 - INFO - Batch 0/56
396
+ 2025-04-25 00:10:35,264 - INFO - Batch 10/56
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+ 2025-04-25 00:10:37,728 - INFO - Batch 20/56
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+ 2025-04-25 00:10:40,227 - INFO - Batch 30/56
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+ 2025-04-25 00:10:42,689 - INFO - Batch 40/56
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+ 2025-04-25 00:10:45,161 - INFO - Batch 50/56
401
+ 2025-04-25 00:10:56,588 - INFO - Validating...
402
+ 2025-04-25 00:11:10,662 - INFO - Epoch 5/10 completed in 42.48s
403
+ 2025-04-25 00:11:10,664 - INFO - Train Loss: 0.1616 | Train Acc: 94.59%
404
+ 2025-04-25 00:11:10,664 - INFO - Val Loss: 0.3542 | Val Acc: 88.38%
405
+ 2025-04-25 00:11:10,820 - INFO - Model saved!
406
+ 2025-04-25 00:11:10,820 - INFO - Epoch 6/10 started
407
+ 2025-04-25 00:11:10,821 - INFO - Training on 56 batches
408
+ 2025-04-25 00:11:14,489 - INFO - Batch 0/56
409
+ 2025-04-25 00:11:18,058 - INFO - Batch 10/56
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+ 2025-04-25 00:11:20,513 - INFO - Batch 20/56
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+ 2025-04-25 00:11:22,952 - INFO - Batch 30/56
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+ 2025-04-25 00:11:25,462 - INFO - Batch 40/56
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+ 2025-04-25 00:11:27,997 - INFO - Batch 50/56
414
+ 2025-04-25 00:11:39,390 - INFO - Validating...
415
+ 2025-04-25 00:11:53,277 - INFO - Epoch 6/10 completed in 42.46s
416
+ 2025-04-25 00:11:53,277 - INFO - Train Loss: 0.1395 | Train Acc: 95.65%
417
+ 2025-04-25 00:11:53,278 - INFO - Val Loss: 0.3871 | Val Acc: 87.40%
418
+ 2025-04-25 00:11:53,278 - INFO - Epoch 7/10 started
419
+ 2025-04-25 00:11:53,279 - INFO - Training on 56 batches
420
+ 2025-04-25 00:11:56,533 - INFO - Batch 0/56
421
+ 2025-04-25 00:11:59,076 - INFO - Batch 10/56
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+ 2025-04-25 00:12:01,516 - INFO - Batch 20/56
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+ 2025-04-25 00:12:03,950 - INFO - Batch 30/56
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+ 2025-04-25 00:12:06,382 - INFO - Batch 40/56
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+ 2025-04-25 00:12:08,836 - INFO - Batch 50/56
426
+ 2025-04-25 00:12:20,228 - INFO - Validating...
427
+ 2025-04-25 00:12:34,151 - INFO - Epoch 7/10 completed in 40.87s
428
+ 2025-04-25 00:12:34,153 - INFO - Train Loss: 0.1029 | Train Acc: 96.71%
429
+ 2025-04-25 00:12:34,153 - INFO - Val Loss: 0.3075 | Val Acc: 89.80%
430
+ 2025-04-25 00:12:34,272 - INFO - Model saved!
431
+ 2025-04-25 00:12:34,272 - INFO - Epoch 8/10 started
432
+ 2025-04-25 00:12:34,272 - INFO - Training on 56 batches
433
+ 2025-04-25 00:12:39,110 - INFO - Batch 0/56
434
+ 2025-04-25 00:12:42,752 - INFO - Batch 10/56
435
+ 2025-04-25 00:12:45,199 - INFO - Batch 20/56
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+ 2025-04-25 00:12:47,645 - INFO - Batch 30/56
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+ 2025-04-25 00:12:50,104 - INFO - Batch 40/56
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+ 2025-04-25 00:12:52,535 - INFO - Batch 50/56
439
+ 2025-04-25 00:13:03,929 - INFO - Validating...
440
+ 2025-04-25 00:13:17,623 - INFO - Epoch 8/10 completed in 43.35s
441
+ 2025-04-25 00:13:17,624 - INFO - Train Loss: 0.0978 | Train Acc: 96.80%
442
+ 2025-04-25 00:13:17,625 - INFO - Val Loss: 0.3571 | Val Acc: 91.31%
443
+ 2025-04-25 00:13:17,795 - INFO - Model saved!
444
+ 2025-04-25 00:13:17,795 - INFO - Epoch 9/10 started
445
+ 2025-04-25 00:13:17,796 - INFO - Training on 56 batches
446
+ 2025-04-25 00:13:21,626 - INFO - Batch 0/56
447
+ 2025-04-25 00:13:25,117 - INFO - Batch 10/56
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+ 2025-04-25 00:13:27,598 - INFO - Batch 20/56
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+ 2025-04-25 00:13:30,097 - INFO - Batch 30/56
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+ 2025-04-25 00:13:32,777 - INFO - Batch 40/56
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+ 2025-04-25 00:13:35,251 - INFO - Batch 50/56
452
+ 2025-04-25 00:13:46,619 - INFO - Validating...
453
+ 2025-04-25 00:13:59,882 - INFO - Epoch 9/10 completed in 42.09s
454
+ 2025-04-25 00:13:59,884 - INFO - Train Loss: 0.0886 | Train Acc: 96.82%
455
+ 2025-04-25 00:13:59,884 - INFO - Val Loss: 0.3295 | Val Acc: 89.86%
456
+ 2025-04-25 00:13:59,885 - INFO - Epoch 10/10 started
457
+ 2025-04-25 00:13:59,887 - INFO - Training on 56 batches
458
+ 2025-04-25 00:14:03,369 - INFO - Batch 0/56
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+ 2025-04-25 00:14:06,733 - INFO - Batch 10/56
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+ 2025-04-25 00:14:09,239 - INFO - Batch 20/56
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+ 2025-04-25 00:14:11,736 - INFO - Batch 30/56
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+ 2025-04-25 00:14:14,701 - INFO - Batch 40/56
463
+ 2025-04-25 00:14:18,161 - INFO - Batch 50/56
464
+ 2025-04-25 00:14:31,156 - INFO - Validating...
465
+ 2025-04-25 00:14:44,678 - INFO - Epoch 10/10 completed in 44.79s
466
+ 2025-04-25 00:14:44,678 - INFO - Train Loss: 0.0612 | Train Acc: 98.33%
467
+ 2025-04-25 00:14:44,678 - INFO - Val Loss: 0.3382 | Val Acc: 91.43%
468
+ 2025-04-25 00:14:44,827 - INFO - Model saved!
469
+ 2025-04-25 00:14:44,829 - INFO - Training complete. Best Val Acc: 91.43%
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