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logs/train.log

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+2024-07-30 09:42:54 train_clip.py [line:144] INFO: Model will be saved at ckptFE/07-30/version_1
+2024-07-30 09:42:54 train_clip.py [line:73] INFO: model parameters: 
+
+2024-07-30 09:42:54 train_clip.py [line:74] INFO: +-----------------------+-------------------+
+| Parameter             | Value             |
++=======================+===================+
+| seed                  | 123               |
++-----------------------+-------------------+
+| optimizer             | Adan              |
++-----------------------+-------------------+
+| lr                    | 3e-06             |
++-----------------------+-------------------+
+| betas                 | [0.9, 0.98, 0.98] |
++-----------------------+-------------------+
+| eps                   | 1e-08             |
++-----------------------+-------------------+
+| weight_decay          | 0.2               |
++-----------------------+-------------------+
+| batch_size            | 256               |
++-----------------------+-------------------+
+| num_workers           | 8                 |
++-----------------------+-------------------+
+| epochs                | 100               |
++-----------------------+-------------------+
+| early_stop            | False             |
++-----------------------+-------------------+
+| patience              | 10                |
++-----------------------+-------------------+
+| delta                 | 0.0001            |
++-----------------------+-------------------+
+| caption_version       | 2                 |
++-----------------------+-------------------+
+| data_augment          | 0                 |
++-----------------------+-------------------+
+| model_save_path       | ckptFE            |
++-----------------------+-------------------+
+| log_save_path         | logs              |
++-----------------------+-------------------+
+| compute_acc_frequency | 0                 |
++-----------------------+-------------------+
+| use_scheduler         | False             |
++-----------------------+-------------------+
+| save_frequency        | 5                 |
++-----------------------+-------------------+
+| freeze_version        | 2                 |
++-----------------------+-------------------+
+2024-07-30 09:42:54 train_clip.py [line:76] INFO: 
+
+Start training...
+2024-07-30 09:43:15 train_clip.py [line:116] INFO: Epoch: 1, Loss: 6.7326 Min Loss: 6.7326
+2024-07-30 09:43:26 train_clip.py [line:116] INFO: Epoch: 2, Loss: 4.8350 Min Loss: 4.8350
+2024-07-30 09:43:36 train_clip.py [line:116] INFO: Epoch: 3, Loss: 4.2236 Min Loss: 4.2236
+2024-07-30 09:43:47 train_clip.py [line:116] INFO: Epoch: 4, Loss: 3.6406 Min Loss: 3.6406
+2024-07-30 09:44:00 train_clip.py [line:116] INFO: Epoch: 5, Loss: 3.1923 Min Loss: 3.1923
+2024-07-30 09:44:10 train_clip.py [line:116] INFO: Epoch: 6, Loss: 2.7900 Min Loss: 2.7900
+2024-07-30 09:44:21 train_clip.py [line:116] INFO: Epoch: 7, Loss: 2.7613 Min Loss: 2.7613
+2024-07-30 09:44:31 train_clip.py [line:116] INFO: Epoch: 8, Loss: 2.4837 Min Loss: 2.4837
+2024-07-30 09:44:42 train_clip.py [line:116] INFO: Epoch: 9, Loss: 2.3107 Min Loss: 2.3107
+2024-07-30 09:44:52 train_clip.py [line:116] INFO: Epoch: 10, Loss: 2.5804 Min Loss: 2.3107
+2024-07-30 09:45:03 train_clip.py [line:116] INFO: Epoch: 11, Loss: 2.3105 Min Loss: 2.3105
+2024-07-30 09:45:13 train_clip.py [line:116] INFO: Epoch: 12, Loss: 2.2390 Min Loss: 2.2390
+2024-07-30 09:45:24 train_clip.py [line:116] INFO: Epoch: 13, Loss: 2.1971 Min Loss: 2.1971
+2024-07-30 09:45:34 train_clip.py [line:116] INFO: Epoch: 14, Loss: 2.1353 Min Loss: 2.1353
+2024-07-30 09:45:44 train_clip.py [line:116] INFO: Epoch: 15, Loss: 2.1982 Min Loss: 2.1353
+2024-07-30 09:45:55 train_clip.py [line:116] INFO: Epoch: 16, Loss: 2.1203 Min Loss: 2.1203
+2024-07-30 09:46:06 train_clip.py [line:116] INFO: Epoch: 17, Loss: 2.0903 Min Loss: 2.0903
+2024-07-30 09:46:12 train_clip.py [line:116] INFO: Epoch: 18, Loss: 2.2247 Min Loss: 2.0903
+2024-07-30 09:46:23 train_clip.py [line:116] INFO: Epoch: 19, Loss: 1.9555 Min Loss: 1.9555
+2024-07-30 09:46:34 train_clip.py [line:116] INFO: Epoch: 20, Loss: 2.1647 Min Loss: 1.9555
+2024-07-30 09:46:40 train_clip.py [line:116] INFO: Epoch: 21, Loss: 2.1485 Min Loss: 1.9555
+2024-07-30 09:46:48 train_clip.py [line:116] INFO: Epoch: 22, Loss: 1.9868 Min Loss: 1.9555
+2024-07-30 09:46:55 train_clip.py [line:116] INFO: Epoch: 23, Loss: 2.0948 Min Loss: 1.9555
+2024-07-30 09:47:02 train_clip.py [line:116] INFO: Epoch: 24, Loss: 2.2866 Min Loss: 1.9555
+2024-07-30 09:47:14 train_clip.py [line:116] INFO: Epoch: 25, Loss: 2.0188 Min Loss: 1.9555
+2024-07-30 09:47:20 train_clip.py [line:116] INFO: Epoch: 26, Loss: 1.9677 Min Loss: 1.9555
+2024-07-30 09:47:27 train_clip.py [line:116] INFO: Epoch: 27, Loss: 2.1724 Min Loss: 1.9555
+2024-07-30 09:47:35 train_clip.py [line:116] INFO: Epoch: 28, Loss: 2.1688 Min Loss: 1.9555
+2024-07-30 09:47:42 train_clip.py [line:116] INFO: Epoch: 29, Loss: 2.1263 Min Loss: 1.9555
+2024-07-30 09:47:53 train_clip.py [line:116] INFO: Epoch: 30, Loss: 1.9607 Min Loss: 1.9555
+2024-07-30 09:48:00 train_clip.py [line:116] INFO: Epoch: 31, Loss: 2.1069 Min Loss: 1.9555
+2024-07-30 09:48:07 train_clip.py [line:116] INFO: Epoch: 32, Loss: 2.1050 Min Loss: 1.9555
+2024-07-30 09:48:14 train_clip.py [line:116] INFO: Epoch: 33, Loss: 1.9982 Min Loss: 1.9555
+2024-07-30 09:48:22 train_clip.py [line:116] INFO: Epoch: 34, Loss: 2.0697 Min Loss: 1.9555
+2024-07-30 09:48:33 train_clip.py [line:116] INFO: Epoch: 35, Loss: 2.0341 Min Loss: 1.9555
+2024-07-30 09:48:39 train_clip.py [line:116] INFO: Epoch: 36, Loss: 2.1605 Min Loss: 1.9555
+2024-07-30 09:48:47 train_clip.py [line:116] INFO: Epoch: 37, Loss: 1.9961 Min Loss: 1.9555
+2024-07-30 09:48:54 train_clip.py [line:116] INFO: Epoch: 38, Loss: 2.1738 Min Loss: 1.9555
+2024-07-30 09:49:01 train_clip.py [line:116] INFO: Epoch: 39, Loss: 2.1491 Min Loss: 1.9555
+2024-07-30 09:49:12 train_clip.py [line:116] INFO: Epoch: 40, Loss: 1.9688 Min Loss: 1.9555
+2024-07-30 09:49:19 train_clip.py [line:116] INFO: Epoch: 41, Loss: 2.0219 Min Loss: 1.9555
+2024-07-30 09:49:26 train_clip.py [line:116] INFO: Epoch: 42, Loss: 1.9816 Min Loss: 1.9555
+2024-07-30 09:49:34 train_clip.py [line:116] INFO: Epoch: 43, Loss: 2.0341 Min Loss: 1.9555
+2024-07-30 09:49:41 train_clip.py [line:116] INFO: Epoch: 44, Loss: 2.1563 Min Loss: 1.9555
+2024-07-30 09:49:52 train_clip.py [line:116] INFO: Epoch: 45, Loss: 1.9851 Min Loss: 1.9555
+2024-07-30 09:49:59 train_clip.py [line:116] INFO: Epoch: 46, Loss: 2.0096 Min Loss: 1.9555
+2024-07-30 09:50:10 train_clip.py [line:116] INFO: Epoch: 47, Loss: 1.9379 Min Loss: 1.9379
+2024-07-30 09:50:17 train_clip.py [line:116] INFO: Epoch: 48, Loss: 2.0642 Min Loss: 1.9379
+2024-07-30 09:50:24 train_clip.py [line:116] INFO: Epoch: 49, Loss: 2.0583 Min Loss: 1.9379
+2024-07-30 09:50:35 train_clip.py [line:116] INFO: Epoch: 50, Loss: 1.9452 Min Loss: 1.9379
+2024-07-30 09:50:42 train_clip.py [line:116] INFO: Epoch: 51, Loss: 2.0361 Min Loss: 1.9379
+2024-07-30 09:50:49 train_clip.py [line:116] INFO: Epoch: 52, Loss: 1.9722 Min Loss: 1.9379
+2024-07-30 09:50:56 train_clip.py [line:116] INFO: Epoch: 53, Loss: 1.9925 Min Loss: 1.9379
+2024-07-30 09:51:04 train_clip.py [line:116] INFO: Epoch: 54, Loss: 2.1328 Min Loss: 1.9379
+2024-07-30 09:51:15 train_clip.py [line:116] INFO: Epoch: 55, Loss: 2.0497 Min Loss: 1.9379
+2024-07-30 09:51:21 train_clip.py [line:116] INFO: Epoch: 56, Loss: 2.0061 Min Loss: 1.9379
+2024-07-30 09:51:29 train_clip.py [line:116] INFO: Epoch: 57, Loss: 2.2227 Min Loss: 1.9379
+2024-07-30 09:51:36 train_clip.py [line:116] INFO: Epoch: 58, Loss: 1.9891 Min Loss: 1.9379
+2024-07-30 09:51:43 train_clip.py [line:116] INFO: Epoch: 59, Loss: 1.9929 Min Loss: 1.9379
+2024-07-30 09:51:54 train_clip.py [line:116] INFO: Epoch: 60, Loss: 2.0990 Min Loss: 1.9379
+2024-07-30 09:52:01 train_clip.py [line:116] INFO: Epoch: 61, Loss: 2.0332 Min Loss: 1.9379
+2024-07-30 09:52:12 train_clip.py [line:116] INFO: Epoch: 62, Loss: 1.9359 Min Loss: 1.9359
+2024-07-30 09:52:19 train_clip.py [line:116] INFO: Epoch: 63, Loss: 2.0810 Min Loss: 1.9359
+2024-07-30 09:52:26 train_clip.py [line:116] INFO: Epoch: 64, Loss: 2.1124 Min Loss: 1.9359
+2024-07-30 09:52:37 train_clip.py [line:116] INFO: Epoch: 65, Loss: 2.0724 Min Loss: 1.9359
+2024-07-30 09:52:44 train_clip.py [line:116] INFO: Epoch: 66, Loss: 2.0832 Min Loss: 1.9359
+2024-07-30 09:52:52 train_clip.py [line:116] INFO: Epoch: 67, Loss: 2.0640 Min Loss: 1.9359
+2024-07-30 09:53:03 train_clip.py [line:116] INFO: Epoch: 68, Loss: 1.9184 Min Loss: 1.9184
+2024-07-30 09:53:10 train_clip.py [line:116] INFO: Epoch: 69, Loss: 1.9776 Min Loss: 1.9184
+2024-07-30 09:53:22 train_clip.py [line:116] INFO: Epoch: 70, Loss: 1.9696 Min Loss: 1.9184
+2024-07-30 09:53:28 train_clip.py [line:116] INFO: Epoch: 71, Loss: 2.1936 Min Loss: 1.9184
+2024-07-30 09:53:35 train_clip.py [line:116] INFO: Epoch: 72, Loss: 2.1248 Min Loss: 1.9184
+2024-07-30 09:53:43 train_clip.py [line:116] INFO: Epoch: 73, Loss: 2.1000 Min Loss: 1.9184
+2024-07-30 09:53:50 train_clip.py [line:116] INFO: Epoch: 74, Loss: 1.9791 Min Loss: 1.9184
+2024-07-30 09:54:02 train_clip.py [line:116] INFO: Epoch: 75, Loss: 1.9313 Min Loss: 1.9184
+2024-07-30 09:54:08 train_clip.py [line:116] INFO: Epoch: 76, Loss: 2.1005 Min Loss: 1.9184
+2024-07-30 09:54:15 train_clip.py [line:116] INFO: Epoch: 77, Loss: 2.1343 Min Loss: 1.9184
+2024-07-30 09:54:23 train_clip.py [line:116] INFO: Epoch: 78, Loss: 2.0381 Min Loss: 1.9184
+2024-07-30 09:54:30 train_clip.py [line:116] INFO: Epoch: 79, Loss: 2.0349 Min Loss: 1.9184
+2024-07-30 09:54:41 train_clip.py [line:116] INFO: Epoch: 80, Loss: 2.1082 Min Loss: 1.9184
+2024-07-30 09:54:48 train_clip.py [line:116] INFO: Epoch: 81, Loss: 1.9580 Min Loss: 1.9184
+2024-07-30 09:54:55 train_clip.py [line:116] INFO: Epoch: 82, Loss: 2.0330 Min Loss: 1.9184
+2024-07-30 09:55:02 train_clip.py [line:116] INFO: Epoch: 83, Loss: 2.0308 Min Loss: 1.9184
+2024-07-30 09:55:09 train_clip.py [line:116] INFO: Epoch: 84, Loss: 1.9555 Min Loss: 1.9184
+2024-07-30 09:55:21 train_clip.py [line:116] INFO: Epoch: 85, Loss: 2.0020 Min Loss: 1.9184
+2024-07-30 09:55:28 train_clip.py [line:116] INFO: Epoch: 86, Loss: 2.0153 Min Loss: 1.9184
+2024-07-30 09:55:39 train_clip.py [line:116] INFO: Epoch: 87, Loss: 1.9062 Min Loss: 1.9062
+2024-07-30 09:55:46 train_clip.py [line:116] INFO: Epoch: 88, Loss: 2.1427 Min Loss: 1.9062
+2024-07-30 09:55:53 train_clip.py [line:116] INFO: Epoch: 89, Loss: 2.1196 Min Loss: 1.9062
+2024-07-30 09:56:08 train_clip.py [line:116] INFO: Epoch: 90, Loss: 1.8230 Min Loss: 1.8230
+2024-07-30 09:56:14 train_clip.py [line:116] INFO: Epoch: 91, Loss: 2.1242 Min Loss: 1.8230
+2024-07-30 09:56:22 train_clip.py [line:116] INFO: Epoch: 92, Loss: 2.0993 Min Loss: 1.8230
+2024-07-30 09:56:29 train_clip.py [line:116] INFO: Epoch: 93, Loss: 1.9123 Min Loss: 1.8230
+2024-07-30 09:56:36 train_clip.py [line:116] INFO: Epoch: 94, Loss: 2.0217 Min Loss: 1.8230
+2024-07-30 09:56:48 train_clip.py [line:116] INFO: Epoch: 95, Loss: 1.9521 Min Loss: 1.8230
+2024-07-30 09:56:54 train_clip.py [line:116] INFO: Epoch: 96, Loss: 2.0764 Min Loss: 1.8230
+2024-07-30 09:57:02 train_clip.py [line:116] INFO: Epoch: 97, Loss: 1.9347 Min Loss: 1.8230
+2024-07-30 09:57:09 train_clip.py [line:116] INFO: Epoch: 98, Loss: 1.9534 Min Loss: 1.8230
+2024-07-30 09:57:16 train_clip.py [line:116] INFO: Epoch: 99, Loss: 2.0558 Min Loss: 1.8230
+2024-07-30 09:57:28 train_clip.py [line:116] INFO: Epoch: 100, Loss: 1.9141 Min Loss: 1.8230
+2024-07-30 09:57:28 train_clip.py [line:125] INFO: 
+
+Finish training...