2023-05-19 14:34:14,060:INFO: Effective parameters: 2023-05-19 14:34:14,060:INFO: <<< __deprecated_keys__: set() 2023-05-19 14:34:14,060:INFO: <<< __immutable__: False 2023-05-19 14:34:14,060:INFO: <<< __new_allowed__: False 2023-05-19 14:34:14,060:INFO: <<< __renamed_keys__: {} 2023-05-19 14:34:14,060:INFO: device: cuda:0 n_gpu: 4 2023-05-19 14:34:14,084:INFO: device: cuda:3 n_gpu: 4 2023-05-19 14:34:14,084:INFO: device: cuda:2 n_gpu: 4 2023-05-19 14:34:14,085:INFO: device: cuda:1 n_gpu: 4 2023-05-19 14:34:14,801:INFO: Model config { "attention_probs_dropout_prob": 0.1, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "hidden_size": 512, "initializer_range": 0.02, "intermediate_size": 2048, "max_position_embeddings": 128, "num_attention_heads": 8, "num_hidden_layers": 4, "type_vocab_size": 2, "vocab_size": 512 } 2023-05-19 14:34:14,802:WARNING: Stage-One:True, Stage-Two:False 2023-05-19 14:34:14,802:WARNING: Test retrieval by loose type. 2023-05-19 14:34:14,802:WARNING: embed_dim: 512 2023-05-19 14:34:14,802:WARNING: image_resolution: 224 2023-05-19 14:34:14,802:WARNING: vision_layers: 12 2023-05-19 14:34:14,802:WARNING: vision_width: 768 2023-05-19 14:34:14,802:WARNING: vision_patch_size: 32 2023-05-19 14:34:14,802:WARNING: context_length: 77 2023-05-19 14:34:14,802:WARNING: vocab_size: 49408 2023-05-19 14:34:14,802:WARNING: transformer_width: 512 2023-05-19 14:34:14,802:WARNING: transformer_heads: 8 2023-05-19 14:34:14,802:WARNING: transformer_layers: 12 2023-05-19 14:34:14,802:WARNING: linear_patch: 2d 2023-05-19 14:34:14,802:WARNING: cut_top_layer: 0 2023-05-19 14:34:16,508:WARNING: sim_header: meanP 2023-05-19 14:34:20,144:INFO: -------------------- 2023-05-19 14:34:20,145:INFO: Weights from pretrained model not used in CLIP4Clip: clip.input_resolution clip.context_length clip.vocab_size 2023-05-19 14:34:21,650:INFO: ***** Running test ***** 2023-05-19 14:34:21,650:INFO: Num examples = 1000 2023-05-19 14:34:21,650:INFO: Batch size = 16 2023-05-19 14:34:21,650:INFO: Num steps = 63 2023-05-19 14:34:21,650:INFO: ***** Running val ***** 2023-05-19 14:34:21,650:INFO: Num examples = 1000 2023-05-19 14:34:32,430:INFO: ***** Running training ***** 2023-05-19 14:34:32,431:INFO: Num examples = 180000 2023-05-19 14:34:32,431:INFO: Batch size = 128 2023-05-19 14:34:32,431:INFO: Num steps = 7030 2023-05-19 14:35:05,888:INFO: Reducer buckets have been rebuilt in this iteration. 2023-05-19 14:35:05,898:INFO: Reducer buckets have been rebuilt in this iteration. 2023-05-19 14:35:05,901:INFO: Reducer buckets have been rebuilt in this iteration. 2023-05-19 14:35:05,902:INFO: Reducer buckets have been rebuilt in this iteration. 2023-05-19 14:42:36,083:INFO: Epoch: 1/5, Step: 50/1406, Lr: 0.000000007, Loss: 1.772803, Time/step: 9.672644 2023-05-19 14:49:58,886:INFO: Epoch: 1/5, Step: 100/1406, Lr: 0.000000014, Loss: 1.799614, Time/step: 8.856049 2023-05-19 14:57:36,268:INFO: Epoch: 1/5, Step: 150/1406, Lr: 0.000000021, Loss: 1.159466, Time/step: 9.147633 2023-05-19 15:05:04,683:INFO: Epoch: 1/5, Step: 200/1406, Lr: 0.000000028, Loss: 1.352810, Time/step: 8.968296 2023-05-19 15:12:32,342:INFO: Epoch: 1/5, Step: 250/1406, Lr: 0.000000036, Loss: 1.261858, Time/step: 8.953166 2023-05-19 15:20:27,809:INFO: Epoch: 1/5, Step: 300/1406, Lr: 0.000000043, Loss: 1.212567, Time/step: 9.509343 2023-05-19 15:27:50,955:INFO: Epoch: 1/5, Step: 350/1406, Lr: 0.000000050, Loss: 1.254130, Time/step: 8.862908 2023-05-19 15:35:47,737:INFO: Epoch: 1/5, Step: 400/1406, Lr: 0.000000057, Loss: 1.151219, Time/step: 9.535638 2023-05-19 15:43:22,877:INFO: Epoch: 1/5, Step: 450/1406, Lr: 0.000000064, Loss: 0.940618, Time/step: 9.102783 2023-05-19 15:50:55,624:INFO: Epoch: 1/5, Step: 500/1406, Lr: 0.000000071, Loss: 0.998732, Time/step: 9.054932 2023-05-19 15:58:03,175:INFO: Epoch: 1/5, Step: 550/1406, Lr: 0.000000078, Loss: 0.873881, Time/step: 8.551015 2023-05-19 16:05:18,529:INFO: Epoch: 1/5, Step: 600/1406, Lr: 0.000000085, Loss: 1.040758, Time/step: 8.707076 2023-05-19 16:13:00,345:INFO: Epoch: 1/5, Step: 650/1406, Lr: 0.000000092, Loss: 1.025295, Time/step: 9.236312 2023-05-19 16:20:15,259:INFO: Epoch: 1/5, Step: 700/1406, Lr: 0.000000100, Loss: 0.985034, Time/step: 8.698277 2023-05-19 16:27:41,161:INFO: Epoch: 1/5, Step: 750/1406, Lr: 0.000000097, Loss: 0.781845, Time/step: 8.918034 2023-05-19 16:35:05,900:INFO: Epoch: 1/5, Step: 800/1406, Lr: 0.000000097, Loss: 0.863240, Time/step: 8.894773 2023-05-19 16:42:31,212:INFO: Epoch: 1/5, Step: 850/1406, Lr: 0.000000096, Loss: 0.770174, Time/step: 8.906231 2023-05-19 16:50:11,254:INFO: Epoch: 1/5, Step: 900/1406, Lr: 0.000000096, Loss: 0.996139, Time/step: 9.200837 2023-05-19 16:57:48,428:INFO: Epoch: 1/5, Step: 950/1406, Lr: 0.000000096, Loss: 0.874828, Time/step: 9.143474 2023-05-19 17:04:53,977:INFO: Epoch: 1/5, Step: 1000/1406, Lr: 0.000000095, Loss: 1.004976, Time/step: 8.510964 2023-05-19 17:12:36,176:INFO: Epoch: 1/5, Step: 1050/1406, Lr: 0.000000095, Loss: 0.801645, Time/step: 9.243977 2023-05-19 17:20:30,159:INFO: Epoch: 1/5, Step: 1100/1406, Lr: 0.000000094, Loss: 0.618540, Time/step: 9.479651 2023-05-19 17:27:59,503:INFO: Epoch: 1/5, Step: 1150/1406, Lr: 0.000000094, Loss: 0.683802, Time/step: 8.986874 2023-05-19 17:35:24,654:INFO: Epoch: 1/5, Step: 1200/1406, Lr: 0.000000093, Loss: 0.733529, Time/step: 8.903008 2023-05-19 17:43:23,057:INFO: Epoch: 1/5, Step: 1250/1406, Lr: 0.000000092, Loss: 0.824775, Time/step: 9.568058 2023-05-19 17:50:28,762:INFO: Epoch: 1/5, Step: 1300/1406, Lr: 0.000000092, Loss: 0.655520, Time/step: 8.514079 2023-05-19 17:58:27,413:INFO: Epoch: 1/5, Step: 1350/1406, Lr: 0.000000091, Loss: 0.628934, Time/step: 9.573027 2023-05-19 18:06:38,035:INFO: Epoch: 1/5, Step: 1400/1406, Lr: 0.000000091, Loss: 0.415231, Time/step: 9.812421 2023-05-19 18:07:27,429:INFO: Epoch 1/5 Finished, Train Loss: 1.014174 2023-05-19 18:07:28,603:INFO: Model saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.0 2023-05-19 18:07:28,603:INFO: Optimizer saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_opt.bin.0 2023-05-19 18:12:01,088:INFO: sim matrix size: 1000, 1000 2023-05-19 18:12:01,195:INFO: Length-T: 1000, Length-V:1000 2023-05-19 18:12:01,195:INFO: Text-to-Video: 2023-05-19 18:12:01,195:INFO: >>> R@1: 42.2 - R@5: 69.7 - R@10: 79.1 - Median R: 2.0 - Mean R: 16.3 2023-05-19 18:12:01,195:INFO: Video-to-Text: 2023-05-19 18:12:01,195:INFO: >>> R@1: 42.6 - V2T$R@5: 70.4 - V2T$R@10: 80.8 - V2T$Median R: 2.0 - V2T$Mean R: 12.2 2023-05-19 18:12:01,197:INFO: The best model is: /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.0, the R1 is: 42.2000 2023-05-19 18:18:33,027:INFO: Epoch: 2/5, Step: 44/1406, Lr: 0.000000090, Loss: 0.607899, Time/step: 7.831941 2023-05-19 18:26:06,023:INFO: Epoch: 2/5, Step: 94/1406, Lr: 0.000000089, Loss: 0.840140, Time/step: 9.059904 2023-05-19 18:33:31,199:INFO: Epoch: 2/5, Step: 144/1406, Lr: 0.000000088, Loss: 0.631595, Time/step: 8.903526 2023-05-19 18:40:34,298:INFO: Epoch: 2/5, Step: 194/1406, Lr: 0.000000088, Loss: 0.615566, Time/step: 8.461967 2023-05-19 18:47:48,242:INFO: Epoch: 2/5, Step: 244/1406, Lr: 0.000000087, Loss: 0.482479, Time/step: 8.678871 2023-05-19 18:55:39,164:INFO: Epoch: 2/5, Step: 294/1406, Lr: 0.000000086, Loss: 0.584932, Time/step: 9.418427 2023-05-19 19:02:50,486:INFO: Epoch: 2/5, Step: 344/1406, Lr: 0.000000085, Loss: 0.861302, Time/step: 8.626442 2023-05-19 19:10:34,135:INFO: Epoch: 2/5, Step: 394/1406, Lr: 0.000000085, Loss: 0.669575, Time/step: 9.272967 2023-05-19 19:19:44,748:INFO: Epoch: 2/5, Step: 444/1406, Lr: 0.000000084, Loss: 0.717069, Time/step: 11.012259 2023-05-19 19:27:32,073:INFO: Epoch: 2/5, Step: 494/1406, Lr: 0.000000083, Loss: 0.717894, Time/step: 9.346487 2023-05-19 19:34:25,911:INFO: Epoch: 2/5, Step: 544/1406, Lr: 0.000000082, Loss: 0.497785, Time/step: 8.276749 2023-05-19 19:42:09,784:INFO: Epoch: 2/5, Step: 594/1406, Lr: 0.000000081, Loss: 0.674969, Time/step: 9.277466 2023-05-19 19:49:36,042:INFO: Epoch: 2/5, Step: 644/1406, Lr: 0.000000080, Loss: 0.593538, Time/step: 8.925140 2023-05-19 19:56:48,887:INFO: Epoch: 2/5, Step: 694/1406, Lr: 0.000000080, Loss: 0.739679, Time/step: 8.656898 2023-05-19 20:04:20,359:INFO: Epoch: 2/5, Step: 744/1406, Lr: 0.000000079, Loss: 0.664531, Time/step: 9.029429 2023-05-19 20:11:36,474:INFO: Epoch: 2/5, Step: 794/1406, Lr: 0.000000078, Loss: 0.570635, Time/step: 8.722302 2023-05-19 20:18:23,992:INFO: Epoch: 2/5, Step: 844/1406, Lr: 0.000000077, Loss: 0.647684, Time/step: 8.150353 2023-05-19 20:24:42,643:INFO: Epoch: 2/5, Step: 894/1406, Lr: 0.000000076, Loss: 0.602469, Time/step: 7.572995 2023-05-19 20:31:00,578:INFO: Epoch: 2/5, Step: 944/1406, Lr: 0.000000075, Loss: 0.713058, Time/step: 7.558710 2023-05-19 20:37:32,846:INFO: Epoch: 2/5, Step: 994/1406, Lr: 0.000000074, Loss: 0.638026, Time/step: 7.845348 2023-05-19 20:43:57,010:INFO: Epoch: 2/5, Step: 1044/1406, Lr: 0.000000073, Loss: 0.587895, Time/step: 7.683276 2023-05-19 20:50:56,519:INFO: Epoch: 2/5, Step: 1094/1406, Lr: 0.000000072, Loss: 0.647776, Time/step: 8.390173 2023-05-19 20:58:29,188:INFO: Epoch: 2/5, Step: 1144/1406, Lr: 0.000000071, Loss: 0.640317, Time/step: 9.053278 2023-05-19 21:05:40,071:INFO: Epoch: 2/5, Step: 1194/1406, Lr: 0.000000070, Loss: 0.876661, Time/step: 8.617661 2023-05-19 21:13:13,842:INFO: Epoch: 2/5, Step: 1244/1406, Lr: 0.000000069, Loss: 0.472765, Time/step: 9.075399 2023-05-19 21:20:41,327:INFO: Epoch: 2/5, Step: 1294/1406, Lr: 0.000000068, Loss: 0.726190, Time/step: 8.949702 2023-05-19 21:27:56,645:INFO: Epoch: 2/5, Step: 1344/1406, Lr: 0.000000067, Loss: 0.724819, Time/step: 8.706351 2023-05-19 21:35:02,527:INFO: Epoch: 2/5, Step: 1394/1406, Lr: 0.000000066, Loss: 0.555131, Time/step: 8.517618 2023-05-19 21:36:48,743:INFO: Epoch 2/5 Finished, Train Loss: 0.609350 2023-05-19 21:36:49,942:INFO: Model saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.1 2023-05-19 21:36:49,943:INFO: Optimizer saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_opt.bin.1 2023-05-19 21:41:05,749:INFO: sim matrix size: 1000, 1000 2023-05-19 21:41:05,863:INFO: Length-T: 1000, Length-V:1000 2023-05-19 21:41:05,863:INFO: Text-to-Video: 2023-05-19 21:41:05,863:INFO: >>> R@1: 42.1 - R@5: 70.1 - R@10: 79.7 - Median R: 2.0 - Mean R: 15.7 2023-05-19 21:41:05,863:INFO: Video-to-Text: 2023-05-19 21:41:05,863:INFO: >>> R@1: 42.6 - V2T$R@5: 70.7 - V2T$R@10: 81.4 - V2T$Median R: 2.0 - V2T$Mean R: 11.6 2023-05-19 21:41:05,865:INFO: The best model is: /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.0, the R1 is: 42.2000 2023-05-19 21:47:00,875:INFO: Epoch: 3/5, Step: 38/1406, Lr: 0.000000065, Loss: 0.402465, Time/step: 7.096339 2023-05-19 21:54:38,595:INFO: Epoch: 3/5, Step: 88/1406, Lr: 0.000000064, Loss: 0.420273, Time/step: 9.154390 2023-05-19 22:01:56,214:INFO: Epoch: 3/5, Step: 138/1406, Lr: 0.000000062, Loss: 0.320869, Time/step: 8.752386 2023-05-19 22:09:33,001:INFO: Epoch: 3/5, Step: 188/1406, Lr: 0.000000061, Loss: 0.342521, Time/step: 9.135721 2023-05-19 22:17:13,529:INFO: Epoch: 3/5, Step: 238/1406, Lr: 0.000000060, Loss: 0.482467, Time/step: 9.210552 2023-05-19 22:25:19,419:INFO: Epoch: 3/5, Step: 288/1406, Lr: 0.000000059, Loss: 0.405158, Time/step: 9.717801 2023-05-19 22:33:17,116:INFO: Epoch: 3/5, Step: 338/1406, Lr: 0.000000058, Loss: 0.244704, Time/step: 9.553921 2023-05-19 22:40:43,495:INFO: Epoch: 3/5, Step: 388/1406, Lr: 0.000000057, Loss: 0.339588, Time/step: 8.927569 2023-05-19 22:48:29,123:INFO: Epoch: 3/5, Step: 438/1406, Lr: 0.000000056, Loss: 0.549697, Time/step: 9.312556 2023-05-19 22:56:38,155:INFO: Epoch: 3/5, Step: 488/1406, Lr: 0.000000055, Loss: 0.333068, Time/step: 9.780634 2023-05-19 23:04:15,115:INFO: Epoch: 3/5, Step: 538/1406, Lr: 0.000000054, Loss: 0.414955, Time/step: 9.139198 2023-05-19 23:11:57,153:INFO: Epoch: 3/5, Step: 588/1406, Lr: 0.000000053, Loss: 0.400595, Time/step: 9.240748 2023-05-19 23:19:40,375:INFO: Epoch: 3/5, Step: 638/1406, Lr: 0.000000051, Loss: 0.387137, Time/step: 9.264428 2023-05-19 23:27:16,713:INFO: Epoch: 3/5, Step: 688/1406, Lr: 0.000000050, Loss: 0.487548, Time/step: 9.126763 2023-05-19 23:34:57,773:INFO: Epoch: 3/5, Step: 738/1406, Lr: 0.000000049, Loss: 0.344679, Time/step: 9.221190 2023-05-19 23:42:57,175:INFO: Epoch: 3/5, Step: 788/1406, Lr: 0.000000048, Loss: 0.450450, Time/step: 9.588032 2023-05-19 23:50:58,984:INFO: Epoch: 3/5, Step: 838/1406, Lr: 0.000000047, Loss: 0.440607, Time/step: 9.636169 2023-05-19 23:58:36,354:INFO: Epoch: 3/5, Step: 888/1406, Lr: 0.000000046, Loss: 0.343349, Time/step: 9.147397 2023-05-20 00:06:09,582:INFO: Epoch: 3/5, Step: 938/1406, Lr: 0.000000045, Loss: 0.591625, Time/step: 9.064545 2023-05-20 00:14:17,375:INFO: Epoch: 3/5, Step: 988/1406, Lr: 0.000000044, Loss: 0.334230, Time/step: 9.755859 2023-05-20 00:21:40,703:INFO: Epoch: 3/5, Step: 1038/1406, Lr: 0.000000043, Loss: 0.475254, Time/step: 8.866553 2023-05-20 00:29:13,367:INFO: Epoch: 3/5, Step: 1088/1406, Lr: 0.000000041, Loss: 0.418965, Time/step: 9.053264 2023-05-20 00:36:50,136:INFO: Epoch: 3/5, Step: 1138/1406, Lr: 0.000000040, Loss: 0.372977, Time/step: 9.135387 2023-05-20 00:44:18,484:INFO: Epoch: 3/5, Step: 1188/1406, Lr: 0.000000039, Loss: 0.470489, Time/step: 8.966951 2023-05-20 00:51:48,301:INFO: Epoch: 3/5, Step: 1238/1406, Lr: 0.000000038, Loss: 0.411091, Time/step: 8.996320 2023-05-20 00:59:32,411:INFO: Epoch: 3/5, Step: 1288/1406, Lr: 0.000000037, Loss: 0.388509, Time/step: 9.282204 2023-05-20 01:07:00,597:INFO: Epoch: 3/5, Step: 1338/1406, Lr: 0.000000036, Loss: 0.471972, Time/step: 8.963709 2023-05-20 01:14:45,683:INFO: Epoch: 3/5, Step: 1388/1406, Lr: 0.000000035, Loss: 0.272990, Time/step: 9.301701 2023-05-20 01:17:21,342:INFO: Epoch 3/5 Finished, Train Loss: 0.432906 2023-05-20 01:17:22,598:INFO: Model saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.2 2023-05-20 01:17:22,599:INFO: Optimizer saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_opt.bin.2 2023-05-20 01:21:45,455:INFO: sim matrix size: 1000, 1000 2023-05-20 01:21:45,564:INFO: Length-T: 1000, Length-V:1000 2023-05-20 01:21:45,564:INFO: Text-to-Video: 2023-05-20 01:21:45,564:INFO: >>> R@1: 42.3 - R@5: 69.4 - R@10: 79.8 - Median R: 2.0 - Mean R: 16.5 2023-05-20 01:21:45,564:INFO: Video-to-Text: 2023-05-20 01:21:45,564:INFO: >>> R@1: 41.3 - V2T$R@5: 71.1 - V2T$R@10: 80.2 - V2T$Median R: 2.0 - V2T$Mean R: 12.0 2023-05-20 01:21:45,566:INFO: The best model is: /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.2, the R1 is: 42.3000 2023-05-20 01:26:43,853:INFO: Epoch: 4/5, Step: 32/1406, Lr: 0.000000034, Loss: 0.398417, Time/step: 5.961623 2023-05-20 01:34:08,665:INFO: Epoch: 4/5, Step: 82/1406, Lr: 0.000000033, Loss: 0.397569, Time/step: 8.896231 2023-05-20 01:41:53,662:INFO: Epoch: 4/5, Step: 132/1406, Lr: 0.000000032, Loss: 0.285948, Time/step: 9.299923 2023-05-20 01:49:18,933:INFO: Epoch: 4/5, Step: 182/1406, Lr: 0.000000031, Loss: 0.382720, Time/step: 8.905423 2023-05-20 01:56:58,028:INFO: Epoch: 4/5, Step: 232/1406, Lr: 0.000000030, Loss: 0.368505, Time/step: 9.181882 2023-05-20 02:04:30,513:INFO: Epoch: 4/5, Step: 282/1406, Lr: 0.000000029, Loss: 0.271590, Time/step: 9.049696 2023-05-20 02:12:08,160:INFO: Epoch: 4/5, Step: 332/1406, Lr: 0.000000028, Loss: 0.257936, Time/step: 9.152929 2023-05-20 02:19:57,951:INFO: Epoch: 4/5, Step: 382/1406, Lr: 0.000000027, Loss: 0.457071, Time/step: 9.395819 2023-05-20 02:27:25,045:INFO: Epoch: 4/5, Step: 432/1406, Lr: 0.000000026, Loss: 0.267229, Time/step: 8.941865 2023-05-20 02:35:06,638:INFO: Epoch: 4/5, Step: 482/1406, Lr: 0.000000025, Loss: 0.267339, Time/step: 9.231869 2023-05-20 02:42:38,893:INFO: Epoch: 4/5, Step: 532/1406, Lr: 0.000000024, Loss: 0.368174, Time/step: 9.045080 2023-05-20 02:50:07,277:INFO: Epoch: 4/5, Step: 582/1406, Lr: 0.000000023, Loss: 0.349071, Time/step: 8.967670 2023-05-20 02:57:49,945:INFO: Epoch: 4/5, Step: 632/1406, Lr: 0.000000022, Loss: 0.331544, Time/step: 9.253368 2023-05-20 03:05:26,270:INFO: Epoch: 4/5, Step: 682/1406, Lr: 0.000000021, Loss: 0.347127, Time/step: 9.126480 2023-05-20 03:13:20,061:INFO: Epoch: 4/5, Step: 732/1406, Lr: 0.000000020, Loss: 0.424346, Time/step: 9.475826 2023-05-20 03:20:45,774:INFO: Epoch: 4/5, Step: 782/1406, Lr: 0.000000019, Loss: 0.422742, Time/step: 8.914255 2023-05-20 03:28:16,173:INFO: Epoch: 4/5, Step: 832/1406, Lr: 0.000000018, Loss: 0.327376, Time/step: 9.007970 2023-05-20 03:36:05,051:INFO: Epoch: 4/5, Step: 882/1406, Lr: 0.000000017, Loss: 0.388233, Time/step: 9.377542 2023-05-20 03:43:30,074:INFO: Epoch: 4/5, Step: 932/1406, Lr: 0.000000017, Loss: 0.355292, Time/step: 8.900455 2023-05-20 03:51:22,000:INFO: Epoch: 4/5, Step: 982/1406, Lr: 0.000000016, Loss: 0.443264, Time/step: 9.438516 2023-05-20 03:58:56,863:INFO: Epoch: 4/5, Step: 1032/1406, Lr: 0.000000015, Loss: 0.558586, Time/step: 9.097255 2023-05-20 04:06:57,542:INFO: Epoch: 4/5, Step: 1082/1406, Lr: 0.000000014, Loss: 0.402262, Time/step: 9.613570 2023-05-20 04:14:23,790:INFO: Epoch: 4/5, Step: 1132/1406, Lr: 0.000000013, Loss: 0.325344, Time/step: 8.924956 2023-05-20 04:21:47,425:INFO: Epoch: 4/5, Step: 1182/1406, Lr: 0.000000013, Loss: 0.298996, Time/step: 8.872690 2023-05-20 04:29:23,548:INFO: Epoch: 4/5, Step: 1232/1406, Lr: 0.000000012, Loss: 0.260300, Time/step: 9.122445 2023-05-20 04:37:24,587:INFO: Epoch: 4/5, Step: 1282/1406, Lr: 0.000000011, Loss: 0.569869, Time/step: 9.620769 2023-05-20 04:44:48,122:INFO: Epoch: 4/5, Step: 1332/1406, Lr: 0.000000011, Loss: 0.254250, Time/step: 8.870698 2023-05-20 04:52:34,961:INFO: Epoch: 4/5, Step: 1382/1406, Lr: 0.000000010, Loss: 0.270247, Time/step: 9.336778 2023-05-20 04:56:01,163:INFO: Epoch 4/5 Finished, Train Loss: 0.344351 2023-05-20 04:56:02,392:INFO: Model saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.3 2023-05-20 04:56:02,392:INFO: Optimizer saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_opt.bin.3 2023-05-20 05:00:29,556:INFO: sim matrix size: 1000, 1000 2023-05-20 05:00:29,663:INFO: Length-T: 1000, Length-V:1000 2023-05-20 05:00:29,663:INFO: Text-to-Video: 2023-05-20 05:00:29,663:INFO: >>> R@1: 41.7 - R@5: 69.2 - R@10: 78.2 - Median R: 2.0 - Mean R: 17.1 2023-05-20 05:00:29,664:INFO: Video-to-Text: 2023-05-20 05:00:29,664:INFO: >>> R@1: 40.7 - V2T$R@5: 69.2 - V2T$R@10: 79.3 - V2T$Median R: 2.0 - V2T$Mean R: 12.5 2023-05-20 05:00:29,666:INFO: The best model is: /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.2, the R1 is: 42.3000 2023-05-20 05:04:32,703:INFO: Epoch: 5/5, Step: 26/1406, Lr: 0.000000009, Loss: 0.268058, Time/step: 4.855750 2023-05-20 05:11:40,599:INFO: Epoch: 5/5, Step: 76/1406, Lr: 0.000000009, Loss: 0.318149, Time/step: 8.557916 2023-05-20 05:18:21,562:INFO: Epoch: 5/5, Step: 126/1406, Lr: 0.000000008, Loss: 0.227530, Time/step: 8.019245 2023-05-20 05:24:19,969:INFO: Epoch: 5/5, Step: 176/1406, Lr: 0.000000007, Loss: 0.305371, Time/step: 7.168131 2023-05-20 05:30:49,495:INFO: Epoch: 5/5, Step: 226/1406, Lr: 0.000000007, Loss: 0.267840, Time/step: 7.790529 2023-05-20 05:37:04,372:INFO: Epoch: 5/5, Step: 276/1406, Lr: 0.000000006, Loss: 0.294461, Time/step: 7.497534 2023-05-20 05:43:32,197:INFO: Epoch: 5/5, Step: 326/1406, Lr: 0.000000006, Loss: 0.331045, Time/step: 7.756488 2023-05-20 05:49:52,464:INFO: Epoch: 5/5, Step: 376/1406, Lr: 0.000000005, Loss: 0.374437, Time/step: 7.605323 2023-05-20 05:56:24,151:INFO: Epoch: 5/5, Step: 426/1406, Lr: 0.000000005, Loss: 0.259266, Time/step: 7.833743 2023-05-20 06:02:49,412:INFO: Epoch: 5/5, Step: 476/1406, Lr: 0.000000004, Loss: 0.231628, Time/step: 7.705199 2023-05-20 06:09:20,596:INFO: Epoch: 5/5, Step: 526/1406, Lr: 0.000000004, Loss: 0.373177, Time/step: 7.823687 2023-05-20 06:15:54,072:INFO: Epoch: 5/5, Step: 576/1406, Lr: 0.000000003, Loss: 0.372456, Time/step: 7.869518 2023-05-20 06:21:54,616:INFO: Epoch: 5/5, Step: 626/1406, Lr: 0.000000003, Loss: 0.333254, Time/step: 7.210856 2023-05-20 06:28:25,059:INFO: Epoch: 5/5, Step: 676/1406, Lr: 0.000000003, Loss: 0.299849, Time/step: 7.808868 2023-05-20 06:35:01,071:INFO: Epoch: 5/5, Step: 726/1406, Lr: 0.000000002, Loss: 0.387183, Time/step: 7.920228 2023-05-20 06:41:24,759:INFO: Epoch: 5/5, Step: 776/1406, Lr: 0.000000002, Loss: 0.359396, Time/step: 7.673741 2023-05-20 06:47:59,210:INFO: Epoch: 5/5, Step: 826/1406, Lr: 0.000000002, Loss: 0.238666, Time/step: 7.889022 2023-05-20 06:54:19,872:INFO: Epoch: 5/5, Step: 876/1406, Lr: 0.000000001, Loss: 0.282849, Time/step: 7.613236 2023-05-20 07:00:31,396:INFO: Epoch: 5/5, Step: 926/1406, Lr: 0.000000001, Loss: 0.256675, Time/step: 7.430471 2023-05-20 07:07:05,233:INFO: Epoch: 5/5, Step: 976/1406, Lr: 0.000000001, Loss: 0.319373, Time/step: 7.876730 2023-05-20 07:13:26,978:INFO: Epoch: 5/5, Step: 1026/1406, Lr: 0.000000001, Loss: 0.351498, Time/step: 7.634893 2023-05-20 07:20:07,940:INFO: Epoch: 5/5, Step: 1076/1406, Lr: 0.000000001, Loss: 0.309928, Time/step: 8.019224 2023-05-20 07:26:15,935:INFO: Epoch: 5/5, Step: 1126/1406, Lr: 0.000000000, Loss: 0.326648, Time/step: 7.359898 2023-05-20 07:33:00,820:INFO: Epoch: 5/5, Step: 1176/1406, Lr: 0.000000000, Loss: 0.406658, Time/step: 8.097700 2023-05-20 07:39:16,197:INFO: Epoch: 5/5, Step: 1226/1406, Lr: 0.000000000, Loss: 0.374230, Time/step: 7.507528 2023-05-20 07:45:32,190:INFO: Epoch: 5/5, Step: 1276/1406, Lr: 0.000000000, Loss: 0.433072, Time/step: 7.519854 2023-05-20 07:51:52,695:INFO: Epoch: 5/5, Step: 1326/1406, Lr: 0.000000000, Loss: 0.346162, Time/step: 7.610092 2023-05-20 07:58:26,738:INFO: Epoch: 5/5, Step: 1376/1406, Lr: 0.000000000, Loss: 0.307711, Time/step: 7.880854 2023-05-20 08:02:12,375:INFO: Epoch 5/5 Finished, Train Loss: 0.319588 2023-05-20 08:02:13,385:INFO: Model saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.4 2023-05-20 08:02:13,386:INFO: Optimizer saved to /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_opt.bin.4 2023-05-20 08:06:04,102:INFO: sim matrix size: 1000, 1000 2023-05-20 08:06:04,211:INFO: Length-T: 1000, Length-V:1000 2023-05-20 08:06:04,211:INFO: Text-to-Video: 2023-05-20 08:06:04,211:INFO: >>> R@1: 41.6 - R@5: 68.8 - R@10: 78.3 - Median R: 2.0 - Mean R: 17.2 2023-05-20 08:06:04,211:INFO: Video-to-Text: 2023-05-20 08:06:04,211:INFO: >>> R@1: 41.0 - V2T$R@5: 69.0 - V2T$R@10: 79.3 - V2T$Median R: 2.0 - V2T$Mean R: 12.5 2023-05-20 01:21:45,564:INFO: Text-to-Video: 2023-05-20 01:21:45,564:INFO: >>> R@1: 42.3 - R@5: 69.4 - R@10: 79.8 - Median R: 2.0 - Mean R: 16.5 2023-05-20 01:21:45,564:INFO: Video-to-Text: 2023-05-20 01:21:45,564:INFO: >>> R@1: 41.3 - V2T$R@5: 71.1 - V2T$R@10: 80.2 - V2T$Median R: 2.0 - V2T$Mean R: 12.0 2023-05-20 08:06:04,213:INFO: The best model is: /data1/workshop/ckpts/ckpt_msrvtt_retrieval_looseType/pytorch_model.bin.2, the R1 is: 42.3000