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Questions about the transfer learning #1

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ha-lins opened this issue Nov 4, 2021 · 2 comments
Closed

Questions about the transfer learning #1

ha-lins opened this issue Nov 4, 2021 · 2 comments

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@ha-lins
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ha-lins commented Nov 4, 2021

Hi @susheels

Thanks for the great work. I tried to reproduce the transfer learning results of AD-GCL. Concretely, I pretrained the model on the ZINC-2M for 100 epochs, and fine-tuned it on the downstream tasks. However, the reproduced results are lower than ones in the paper. Could you pls help me with it? Thanks!

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@susheels
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susheels commented Nov 4, 2021

Hi @ha-lins
Thanks for looking into our work.
I want to point out that we select the epochs of the pretrain model based on finetune validation. For eg. for SIDER the best pretrain model of ZINC-2M is the one obtained at epoch 50 and not 100. This is mentioned in the appendix of the experiments of our paper (Section G.3 page 23).
image

The same setting style applies to all the finetune datasets.

Below is the logs of one of the runs I had back in May 2021 for SIDER dataset have a look.

/homes/suresh43/ml00_str/graph_infomax
ml07.cs.purdue.edu
Tue May 11 19:47:35 EDT 2021
11-May-21 19:47:39 - Using Device: cuda
11-May-21 19:47:39 - Seed: 5
11-May-21 19:47:39 - Namespace(JK='last', batch_size=32, dataset='sider', decay=0, device=0, dropout_ratio=0.5, emb_dim=300, epochs=100, eval_train=1, gnn_type='gin', graph_pooling='mean', input_model_file='models_minmax/pretrain_minmax_seed_0_reg_5.0_epoch_50.pth', lr=0.001, lr_scale=1, num_layer=5, num_workers=4, seed=5, split='scaffold')
11-May-21 19:47:39 - MoleculeDataset(1427)
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:40] WARNING: not removing hydrogen atom without neighbors
[19:47:41] WARNING: not removing hydrogen atom without neighbors
[19:47:41] WARNING: not removing hydrogen atom without neighbors
[19:47:41] WARNING: not removing hydrogen atom without neighbors
[19:47:41] WARNING: not removing hydrogen atom without neighbors
[19:47:41] WARNING: not removing hydrogen atom without neighbors
11-May-21 19:47:42 - scaffold
11-May-21 19:47:42 - Data(edge_attr=[24, 2], edge_index=[2, 24], id=[1], x=[13, 2], y=[27])

0%| | 0/100 [00:00<?, ?it/s]�[A11-May-21 19:47:46 - ====epoch 1 SupervisedLoss 18.787634556040587
11-May-21 19:47:46 - ====Evaluation
11-May-21 19:47:48 - EvalTrain: 0.5834970329887157 EvalVal: 0.5317982698952236 EvalTestt: 0.5298635606928968

1%| | 1/100 [00:03<05:44, 3.48s/it]�[A11-May-21 19:47:49 - ====epoch 2 SupervisedLoss 16.508571281054856
11-May-21 19:47:49 - ====Evaluation
11-May-21 19:47:51 - EvalTrain: 0.6312587236965638 EvalVal: 0.5470104574502754 EvalTestt: 0.5755410259261043

2%|▏ | 2/100 [00:06<05:24, 3.31s/it]�[A11-May-21 19:47:52 - ====epoch 3 SupervisedLoss 16.22026304471623
11-May-21 19:47:52 - ====Evaluation
11-May-21 19:47:54 - EvalTrain: 0.6345529249955519 EvalVal: 0.5644729973120342 EvalTestt: 0.5841271908482789

3%|▎ | 3/100 [00:09<05:13, 3.23s/it]�[A11-May-21 19:47:55 - ====epoch 4 SupervisedLoss 16.07790184530015
11-May-21 19:47:55 - ====Evaluation
11-May-21 19:47:57 - EvalTrain: 0.6426818804960616 EvalVal: 0.544347936207327 EvalTestt: 0.5929974923684722

4%|▍ | 4/100 [00:13<05:12, 3.25s/it]�[A11-May-21 19:47:59 - ====epoch 5 SupervisedLoss 16.0605042118943
11-May-21 19:47:59 - ====Evaluation
11-May-21 19:48:00 - EvalTrain: 0.6610757965180492 EvalVal: 0.5540083010371094 EvalTestt: 0.5891938144150491

5%|▌ | 5/100 [00:16<04:59, 3.16s/it]�[A11-May-21 19:48:02 - ====epoch 6 SupervisedLoss 15.89915447598688
11-May-21 19:48:02 - ====Evaluation
11-May-21 19:48:04 - EvalTrain: 0.6648138238335342 EvalVal: 0.5614471173124509 EvalTestt: 0.604868080554399

6%|▌ | 6/100 [00:19<04:54, 3.14s/it]�[A11-May-21 19:48:05 - ====epoch 7 SupervisedLoss 15.863118016538762
11-May-21 19:48:05 - ====Evaluation
11-May-21 19:48:07 - EvalTrain: 0.6775711122707491 EvalVal: 0.530661695347536 EvalTestt: 0.6033338550564862

7%|▋ | 7/100 [00:22<04:51, 3.13s/it]�[A11-May-21 19:48:08 - ====epoch 8 SupervisedLoss 15.81241348007394
11-May-21 19:48:08 - ====Evaluation
11-May-21 19:48:10 - EvalTrain: 0.6767125373857309 EvalVal: 0.518649993267393 EvalTestt: 0.6124344924034835

8%|▊ | 8/100 [00:25<04:58, 3.24s/it]�[A11-May-21 19:48:11 - ====epoch 9 SupervisedLoss 15.755560486359222
11-May-21 19:48:11 - ====Evaluation
11-May-21 19:48:13 - EvalTrain: 0.6780509172455981 EvalVal: 0.5510770969855282 EvalTestt: 0.6116191003694207

9%|▉ | 9/100 [00:28<04:48, 3.17s/it]�[A11-May-21 19:48:14 - ====epoch 10 SupervisedLoss 15.809212941899476
11-May-21 19:48:14 - ====Evaluation
11-May-21 19:48:16 - EvalTrain: 0.680854209220189 EvalVal: 0.5343226233257174 EvalTestt: 0.6172805642992728

10%|█ | 10/100 [00:32<04:48, 3.20s/it]�[A11-May-21 19:48:18 - ====epoch 11 SupervisedLoss 15.644014863445364
11-May-21 19:48:18 - ====Evaluation
11-May-21 19:48:20 - EvalTrain: 0.6768979191350648 EvalVal: 0.5161187204509772 EvalTestt: 0.5840646146365441

11%|█ | 11/100 [00:35<04:45, 3.21s/it]�[A11-May-21 19:48:21 - ====epoch 12 SupervisedLoss 15.642255098823917
11-May-21 19:48:21 - ====Evaluation
11-May-21 19:48:23 - EvalTrain: 0.6873137314224697 EvalVal: 0.5551592682575122 EvalTestt: 0.6081414446271919

12%|█▏ | 12/100 [00:38<04:42, 3.21s/it]�[A11-May-21 19:48:24 - ====epoch 13 SupervisedLoss 15.557990836248178
11-May-21 19:48:24 - ====Evaluation
11-May-21 19:48:26 - EvalTrain: 0.6909558701611742 EvalVal: 0.5469324468091391 EvalTestt: 0.6138203094331184

13%|█▎ | 13/100 [00:41<04:38, 3.20s/it]�[A11-May-21 19:48:27 - ====epoch 14 SupervisedLoss 15.608347900409983
11-May-21 19:48:27 - ====Evaluation
11-May-21 19:48:29 - EvalTrain: 0.6948668243122843 EvalVal: 0.5254121391459233 EvalTestt: 0.5948736816696747

14%|█▍ | 14/100 [00:44<04:32, 3.17s/it]�[A11-May-21 19:48:31 - ====epoch 15 SupervisedLoss 15.531131243316297
11-May-21 19:48:31 - ====Evaluation
11-May-21 19:48:32 - EvalTrain: 0.6924351673602739 EvalVal: 0.5249709707249905 EvalTestt: 0.5966611780702509

15%|█▌ | 15/100 [00:48<04:31, 3.20s/it]�[A11-May-21 19:48:34 - ====epoch 16 SupervisedLoss 15.486928382811831
11-May-21 19:48:34 - ====Evaluation
11-May-21 19:48:36 - EvalTrain: 0.6896081605234299 EvalVal: 0.5524850043762258 EvalTestt: 0.6072769759932366

16%|█▌ | 16/100 [00:51<04:30, 3.22s/it]�[A11-May-21 19:48:37 - ====epoch 17 SupervisedLoss 15.597546516023215
11-May-21 19:48:37 - ====Evaluation
11-May-21 19:48:39 - EvalTrain: 0.7000628104748416 EvalVal: 0.5410808023694348 EvalTestt: 0.6115652356965446

17%|█▋ | 17/100 [00:54<04:30, 3.25s/it]�[A11-May-21 19:48:40 - ====epoch 18 SupervisedLoss 15.407873400170397
11-May-21 19:48:40 - ====Evaluation
11-May-21 19:48:42 - EvalTrain: 0.6962134326180128 EvalVal: 0.5491864279582567 EvalTestt: 0.6042435805146945

18%|█▊ | 18/100 [00:57<04:26, 3.24s/it]�[A11-May-21 19:48:43 - ====epoch 19 SupervisedLoss 15.475374019360721
11-May-21 19:48:43 - ====Evaluation
11-May-21 19:48:46 - EvalTrain: 0.7003666519537907 EvalVal: 0.539224884837385 EvalTestt: 0.5992673839640126

19%|█▉ | 19/100 [01:01<04:24, 3.27s/it]�[A11-May-21 19:48:47 - ====epoch 20 SupervisedLoss 15.383067774416993
11-May-21 19:48:47 - ====Evaluation
11-May-21 19:48:49 - EvalTrain: 0.7131793981270751 EvalVal: 0.5499578115591975 EvalTestt: 0.6209579934240752

20%|██ | 20/100 [01:04<04:18, 3.23s/it]�[A11-May-21 19:48:50 - ====epoch 21 SupervisedLoss 15.343951863363356
11-May-21 19:48:50 - ====Evaluation
11-May-21 19:48:52 - EvalTrain: 0.7053674738838311 EvalVal: 0.5436160750517568 EvalTestt: 0.6152766225751718

21%|██ | 21/100 [01:07<04:14, 3.22s/it]�[A11-May-21 19:48:53 - ====epoch 22 SupervisedLoss 15.159712269441762
11-May-21 19:48:53 - ====Evaluation
11-May-21 19:48:55 - EvalTrain: 0.7158507169567355 EvalVal: 0.5570333628888772 EvalTestt: 0.6234560503815062

22%|██▏ | 22/100 [01:10<04:13, 3.25s/it]�[A11-May-21 19:48:56 - ====epoch 23 SupervisedLoss 15.23614637814005
11-May-21 19:48:56 - ====Evaluation
11-May-21 19:48:59 - EvalTrain: 0.7158316600325662 EvalVal: 0.5470156206644765 EvalTestt: 0.6158990426030544

23%|██▎ | 23/100 [01:14<04:15, 3.31s/it]�[A11-May-21 19:49:00 - ====epoch 24 SupervisedLoss 15.240737248879846
11-May-21 19:49:00 - ====Evaluation
11-May-21 19:49:02 - EvalTrain: 0.6928019710076865 EvalVal: 0.5499843802791562 EvalTestt: 0.606507279197745

24%|██▍ | 24/100 [01:17<04:09, 3.29s/it]�[A11-May-21 19:49:03 - ====epoch 25 SupervisedLoss 15.160917929178291
11-May-21 19:49:03 - ====Evaluation
11-May-21 19:49:05 - EvalTrain: 0.7246340885286029 EvalVal: 0.5535866344674791 EvalTestt: 0.625319843420298

25%|██▌ | 25/100 [01:20<04:03, 3.25s/it]�[A11-May-21 19:49:06 - ====epoch 26 SupervisedLoss 15.098900554588381
11-May-21 19:49:06 - ====Evaluation
11-May-21 19:49:08 - EvalTrain: 0.7221362969259507 EvalVal: 0.558700066434879 EvalTestt: 0.6312585307951805

26%|██▌ | 26/100 [01:24<04:02, 3.27s/it]�[A11-May-21 19:49:10 - ====epoch 27 SupervisedLoss 15.09654545632305
11-May-21 19:49:10 - ====Evaluation
11-May-21 19:49:11 - EvalTrain: 0.7283467553307141 EvalVal: 0.5452411818273802 EvalTestt: 0.6248519463793775

27%|██▋ | 27/100 [01:27<03:54, 3.21s/it]�[A11-May-21 19:49:13 - ====epoch 28 SupervisedLoss 14.986827685135836
11-May-21 19:49:13 - ====Evaluation
11-May-21 19:49:14 - EvalTrain: 0.7216514171471105 EvalVal: 0.5718023286259245 EvalTestt: 0.6250699136600929

28%|██▊ | 28/100 [01:30<03:47, 3.15s/it]�[A11-May-21 19:49:16 - ====epoch 29 SupervisedLoss 15.113138310670585
11-May-21 19:49:16 - ====Evaluation
11-May-21 19:49:18 - EvalTrain: 0.7190952102466954 EvalVal: 0.5441468420253069 EvalTestt: 0.622595078585744

29%|██▉ | 29/100 [01:33<03:51, 3.26s/it]�[A11-May-21 19:49:19 - ====epoch 30 SupervisedLoss 14.996733127281253
11-May-21 19:49:19 - ====Evaluation
11-May-21 19:49:21 - EvalTrain: 0.7270194551803775 EvalVal: 0.5728680069228768 EvalTestt: 0.6091856336382555

30%|███ | 30/100 [01:36<03:50, 3.29s/it]�[A11-May-21 19:49:23 - ====epoch 31 SupervisedLoss 15.037395260305544
11-May-21 19:49:23 - ====Evaluation
11-May-21 19:49:24 - EvalTrain: 0.7266058537103269 EvalVal: 0.5618292245720855 EvalTestt: 0.6221120581710655

31%|███ | 31/100 [01:40<03:42, 3.23s/it]�[A11-May-21 19:49:26 - ====epoch 32 SupervisedLoss 14.980603630509117
11-May-21 19:49:26 - ====Evaluation
11-May-21 19:49:28 - EvalTrain: 0.7393407181228063 EvalVal: 0.5767243768293243 EvalTestt: 0.6335038298148074

32%|███▏ | 32/100 [01:43<03:37, 3.20s/it]�[A11-May-21 19:49:29 - ====epoch 33 SupervisedLoss 14.902003250609416
11-May-21 19:49:29 - ====Evaluation
11-May-21 19:49:31 - EvalTrain: 0.7231620887478892 EvalVal: 0.5632099642904012 EvalTestt: 0.6358995146761133

33%|███▎ | 33/100 [01:46<03:37, 3.24s/it]�[A11-May-21 19:49:32 - ====epoch 34 SupervisedLoss 14.972253354764945
11-May-21 19:49:32 - ====Evaluation
11-May-21 19:49:34 - EvalTrain: 0.7356887314608948 EvalVal: 0.5592779953322743 EvalTestt: 0.6214108248089554

34%|███▍ | 34/100 [01:49<03:36, 3.27s/it]�[A11-May-21 19:49:35 - ====epoch 35 SupervisedLoss 14.911906405564357
11-May-21 19:49:35 - ====Evaluation
11-May-21 19:49:37 - EvalTrain: 0.7193288292515986 EvalVal: 0.5275161971190889 EvalTestt: 0.5951109854998481

35%|███▌ | 35/100 [01:53<03:30, 3.24s/it]�[A11-May-21 19:49:39 - ====epoch 36 SupervisedLoss 14.892411711420136
11-May-21 19:49:39 - ====Evaluation
11-May-21 19:49:40 - EvalTrain: 0.7335623457441031 EvalVal: 0.5547366966916008 EvalTestt: 0.6273584897777096

36%|███▌ | 36/100 [01:56<03:23, 3.19s/it]�[A11-May-21 19:49:42 - ====epoch 37 SupervisedLoss 14.737416878693248
11-May-21 19:49:42 - ====Evaluation
11-May-21 19:49:44 - EvalTrain: 0.7326668004911404 EvalVal: 0.5532369236339005 EvalTestt: 0.6080790311836192

37%|███▋ | 37/100 [01:59<03:20, 3.19s/it]�[A11-May-21 19:49:45 - ====epoch 38 SupervisedLoss 14.719005457591866
11-May-21 19:49:45 - ====Evaluation
11-May-21 19:49:47 - EvalTrain: 0.7264402567065593 EvalVal: 0.5481364153996308 EvalTestt: 0.61186418494301

38%|███▊ | 38/100 [02:02<03:16, 3.17s/it]�[A11-May-21 19:49:48 - ====epoch 39 SupervisedLoss 14.658291653610828
11-May-21 19:49:48 - ====Evaluation
11-May-21 19:49:50 - EvalTrain: 0.7451848737511982 EvalVal: 0.5617745835077391 EvalTestt: 0.6312429048577426

39%|███▉ | 39/100 [02:05<03:09, 3.11s/it]�[A11-May-21 19:49:51 - ====epoch 40 SupervisedLoss 14.68131735961904
11-May-21 19:49:51 - ====Evaluation
11-May-21 19:49:53 - EvalTrain: 0.7390960398599915 EvalVal: 0.5733662944473129 EvalTestt: 0.6231254110774972

40%|████ | 40/100 [02:08<03:06, 3.10s/it]�[A11-May-21 19:49:54 - ====epoch 41 SupervisedLoss 14.706226191400352
11-May-21 19:49:54 - ====Evaluation
11-May-21 19:49:56 - EvalTrain: 0.7517882291227823 EvalVal: 0.5699047912865401 EvalTestt: 0.6113543762541249

41%|████ | 41/100 [02:11<03:02, 3.10s/it]�[A11-May-21 19:49:57 - ====epoch 42 SupervisedLoss 14.670052904567521
11-May-21 19:49:57 - ====Evaluation
11-May-21 19:49:59 - EvalTrain: 0.7525400254695412 EvalVal: 0.5634348251331264 EvalTestt: 0.63785692238848

42%|████▏ | 42/100 [02:14<02:59, 3.09s/it]�[A11-May-21 19:50:00 - ====epoch 43 SupervisedLoss 14.671966573549005
11-May-21 19:50:00 - ====Evaluation
11-May-21 19:50:02 - EvalTrain: 0.7351812012224243 EvalVal: 0.562159301069624 EvalTestt: 0.6133306995901995

43%|████▎ | 43/100 [02:17<02:56, 3.10s/it]�[A11-May-21 19:50:03 - ====epoch 44 SupervisedLoss 14.716350321348038
11-May-21 19:50:03 - ====Evaluation
11-May-21 19:50:05 - EvalTrain: 0.7475668576139425 EvalVal: 0.5684940929374684 EvalTestt: 0.6130135770673276

44%|████▍ | 44/100 [02:20<02:53, 3.10s/it]�[A11-May-21 19:50:07 - ====epoch 45 SupervisedLoss 14.497882892417124
11-May-21 19:50:07 - ====Evaluation
11-May-21 19:50:08 - EvalTrain: 0.7578193570017462 EvalVal: 0.5724448034582096 EvalTestt: 0.6378281154157404

45%|████▌ | 45/100 [02:23<02:50, 3.10s/it]�[A11-May-21 19:50:10 - ====epoch 46 SupervisedLoss 14.397162334441425
11-May-21 19:50:10 - ====Evaluation
11-May-21 19:50:12 - EvalTrain: 0.7435935193679902 EvalVal: 0.5544213574147487 EvalTestt: 0.6272666459185531

46%|████▌ | 46/100 [02:27<02:53, 3.21s/it]�[A11-May-21 19:50:13 - ====epoch 47 SupervisedLoss 14.387390130078403
11-May-21 19:50:13 - ====Evaluation
11-May-21 19:50:15 - EvalTrain: 0.7568064727890421 EvalVal: 0.5691263456937025 EvalTestt: 0.6280296845928249

47%|████▋ | 47/100 [02:30<02:46, 3.13s/it]�[A11-May-21 19:50:16 - ====epoch 48 SupervisedLoss 14.559332972926613
11-May-21 19:50:16 - ====Evaluation
11-May-21 19:50:18 - EvalTrain: 0.7563204770100216 EvalVal: 0.567231726593526 EvalTestt: 0.6160326677545016

48%|████▊ | 48/100 [02:33<02:44, 3.17s/it]�[A11-May-21 19:50:19 - ====epoch 49 SupervisedLoss 14.486612283765307
11-May-21 19:50:19 - ====Evaluation
11-May-21 19:50:21 - EvalTrain: 0.7651036537726773 EvalVal: 0.586261287845783 EvalTestt: 0.6106649753289172

49%|████▉ | 49/100 [02:36<02:40, 3.15s/it]�[A11-May-21 19:50:22 - ====epoch 50 SupervisedLoss 14.386493367776247
11-May-21 19:50:22 - ====Evaluation
11-May-21 19:50:24 - EvalTrain: 0.7611909504681199 EvalVal: 0.5735535709045297 EvalTestt: 0.6272522985277347

50%|█████ | 50/100 [02:39<02:38, 3.17s/it]�[A11-May-21 19:50:26 - ====epoch 51 SupervisedLoss 14.299365938779651
11-May-21 19:50:26 - ====Evaluation
11-May-21 19:50:27 - EvalTrain: 0.772796800610913 EvalVal: 0.5657355032984159 EvalTestt: 0.6243941972921581

51%|█████ | 51/100 [02:43<02:35, 3.17s/it]�[A11-May-21 19:50:29 - ====epoch 52 SupervisedLoss 14.267982651887056
11-May-21 19:50:29 - ====Evaluation
11-May-21 19:50:31 - EvalTrain: 0.7689726610500256 EvalVal: 0.58287566600386 EvalTestt: 0.6449881478693359

52%|█████▏ | 52/100 [02:46<02:39, 3.32s/it]�[A11-May-21 19:50:33 - ====epoch 53 SupervisedLoss 14.29237940045764
11-May-21 19:50:33 - ====Evaluation
11-May-21 19:50:35 - EvalTrain: 0.7485082605235632 EvalVal: 0.5884716321925841 EvalTestt: 0.6140266650166756

53%|█████▎ | 53/100 [02:50<02:43, 3.48s/it]�[A11-May-21 19:50:37 - ====epoch 54 SupervisedLoss 14.209567660734805
11-May-21 19:50:37 - ====Evaluation
11-May-21 19:50:39 - EvalTrain: 0.7624059174343908 EvalVal: 0.566371366274373 EvalTestt: 0.6136812348578061

54%|█████▍ | 54/100 [02:54<02:45, 3.59s/it]�[A11-May-21 19:50:40 - ====epoch 55 SupervisedLoss 14.225998414910444
11-May-21 19:50:40 - ====Evaluation
11-May-21 19:50:43 - EvalTrain: 0.760286515084084 EvalVal: 0.5793318862290848 EvalTestt: 0.6086781314465242

55%|█████▌ | 55/100 [02:58<02:45, 3.69s/it]�[A11-May-21 19:50:44 - ====epoch 56 SupervisedLoss 14.175613282011929
11-May-21 19:50:44 - ====Evaluation
11-May-21 19:50:46 - EvalTrain: 0.7722270580480896 EvalVal: 0.5779437130370871 EvalTestt: 0.621753901496375

56%|█████▌ | 56/100 [03:02<02:41, 3.68s/it]�[A11-May-21 19:50:48 - ====epoch 57 SupervisedLoss 14.183977578762198
11-May-21 19:50:48 - ====Evaluation
11-May-21 19:50:50 - EvalTrain: 0.7693870830460915 EvalVal: 0.5767206593805461 EvalTestt: 0.6320305211658231

57%|█████▋ | 57/100 [03:05<02:38, 3.69s/it]�[A11-May-21 19:50:52 - ====epoch 58 SupervisedLoss 14.161599439189812
11-May-21 19:50:52 - ====Evaluation
11-May-21 19:50:54 - EvalTrain: 0.7671091555660792 EvalVal: 0.5508397861713513 EvalTestt: 0.6135178266444266

58%|█████▊ | 58/100 [03:09<02:39, 3.79s/it]�[A11-May-21 19:50:56 - ====epoch 59 SupervisedLoss 14.138932425324583
11-May-21 19:50:56 - ====Evaluation
11-May-21 19:50:58 - EvalTrain: 0.7859365099816801 EvalVal: 0.5696652785350539 EvalTestt: 0.6402926477675831

59%|█████▉ | 59/100 [03:13<02:36, 3.81s/it]�[A11-May-21 19:51:00 - ====epoch 60 SupervisedLoss 14.089436427758649
11-May-21 19:51:00 - ====Evaluation
11-May-21 19:51:02 - EvalTrain: 0.7763873583255567 EvalVal: 0.5701218269432112 EvalTestt: 0.6300995155762671

60%|██████ | 60/100 [03:17<02:29, 3.73s/it]�[A11-May-21 19:51:03 - ====epoch 61 SupervisedLoss 14.211200346391838
11-May-21 19:51:03 - ====Evaluation
11-May-21 19:51:05 - EvalTrain: 0.7740659629926824 EvalVal: 0.572226367953342 EvalTestt: 0.6252115734853968

61%|██████ | 61/100 [03:20<02:18, 3.54s/it]�[A11-May-21 19:51:06 - ====epoch 62 SupervisedLoss 14.194435360630514
11-May-21 19:51:06 - ====Evaluation
11-May-21 19:51:08 - EvalTrain: 0.7668069790696601 EvalVal: 0.5624985455277022 EvalTestt: 0.6279072479085198

62%|██████▏ | 62/100 [03:23<02:10, 3.44s/it]�[A11-May-21 19:51:09 - ====epoch 63 SupervisedLoss 13.925070834497696
11-May-21 19:51:09 - ====Evaluation
11-May-21 19:51:11 - EvalTrain: 0.7595589191814065 EvalVal: 0.5643771459352619 EvalTestt: 0.6096824224128663

63%|██████▎ | 63/100 [03:26<02:06, 3.41s/it]�[A11-May-21 19:51:12 - ====epoch 64 SupervisedLoss 14.040576423600447
11-May-21 19:51:12 - ====Evaluation
11-May-21 19:51:15 - EvalTrain: 0.7737874383145374 EvalVal: 0.59016250117372 EvalTestt: 0.6237175961639921

64%|██████▍ | 64/100 [03:30<02:02, 3.41s/it]�[A11-May-21 19:51:16 - ====epoch 65 SupervisedLoss 13.935986497276364
11-May-21 19:51:16 - ====Evaluation
11-May-21 19:51:18 - EvalTrain: 0.7654112423869494 EvalVal: 0.5805961187980289 EvalTestt: 0.6182643042907444

65%|██████▌ | 65/100 [03:33<02:01, 3.46s/it]�[A11-May-21 19:51:19 - ====epoch 66 SupervisedLoss 14.00164019497465
11-May-21 19:51:19 - ====Evaluation
11-May-21 19:51:21 - EvalTrain: 0.7761472770763492 EvalVal: 0.5755326799556989 EvalTestt: 0.6283797297113831

66%|██████▌ | 66/100 [03:37<01:54, 3.38s/it]�[A11-May-21 19:51:23 - ====epoch 67 SupervisedLoss 13.839374995350823
11-May-21 19:51:23 - ====Evaluation
11-May-21 19:51:25 - EvalTrain: 0.787028234305306 EvalVal: 0.5830977484708618 EvalTestt: 0.6156075201326232

67%|██████▋ | 67/100 [03:40<01:51, 3.37s/it]�[A11-May-21 19:51:26 - ====epoch 68 SupervisedLoss 13.733397700534347
11-May-21 19:51:26 - ====Evaluation
11-May-21 19:51:28 - EvalTrain: 0.7756704431302692 EvalVal: 0.5572174483947567 EvalTestt: 0.6240631619438994

68%|██████▊ | 68/100 [03:43<01:45, 3.31s/it]�[A11-May-21 19:51:29 - ====epoch 69 SupervisedLoss 13.874597523995565
11-May-21 19:51:29 - ====Evaluation
11-May-21 19:51:31 - EvalTrain: 0.7827936422812877 EvalVal: 0.5834833024076713 EvalTestt: 0.6189552946426404

69%|██████▉ | 69/100 [03:46<01:42, 3.30s/it]�[A11-May-21 19:51:32 - ====epoch 70 SupervisedLoss 13.859870608658023
11-May-21 19:51:32 - ====Evaluation
11-May-21 19:51:34 - EvalTrain: 0.7772035543551192 EvalVal: 0.5562097173556559 EvalTestt: 0.6220639040895863

70%|███████ | 70/100 [03:49<01:36, 3.22s/it]�[A11-May-21 19:51:35 - ====epoch 71 SupervisedLoss 13.988290007337532
11-May-21 19:51:35 - ====Evaluation
11-May-21 19:51:37 - EvalTrain: 0.7774790572673099 EvalVal: 0.5815748487920992 EvalTestt: 0.6178393251024248

71%|███████ | 71/100 [03:52<01:32, 3.19s/it]�[A11-May-21 19:51:39 - ====epoch 72 SupervisedLoss 13.956982603065766
11-May-21 19:51:39 - ====Evaluation
11-May-21 19:51:40 - EvalTrain: 0.7632138372264095 EvalVal: 0.5559296594512065 EvalTestt: 0.6313936834823036

72%|███████▏ | 72/100 [03:56<01:28, 3.18s/it]�[A11-May-21 19:51:42 - ====epoch 73 SupervisedLoss 13.844897718849925
11-May-21 19:51:42 - ====Evaluation
11-May-21 19:51:44 - EvalTrain: 0.7944746860142878 EvalVal: 0.5826038471700212 EvalTestt: 0.6296958064198992

73%|███████▎ | 73/100 [03:59<01:26, 3.21s/it]�[A11-May-21 19:51:45 - ====epoch 74 SupervisedLoss 13.625081791092349
11-May-21 19:51:45 - ====Evaluation
11-May-21 19:51:47 - EvalTrain: 0.7920116290290579 EvalVal: 0.5702534580700954 EvalTestt: 0.6369304358198827

74%|███████▍ | 74/100 [04:02<01:25, 3.27s/it]�[A11-May-21 19:51:48 - ====epoch 75 SupervisedLoss 13.71672870737676
11-May-21 19:51:48 - ====Evaluation
11-May-21 19:51:50 - EvalTrain: 0.7846073050604808 EvalVal: 0.5925669996684358 EvalTestt: 0.6141806451675044

75%|███████▌ | 75/100 [04:05<01:20, 3.23s/it]�[A11-May-21 19:51:52 - ====epoch 76 SupervisedLoss 13.81808922766311
11-May-21 19:51:52 - ====Evaluation
11-May-21 19:51:53 - EvalTrain: 0.7880164534465003 EvalVal: 0.5642101838859085 EvalTestt: 0.617483448967328

76%|███████▌ | 76/100 [04:08<01:15, 3.16s/it]�[A11-May-21 19:51:55 - ====epoch 77 SupervisedLoss 13.651492937280413
11-May-21 19:51:55 - ====Evaluation
11-May-21 19:51:57 - EvalTrain: 0.7830535304095457 EvalVal: 0.5753837193054702 EvalTestt: 0.6191564605912695

77%|███████▋ | 77/100 [04:12<01:13, 3.20s/it]�[A11-May-21 19:51:58 - ====epoch 78 SupervisedLoss 13.768365278419289
11-May-21 19:51:58 - ====Evaluation
11-May-21 19:52:00 - EvalTrain: 0.7831957584208503 EvalVal: 0.5579458464584189 EvalTestt: 0.6165957044331771

78%|███████▊ | 78/100 [04:15<01:09, 3.16s/it]�[A11-May-21 19:52:01 - ====epoch 79 SupervisedLoss 13.650499973728957
11-May-21 19:52:01 - ====Evaluation
11-May-21 19:52:03 - EvalTrain: 0.793530995643477 EvalVal: 0.5742479669829718 EvalTestt: 0.6052043567167978

79%|███████▉ | 79/100 [04:18<01:05, 3.11s/it]�[A11-May-21 19:52:04 - ====epoch 80 SupervisedLoss 13.65745620131962
11-May-21 19:52:04 - ====Evaluation
11-May-21 19:52:06 - EvalTrain: 0.7903074696157097 EvalVal: 0.5716051062662324 EvalTestt: 0.6247410466409204

80%|████████ | 80/100 [04:21<01:02, 3.12s/it]�[A11-May-21 19:52:07 - ====epoch 81 SupervisedLoss 13.586460293370036
11-May-21 19:52:07 - ====Evaluation
11-May-21 19:52:09 - EvalTrain: 0.8069382367405997 EvalVal: 0.5781995276748797 EvalTestt: 0.6205431329774245

81%|████████ | 81/100 [04:24<00:59, 3.13s/it]�[A11-May-21 19:52:10 - ====epoch 82 SupervisedLoss 13.462619779802965
11-May-21 19:52:10 - ====Evaluation
11-May-21 19:52:12 - EvalTrain: 0.803339395016876 EvalVal: 0.5692274194699907 EvalTestt: 0.6164653300748967

82%|████████▏ | 82/100 [04:27<00:56, 3.13s/it]�[A11-May-21 19:52:13 - ====epoch 83 SupervisedLoss 13.48700341534857
11-May-21 19:52:13 - ====Evaluation
11-May-21 19:52:15 - EvalTrain: 0.814294528271782 EvalVal: 0.5938072018428157 EvalTestt: 0.6348189012077746

83%|████████▎ | 83/100 [04:30<00:52, 3.09s/it]�[A11-May-21 19:52:16 - ====epoch 84 SupervisedLoss 13.390580403414278
11-May-21 19:52:16 - ====Evaluation
11-May-21 19:52:18 - EvalTrain: 0.8048076135463769 EvalVal: 0.5887557749764462 EvalTestt: 0.6141031567399582

84%|████████▍ | 84/100 [04:34<00:50, 3.15s/it]�[A11-May-21 19:52:20 - ====epoch 85 SupervisedLoss 13.451424490466557
11-May-21 19:52:20 - ====Evaluation
11-May-21 19:52:22 - EvalTrain: 0.7972969466319215 EvalVal: 0.5835519705379464 EvalTestt: 0.6201273831361925

85%|████████▌ | 85/100 [04:37<00:47, 3.19s/it]�[A11-May-21 19:52:23 - ====epoch 86 SupervisedLoss 13.553169155568261
11-May-21 19:52:23 - ====Evaluation
11-May-21 19:52:25 - EvalTrain: 0.8158994460124077 EvalVal: 0.5795682563564607 EvalTestt: 0.635493044308076

86%|████████▌ | 86/100 [04:40<00:43, 3.14s/it]�[A11-May-21 19:52:26 - ====epoch 87 SupervisedLoss 13.390607050167631
11-May-21 19:52:26 - ====Evaluation
11-May-21 19:52:28 - EvalTrain: 0.8116669224127406 EvalVal: 0.5900364126320231 EvalTestt: 0.6319795921681158

87%|████████▋ | 87/100 [04:43<00:40, 3.09s/it]�[A11-May-21 19:52:29 - ====epoch 88 SupervisedLoss 13.320713055410044
11-May-21 19:52:29 - ====Evaluation
11-May-21 19:52:31 - EvalTrain: 0.7893558763338808 EvalVal: 0.5598602730730381 EvalTestt: 0.6076625227576222

88%|████████▊ | 88/100 [04:46<00:36, 3.07s/it]�[A11-May-21 19:52:32 - ====epoch 89 SupervisedLoss 13.315756923158466
11-May-21 19:52:32 - ====Evaluation
11-May-21 19:52:34 - EvalTrain: 0.8108801113798142 EvalVal: 0.5807116640910053 EvalTestt: 0.6214298014545464

89%|████████▉ | 89/100 [04:49<00:33, 3.02s/it]�[A11-May-21 19:52:35 - ====epoch 90 SupervisedLoss 13.266129248540999
11-May-21 19:52:35 - ====Evaluation
11-May-21 19:52:37 - EvalTrain: 0.819059578913338 EvalVal: 0.5874306466526037 EvalTestt: 0.6157329545121952

90%|█████████ | 90/100 [04:52<00:31, 3.12s/it]�[A11-May-21 19:52:38 - ====epoch 91 SupervisedLoss 13.277598076081942
11-May-21 19:52:38 - ====Evaluation
11-May-21 19:52:40 - EvalTrain: 0.8085924838493923 EvalVal: 0.5749377424921173 EvalTestt: 0.6322536142664897

91%|█████████ | 91/100 [04:55<00:28, 3.13s/it]�[A11-May-21 19:52:41 - ====epoch 92 SupervisedLoss 13.089540927184075
11-May-21 19:52:41 - ====Evaluation
11-May-21 19:52:43 - EvalTrain: 0.8121689059735019 EvalVal: 0.5789844619654969 EvalTestt: 0.6026469178444154

92%|█████████▏| 92/100 [04:58<00:24, 3.08s/it]�[A11-May-21 19:52:44 - ====epoch 93 SupervisedLoss 13.0661289249025
11-May-21 19:52:44 - ====Evaluation
11-May-21 19:52:47 - EvalTrain: 0.798047982942188 EvalVal: 0.5623503626388705 EvalTestt: 0.6339104220249909

93%|█████████▎| 93/100 [05:02<00:22, 3.19s/it]�[A11-May-21 19:52:48 - ====epoch 94 SupervisedLoss 13.128356508353091
11-May-21 19:52:48 - ====Evaluation
11-May-21 19:52:50 - EvalTrain: 0.8072732881594128 EvalVal: 0.5870244800318608 EvalTestt: 0.6076527983429645

94%|█████████▍| 94/100 [05:05<00:19, 3.17s/it]�[A11-May-21 19:52:51 - ====epoch 95 SupervisedLoss 13.310802029379651
11-May-21 19:52:51 - ====Evaluation
11-May-21 19:52:53 - EvalTrain: 0.8117216279661063 EvalVal: 0.5890129442947897 EvalTestt: 0.624332993373566

95%|█████████▌| 95/100 [05:08<00:15, 3.11s/it]�[A11-May-21 19:52:54 - ====epoch 96 SupervisedLoss 13.125213457930712
11-May-21 19:52:54 - ====Evaluation
11-May-21 19:52:56 - EvalTrain: 0.8154417168049048 EvalVal: 0.5616500031867498 EvalTestt: 0.633317171430967

96%|█████████▌| 96/100 [05:11<00:12, 3.15s/it]�[A11-May-21 19:52:57 - ====epoch 97 SupervisedLoss 13.091280651211104
11-May-21 19:52:57 - ====Evaluation
11-May-21 19:52:59 - EvalTrain: 0.825077288709053 EvalVal: 0.5632975551092907 EvalTestt: 0.6284317128641612

97%|█████████▋| 97/100 [05:14<00:09, 3.20s/it]�[A11-May-21 19:53:00 - ====epoch 98 SupervisedLoss 13.038309983310134
11-May-21 19:53:00 - ====Evaluation
11-May-21 19:53:02 - EvalTrain: 0.8185565480009993 EvalVal: 0.580538238277872 EvalTestt: 0.62431815023306

98%|█████████▊| 98/100 [05:18<00:06, 3.23s/it]�[A11-May-21 19:53:04 - ====epoch 99 SupervisedLoss 13.01510590830761
11-May-21 19:53:04 - ====Evaluation
11-May-21 19:53:06 - EvalTrain: 0.8176328143135522 EvalVal: 0.5776437332775322 EvalTestt: 0.6214143726343679

99%|█████████▉| 99/100 [05:21<00:03, 3.24s/it]�[A11-May-21 19:53:07 - ====epoch 100 SupervisedLoss 12.952984047359708
11-May-21 19:53:07 - ====Evaluation
11-May-21 19:53:09 - EvalTrain: 0.8108273251038272 EvalVal: 0.5651134259139261 EvalTestt: 0.6155343900557468

100%|██████████| 100/100 [05:24<00:00, 3.27s/it]�[A
100%|██████████| 100/100 [05:24<00:00, 3.25s/it]
11-May-21 19:53:09 - [0.5834970329887157, 0.6312587236965638, 0.6345529249955519, 0.6426818804960616, 0.6610757965180492, 0.6648138238335342, 0.6775711122707491, 0.6767125373857309, 0.6780509172455981, 0.680854209220189, 0.6768979191350648, 0.6873137314224697, 0.6909558701611742, 0.6948668243122843, 0.6924351673602739, 0.6896081605234299, 0.7000628104748416, 0.6962134326180128, 0.7003666519537907, 0.7131793981270751, 0.7053674738838311, 0.7158507169567355, 0.7158316600325662, 0.6928019710076865, 0.7246340885286029, 0.7221362969259507, 0.7283467553307141, 0.7216514171471105, 0.7190952102466954, 0.7270194551803775, 0.7266058537103269, 0.7393407181228063, 0.7231620887478892, 0.7356887314608948, 0.7193288292515986, 0.7335623457441031, 0.7326668004911404, 0.7264402567065593, 0.7451848737511982, 0.7390960398599915, 0.7517882291227823, 0.7525400254695412, 0.7351812012224243, 0.7475668576139425, 0.7578193570017462, 0.7435935193679902, 0.7568064727890421, 0.7563204770100216, 0.7651036537726773, 0.7611909504681199, 0.772796800610913, 0.7689726610500256, 0.7485082605235632, 0.7624059174343908, 0.760286515084084, 0.7722270580480896, 0.7693870830460915, 0.7671091555660792, 0.7859365099816801, 0.7763873583255567, 0.7740659629926824, 0.7668069790696601, 0.7595589191814065, 0.7737874383145374, 0.7654112423869494, 0.7761472770763492, 0.787028234305306, 0.7756704431302692, 0.7827936422812877, 0.7772035543551192, 0.7774790572673099, 0.7632138372264095, 0.7944746860142878, 0.7920116290290579, 0.7846073050604808, 0.7880164534465003, 0.7830535304095457, 0.7831957584208503, 0.793530995643477, 0.7903074696157097, 0.8069382367405997, 0.803339395016876, 0.814294528271782, 0.8048076135463769, 0.7972969466319215, 0.8158994460124077, 0.8116669224127406, 0.7893558763338808, 0.8108801113798142, 0.819059578913338, 0.8085924838493923, 0.8121689059735019, 0.798047982942188, 0.8072732881594128, 0.8117216279661063, 0.8154417168049048, 0.825077288709053, 0.8185565480009993, 0.8176328143135522, 0.8108273251038272]
11-May-21 19:53:09 - [0.5317982698952236, 0.5470104574502754, 0.5644729973120342, 0.544347936207327, 0.5540083010371094, 0.5614471173124509, 0.530661695347536, 0.518649993267393, 0.5510770969855282, 0.5343226233257174, 0.5161187204509772, 0.5551592682575122, 0.5469324468091391, 0.5254121391459233, 0.5249709707249905, 0.5524850043762258, 0.5410808023694348, 0.5491864279582567, 0.539224884837385, 0.5499578115591975, 0.5436160750517568, 0.5570333628888772, 0.5470156206644765, 0.5499843802791562, 0.5535866344674791, 0.558700066434879, 0.5452411818273802, 0.5718023286259245, 0.5441468420253069, 0.5728680069228768, 0.5618292245720855, 0.5767243768293243, 0.5632099642904012, 0.5592779953322743, 0.5275161971190889, 0.5547366966916008, 0.5532369236339005, 0.5481364153996308, 0.5617745835077391, 0.5733662944473129, 0.5699047912865401, 0.5634348251331264, 0.562159301069624, 0.5684940929374684, 0.5724448034582096, 0.5544213574147487, 0.5691263456937025, 0.567231726593526, 0.586261287845783, 0.5735535709045297, 0.5657355032984159, 0.58287566600386, 0.5884716321925841, 0.566371366274373, 0.5793318862290848, 0.5779437130370871, 0.5767206593805461, 0.5508397861713513, 0.5696652785350539, 0.5701218269432112, 0.572226367953342, 0.5624985455277022, 0.5643771459352619, 0.59016250117372, 0.5805961187980289, 0.5755326799556989, 0.5830977484708618, 0.5572174483947567, 0.5834833024076713, 0.5562097173556559, 0.5815748487920992, 0.5559296594512065, 0.5826038471700212, 0.5702534580700954, 0.5925669996684358, 0.5642101838859085, 0.5753837193054702, 0.5579458464584189, 0.5742479669829718, 0.5716051062662324, 0.5781995276748797, 0.5692274194699907, 0.5938072018428157, 0.5887557749764462, 0.5835519705379464, 0.5795682563564607, 0.5900364126320231, 0.5598602730730381, 0.5807116640910053, 0.5874306466526037, 0.5749377424921173, 0.5789844619654969, 0.5623503626388705, 0.5870244800318608, 0.5890129442947897, 0.5616500031867498, 0.5632975551092907, 0.580538238277872, 0.5776437332775322, 0.5651134259139261]
11-May-21 19:53:09 - [0.5298635606928968, 0.5755410259261043, 0.5841271908482789, 0.5929974923684722, 0.5891938144150491, 0.604868080554399, 0.6033338550564862, 0.6124344924034835, 0.6116191003694207, 0.6172805642992728, 0.5840646146365441, 0.6081414446271919, 0.6138203094331184, 0.5948736816696747, 0.5966611780702509, 0.6072769759932366, 0.6115652356965446, 0.6042435805146945, 0.5992673839640126, 0.6209579934240752, 0.6152766225751718, 0.6234560503815062, 0.6158990426030544, 0.606507279197745, 0.625319843420298, 0.6312585307951805, 0.6248519463793775, 0.6250699136600929, 0.622595078585744, 0.6091856336382555, 0.6221120581710655, 0.6335038298148074, 0.6358995146761133, 0.6214108248089554, 0.5951109854998481, 0.6273584897777096, 0.6080790311836192, 0.61186418494301, 0.6312429048577426, 0.6231254110774972, 0.6113543762541249, 0.63785692238848, 0.6133306995901995, 0.6130135770673276, 0.6378281154157404, 0.6272666459185531, 0.6280296845928249, 0.6160326677545016, 0.6106649753289172, 0.6272522985277347, 0.6243941972921581, 0.6449881478693359, 0.6140266650166756, 0.6136812348578061, 0.6086781314465242, 0.621753901496375, 0.6320305211658231, 0.6135178266444266, 0.6402926477675831, 0.6300995155762671, 0.6252115734853968, 0.6279072479085198, 0.6096824224128663, 0.6237175961639921, 0.6182643042907444, 0.6283797297113831, 0.6156075201326232, 0.6240631619438994, 0.6189552946426404, 0.6220639040895863, 0.6178393251024248, 0.6313936834823036, 0.6296958064198992, 0.6369304358198827, 0.6141806451675044, 0.617483448967328, 0.6191564605912695, 0.6165957044331771, 0.6052043567167978, 0.6247410466409204, 0.6205431329774245, 0.6164653300748967, 0.6348189012077746, 0.6141031567399582, 0.6201273831361925, 0.635493044308076, 0.6319795921681158, 0.6076625227576222, 0.6214298014545464, 0.6157329545121952, 0.6322536142664897, 0.6026469178444154, 0.6339104220249909, 0.6076527983429645, 0.624332993373566, 0.633317171430967, 0.6284317128641612, 0.62431815023306, 0.6214143726343679, 0.6155343900557468]
11-May-21 19:53:09 - FinishedTraining!
11-May-21 19:53:09 - BestEpoch: 82
11-May-21 19:53:09 - BestTrainScore: 0.825077288709053
11-May-21 19:53:09 - BestValidationScore: 0.5938072018428157
11-May-21 19:53:09 - FinalTestScore: 0.6348189012077746

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ha-lins commented Nov 9, 2021

Thank you for pointing out this important detail. I will try again.

@ha-lins ha-lins closed this as completed Nov 9, 2021
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