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iamgroot42/train.log

Created February 24, 2019 11:52
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train.log
INFO - 02/22/19 01:59:59 - 0:00:00 - ============ Initialized logger ============
INFO - 02/22/19 01:59:59 - 0:00:00 - adversarial: True
batch_size: 32
cuda: True
dico_build: S2T
dico_eval: default
dico_max_rank: 0
dico_max_size: 0
dico_method: csls_knn_10
dico_min_size: 0
dico_threshold: 0
dis_clip_weights: 0
dis_dropout: 0.0
dis_hid_dim: 2048
dis_input_dropout: 0.1
dis_lambda: 1
dis_layers: 2
dis_most_frequent: 30000
dis_optimizer: sgd,lr=0.1
dis_smooth: 0.1
dis_steps: 5
emb_dim: 300
epoch_size: 1000000
exp_id:
exp_name: masked_exps
exp_path: data/masked_exps/v0mh1v198i
export: txt
lr_decay: 0.98
lr_shrink: 0.5
map_beta: 0.001
map_id_init: True
map_optimizer: sgd,lr=0.1
max_vocab: -1
min_lr: 1e-06
n_epochs: 5
n_refinement: 5
normalize_embeddings: center
seed: 2019
src_emb: data/wiki-news-300d-1M.vec
src_lang: en
tgt_emb: data/masked_embeddings.vec
tgt_lang: meme
verbose: 2
INFO - 02/22/19 01:59:59 - 0:00:00 - The experiment will be stored in data/masked_exps/v0mh1v198i
INFO - 02/22/19 02:01:03 - 0:01:04 - Loaded 830461 pre-trained word embeddings.
INFO - 02/22/19 02:01:36 - 0:01:37 - Loaded 88586 pre-trained word embeddings.
INFO - 02/22/19 02:01:37 - 0:01:38 - ----> ADVERSARIAL TRAINING <----
INFO - 02/22/19 02:01:37 - 0:01:38 - Starting adversarial training epoch 0...
INFO - 02/22/19 02:01:37 - 0:01:38 - 000000 - Discriminator loss: 0.6623 - 1933 samples/s
INFO - 02/22/19 02:01:39 - 0:01:40 - 004000 - Discriminator loss: 0.3660 - 4609 samples/s
INFO - 02/22/19 02:01:40 - 0:01:41 - 008000 - Discriminator loss: 0.3645 - 4878 samples/s
INFO - 02/22/19 02:01:42 - 0:01:43 - 012000 - Discriminator loss: 0.3526 - 4872 samples/s
INFO - 02/22/19 02:01:44 - 0:01:45 - 016000 - Discriminator loss: 0.3500 - 4449 samples/s
INFO - 02/22/19 02:01:46 - 0:01:47 - 020000 - Discriminator loss: 0.3494 - 4193 samples/s
INFO - 02/22/19 02:01:48 - 0:01:49 - 024000 - Discriminator loss: 0.3508 - 4032 samples/s
INFO - 02/22/19 02:01:50 - 0:01:51 - 028000 - Discriminator loss: 0.3502 - 4170 samples/s
INFO - 02/22/19 02:01:51 - 0:01:52 - 032000 - Discriminator loss: 0.3499 - 4411 samples/s
INFO - 02/22/19 02:01:53 - 0:01:54 - 036000 - Discriminator loss: 0.3501 - 4293 samples/s
INFO - 02/22/19 02:01:55 - 0:01:56 - 040000 - Discriminator loss: 0.3477 - 4035 samples/s
INFO - 02/22/19 02:01:57 - 0:01:58 - 044000 - Discriminator loss: 0.3495 - 3948 samples/s
INFO - 02/22/19 02:01:59 - 0:02:00 - 048000 - Discriminator loss: 0.3503 - 4404 samples/s
INFO - 02/22/19 02:02:01 - 0:02:02 - 052000 - Discriminator loss: 0.3496 - 4838 samples/s
INFO - 02/22/19 02:02:02 - 0:02:03 - 056000 - Discriminator loss: 0.3478 - 4842 samples/s
INFO - 02/22/19 02:02:04 - 0:02:05 - 060000 - Discriminator loss: 0.3474 - 4602 samples/s
INFO - 02/22/19 02:02:06 - 0:02:07 - 064000 - Discriminator loss: 0.3488 - 4841 samples/s
INFO - 02/22/19 02:02:07 - 0:02:09 - 068000 - Discriminator loss: 0.3476 - 4536 samples/s
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INFO - 02/22/19 02:06:53 - 0:06:54 - 756000 - Discriminator loss: 0.3275 - 4479 samples/s
INFO - 02/22/19 02:06:54 - 0:06:56 - 760000 - Discriminator loss: 0.3274 - 4874 samples/s
INFO - 02/22/19 02:06:56 - 0:06:57 - 764000 - Discriminator loss: 0.3276 - 4879 samples/s
INFO - 02/22/19 02:06:58 - 0:06:59 - 768000 - Discriminator loss: 0.3270 - 4898 samples/s
INFO - 02/22/19 02:06:59 - 0:07:00 - 772000 - Discriminator loss: 0.3270 - 4878 samples/s
INFO - 02/22/19 02:07:01 - 0:07:02 - 776000 - Discriminator loss: 0.3267 - 4861 samples/s
INFO - 02/22/19 02:07:03 - 0:07:04 - 780000 - Discriminator loss: 0.3270 - 4730 samples/s
INFO - 02/22/19 02:07:04 - 0:07:06 - 784000 - Discriminator loss: 0.3270 - 4686 samples/s
INFO - 02/22/19 02:07:06 - 0:07:07 - 788000 - Discriminator loss: 0.3274 - 4823 samples/s
INFO - 02/22/19 02:07:08 - 0:07:09 - 792000 - Discriminator loss: 0.3269 - 4579 samples/s
INFO - 02/22/19 02:07:09 - 0:07:11 - 796000 - Discriminator loss: 0.3269 - 4655 samples/s
INFO - 02/22/19 02:07:11 - 0:07:12 - 800000 - Discriminator loss: 0.3269 - 4895 samples/s
INFO - 02/22/19 02:07:13 - 0:07:14 - 804000 - Discriminator loss: 0.3271 - 4569 samples/s
INFO - 02/22/19 02:07:15 - 0:07:16 - 808000 - Discriminator loss: 0.3271 - 4550 samples/s
INFO - 02/22/19 02:07:16 - 0:07:17 - 812000 - Discriminator loss: 0.3270 - 4822 samples/s
INFO - 02/22/19 02:07:18 - 0:07:19 - 816000 - Discriminator loss: 0.3272 - 4857 samples/s
INFO - 02/22/19 02:07:20 - 0:07:21 - 820000 - Discriminator loss: 0.3272 - 4906 samples/s
INFO - 02/22/19 02:07:21 - 0:07:22 - 824000 - Discriminator loss: 0.3271 - 4915 samples/s
INFO - 02/22/19 02:07:23 - 0:07:24 - 828000 - Discriminator loss: 0.3270 - 5854 samples/s
INFO - 02/22/19 02:07:24 - 0:07:25 - 832000 - Discriminator loss: 0.3271 - 6025 samples/s
INFO - 02/22/19 02:07:25 - 0:07:26 - 836000 - Discriminator loss: 0.3271 - 7107 samples/s
INFO - 02/22/19 02:07:26 - 0:07:27 - 840000 - Discriminator loss: 0.3270 - 7099 samples/s
INFO - 02/22/19 02:07:27 - 0:07:28 - 844000 - Discriminator loss: 0.3272 - 7095 samples/s
INFO - 02/22/19 02:07:28 - 0:07:30 - 848000 - Discriminator loss: 0.3278 - 7105 samples/s
INFO - 02/22/19 02:07:30 - 0:07:31 - 852000 - Discriminator loss: 0.3277 - 7100 samples/s
INFO - 02/22/19 02:07:31 - 0:07:32 - 856000 - Discriminator loss: 0.3276 - 7104 samples/s
INFO - 02/22/19 02:07:32 - 0:07:33 - 860000 - Discriminator loss: 0.3275 - 7080 samples/s
INFO - 02/22/19 02:07:33 - 0:07:34 - 864000 - Discriminator loss: 0.3275 - 7097 samples/s
INFO - 02/22/19 02:07:34 - 0:07:35 - 868000 - Discriminator loss: 0.3274 - 7079 samples/s
INFO - 02/22/19 02:07:35 - 0:07:36 - 872000 - Discriminator loss: 0.3273 - 7099 samples/s
INFO - 02/22/19 02:07:36 - 0:07:37 - 876000 - Discriminator loss: 0.3273 - 7089 samples/s
INFO - 02/22/19 02:07:37 - 0:07:39 - 880000 - Discriminator loss: 0.3271 - 7104 samples/s
INFO - 02/22/19 02:07:39 - 0:07:40 - 884000 - Discriminator loss: 0.3274 - 7102 samples/s
INFO - 02/22/19 02:07:40 - 0:07:41 - 888000 - Discriminator loss: 0.3272 - 7094 samples/s
INFO - 02/22/19 02:07:41 - 0:07:42 - 892000 - Discriminator loss: 0.3275 - 7098 samples/s
INFO - 02/22/19 02:07:42 - 0:07:43 - 896000 - Discriminator loss: 0.3272 - 7094 samples/s
INFO - 02/22/19 02:07:43 - 0:07:44 - 900000 - Discriminator loss: 0.3275 - 7105 samples/s
INFO - 02/22/19 02:07:44 - 0:07:45 - 904000 - Discriminator loss: 0.3272 - 7079 samples/s
INFO - 02/22/19 02:07:45 - 0:07:46 - 908000 - Discriminator loss: 0.3270 - 7071 samples/s
INFO - 02/22/19 02:07:46 - 0:07:48 - 912000 - Discriminator loss: 0.3272 - 7104 samples/s
INFO - 02/22/19 02:07:48 - 0:07:49 - 916000 - Discriminator loss: 0.3270 - 7106 samples/s
INFO - 02/22/19 02:07:49 - 0:07:50 - 920000 - Discriminator loss: 0.3267 - 7104 samples/s
INFO - 02/22/19 02:07:50 - 0:07:51 - 924000 - Discriminator loss: 0.3269 - 7079 samples/s
INFO - 02/22/19 02:07:51 - 0:07:52 - 928000 - Discriminator loss: 0.3267 - 7103 samples/s
INFO - 02/22/19 02:07:52 - 0:07:53 - 932000 - Discriminator loss: 0.3266 - 7107 samples/s
INFO - 02/22/19 02:07:53 - 0:07:54 - 936000 - Discriminator loss: 0.3271 - 7083 samples/s
INFO - 02/22/19 02:07:54 - 0:07:55 - 940000 - Discriminator loss: 0.3270 - 7102 samples/s
INFO - 02/22/19 02:07:55 - 0:07:57 - 944000 - Discriminator loss: 0.3269 - 7100 samples/s
INFO - 02/22/19 02:07:57 - 0:07:58 - 948000 - Discriminator loss: 0.3270 - 7100 samples/s
INFO - 02/22/19 02:07:58 - 0:07:59 - 952000 - Discriminator loss: 0.3269 - 7089 samples/s
INFO - 02/22/19 02:07:59 - 0:08:00 - 956000 - Discriminator loss: 0.3266 - 7102 samples/s
INFO - 02/22/19 02:08:00 - 0:08:01 - 960000 - Discriminator loss: 0.3264 - 7107 samples/s
INFO - 02/22/19 02:08:01 - 0:08:02 - 964000 - Discriminator loss: 0.3263 - 7095 samples/s
INFO - 02/22/19 02:08:02 - 0:08:03 - 968000 - Discriminator loss: 0.3272 - 7098 samples/s
INFO - 02/22/19 02:08:03 - 0:08:05 - 972000 - Discriminator loss: 0.3270 - 7109 samples/s
INFO - 02/22/19 02:08:04 - 0:08:06 - 976000 - Discriminator loss: 0.3267 - 7079 samples/s
INFO - 02/22/19 02:08:06 - 0:08:07 - 980000 - Discriminator loss: 0.3270 - 7098 samples/s
INFO - 02/22/19 02:08:07 - 0:08:08 - 984000 - Discriminator loss: 0.3270 - 7084 samples/s
INFO - 02/22/19 02:08:08 - 0:08:09 - 988000 - Discriminator loss: 0.3266 - 7099 samples/s
INFO - 02/22/19 02:08:09 - 0:08:10 - 992000 - Discriminator loss: 0.3270 - 7107 samples/s
INFO - 02/22/19 02:08:10 - 0:08:11 - 996000 - Discriminator loss: 0.3269 - 7097 samples/s
INFO - 02/22/19 02:08:26 - 0:08:27 - Building the train dictionary ...
INFO - 02/22/19 02:08:26 - 0:08:27 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:08:26 - 0:08:27 - Mean cosine (nn method, S2T build, 10000 max size): 0.50058
INFO - 02/22/19 02:10:01 - 0:10:02 - Building the train dictionary ...
INFO - 02/22/19 02:10:01 - 0:10:02 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:10:01 - 0:10:02 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.41910
INFO - 02/22/19 02:10:04 - 0:10:06 - Discriminator source / target predictions: 0.93369 / 0.19448
INFO - 02/22/19 02:10:04 - 0:10:06 - Discriminator source / target / global accuracy: 0.99987 / 0.91954 / 0.99213
INFO - 02/22/19 02:10:04 - 0:10:06 - __log__:{"n_epoch": 0, "mean_cosine-nn-S2T-10000": 0.5005826354026794, "mean_cosine-csls_knn_10-S2T-10000": 0.41910287737846375, "dis_accu": 0.9921309791555818, "dis_src_pred": 0.9336927532222188, "dis_tgt_pred": 0.194476096658546}
INFO - 02/22/19 02:10:04 - 0:10:06 - * Best value for "mean_cosine-csls_knn_10-S2T-10000": 0.41910
INFO - 02/22/19 02:10:04 - 0:10:06 - * Saving the mapping to data/masked_exps/v0mh1v198i/best_mapping.pth ...
INFO - 02/22/19 02:10:04 - 0:10:06 - End of epoch 0.
INFO - 02/22/19 02:10:04 - 0:10:06 - Decreasing learning rate: 0.10000000 -> 0.09800000
INFO - 02/22/19 02:10:04 - 0:10:06 - Starting adversarial training epoch 1...
INFO - 02/22/19 02:10:04 - 0:10:06 - 000000 - Discriminator loss: 0.3255 - 4940 samples/s
INFO - 02/22/19 02:10:06 - 0:10:07 - 004000 - Discriminator loss: 0.3266 - 4662 samples/s
INFO - 02/22/19 02:10:08 - 0:10:09 - 008000 - Discriminator loss: 0.3269 - 4891 samples/s
INFO - 02/22/19 02:10:10 - 0:10:11 - 012000 - Discriminator loss: 0.3268 - 4812 samples/s
INFO - 02/22/19 02:10:11 - 0:10:12 - 016000 - Discriminator loss: 0.3273 - 4866 samples/s
INFO - 02/22/19 02:10:13 - 0:10:14 - 020000 - Discriminator loss: 0.3266 - 4922 samples/s
INFO - 02/22/19 02:10:14 - 0:10:16 - 024000 - Discriminator loss: 0.3269 - 4893 samples/s
INFO - 02/22/19 02:10:16 - 0:10:17 - 028000 - Discriminator loss: 0.3269 - 4899 samples/s
INFO - 02/22/19 02:10:18 - 0:10:19 - 032000 - Discriminator loss: 0.3270 - 4869 samples/s
INFO - 02/22/19 02:10:19 - 0:10:21 - 036000 - Discriminator loss: 0.3270 - 4634 samples/s
INFO - 02/22/19 02:10:21 - 0:10:22 - 040000 - Discriminator loss: 0.3269 - 4911 samples/s
INFO - 02/22/19 02:10:23 - 0:10:24 - 044000 - Discriminator loss: 0.3271 - 4903 samples/s
INFO - 02/22/19 02:10:24 - 0:10:25 - 048000 - Discriminator loss: 0.3271 - 4837 samples/s
INFO - 02/22/19 02:10:26 - 0:10:27 - 052000 - Discriminator loss: 0.3270 - 4876 samples/s
INFO - 02/22/19 02:10:28 - 0:10:29 - 056000 - Discriminator loss: 0.3271 - 4896 samples/s
INFO - 02/22/19 02:10:29 - 0:10:30 - 060000 - Discriminator loss: 0.3271 - 4923 samples/s
INFO - 02/22/19 02:10:31 - 0:10:32 - 064000 - Discriminator loss: 0.3269 - 4772 samples/s
INFO - 02/22/19 02:10:33 - 0:10:34 - 068000 - Discriminator loss: 0.3268 - 4913 samples/s
INFO - 02/22/19 02:10:34 - 0:10:35 - 072000 - Discriminator loss: 0.3271 - 4852 samples/s
INFO - 02/22/19 02:10:36 - 0:10:37 - 076000 - Discriminator loss: 0.3270 - 4745 samples/s
INFO - 02/22/19 02:10:38 - 0:10:39 - 080000 - Discriminator loss: 0.3268 - 4701 samples/s
INFO - 02/22/19 02:10:39 - 0:10:40 - 084000 - Discriminator loss: 0.3270 - 4753 samples/s
INFO - 02/22/19 02:10:41 - 0:10:42 - 088000 - Discriminator loss: 0.3270 - 4852 samples/s
INFO - 02/22/19 02:10:43 - 0:10:44 - 092000 - Discriminator loss: 0.3273 - 4925 samples/s
INFO - 02/22/19 02:10:44 - 0:10:45 - 096000 - Discriminator loss: 0.3269 - 4818 samples/s
INFO - 02/22/19 02:10:46 - 0:10:47 - 100000 - Discriminator loss: 0.3268 - 5048 samples/s
INFO - 02/22/19 02:10:47 - 0:10:49 - 104000 - Discriminator loss: 0.3268 - 4759 samples/s
INFO - 02/22/19 02:10:49 - 0:10:50 - 108000 - Discriminator loss: 0.3268 - 4523 samples/s
INFO - 02/22/19 02:10:51 - 0:10:52 - 112000 - Discriminator loss: 0.3271 - 4986 samples/s
INFO - 02/22/19 02:10:53 - 0:10:54 - 116000 - Discriminator loss: 0.3274 - 4731 samples/s
INFO - 02/22/19 02:10:54 - 0:10:55 - 120000 - Discriminator loss: 0.3270 - 4837 samples/s
INFO - 02/22/19 02:10:56 - 0:10:57 - 124000 - Discriminator loss: 0.3267 - 4801 samples/s
INFO - 02/22/19 02:10:57 - 0:10:59 - 128000 - Discriminator loss: 0.3267 - 4912 samples/s
INFO - 02/22/19 02:10:59 - 0:11:00 - 132000 - Discriminator loss: 0.3267 - 4585 samples/s
INFO - 02/22/19 02:11:01 - 0:11:02 - 136000 - Discriminator loss: 0.3267 - 4732 samples/s
INFO - 02/22/19 02:11:03 - 0:11:04 - 140000 - Discriminator loss: 0.3265 - 4838 samples/s
INFO - 02/22/19 02:11:04 - 0:11:05 - 144000 - Discriminator loss: 0.3267 - 4823 samples/s
INFO - 02/22/19 02:11:06 - 0:11:07 - 148000 - Discriminator loss: 0.3269 - 4645 samples/s
INFO - 02/22/19 02:11:08 - 0:11:09 - 152000 - Discriminator loss: 0.3265 - 4781 samples/s
INFO - 02/22/19 02:11:09 - 0:11:10 - 156000 - Discriminator loss: 0.3266 - 4825 samples/s
INFO - 02/22/19 02:11:11 - 0:11:12 - 160000 - Discriminator loss: 0.3268 - 4845 samples/s
INFO - 02/22/19 02:11:13 - 0:11:14 - 164000 - Discriminator loss: 0.3266 - 4891 samples/s
INFO - 02/22/19 02:11:14 - 0:11:15 - 168000 - Discriminator loss: 0.3266 - 4913 samples/s
INFO - 02/22/19 02:11:16 - 0:11:17 - 172000 - Discriminator loss: 0.3267 - 4642 samples/s
INFO - 02/22/19 02:11:18 - 0:11:19 - 176000 - Discriminator loss: 0.3265 - 4690 samples/s
INFO - 02/22/19 02:11:19 - 0:11:20 - 180000 - Discriminator loss: 0.3264 - 4682 samples/s
INFO - 02/22/19 02:11:21 - 0:11:22 - 184000 - Discriminator loss: 0.3266 - 4894 samples/s
INFO - 02/22/19 02:11:23 - 0:11:24 - 188000 - Discriminator loss: 0.3266 - 4797 samples/s
INFO - 02/22/19 02:11:24 - 0:11:25 - 192000 - Discriminator loss: 0.3269 - 4811 samples/s
INFO - 02/22/19 02:11:26 - 0:11:27 - 196000 - Discriminator loss: 0.3267 - 4678 samples/s
INFO - 02/22/19 02:11:28 - 0:11:29 - 200000 - Discriminator loss: 0.3265 - 4851 samples/s
INFO - 02/22/19 02:11:29 - 0:11:30 - 204000 - Discriminator loss: 0.3264 - 4703 samples/s
INFO - 02/22/19 02:11:31 - 0:11:32 - 208000 - Discriminator loss: 0.3266 - 4796 samples/s
INFO - 02/22/19 02:11:33 - 0:11:34 - 212000 - Discriminator loss: 0.3264 - 4842 samples/s
INFO - 02/22/19 02:11:34 - 0:11:35 - 216000 - Discriminator loss: 0.3262 - 4870 samples/s
INFO - 02/22/19 02:11:36 - 0:11:37 - 220000 - Discriminator loss: 0.3263 - 4877 samples/s
INFO - 02/22/19 02:11:38 - 0:11:39 - 224000 - Discriminator loss: 0.3262 - 4906 samples/s
INFO - 02/22/19 02:11:39 - 0:11:40 - 228000 - Discriminator loss: 0.3261 - 4900 samples/s
INFO - 02/22/19 02:11:41 - 0:11:42 - 232000 - Discriminator loss: 0.3263 - 5244 samples/s
INFO - 02/22/19 02:11:42 - 0:11:43 - 236000 - Discriminator loss: 0.3261 - 5878 samples/s
INFO - 02/22/19 02:11:43 - 0:11:45 - 240000 - Discriminator loss: 0.3262 - 5957 samples/s
INFO - 02/22/19 02:11:45 - 0:11:46 - 244000 - Discriminator loss: 0.3263 - 5937 samples/s
INFO - 02/22/19 02:11:46 - 0:11:47 - 248000 - Discriminator loss: 0.3262 - 5889 samples/s
INFO - 02/22/19 02:11:47 - 0:11:49 - 252000 - Discriminator loss: 0.3262 - 5947 samples/s
INFO - 02/22/19 02:11:49 - 0:11:50 - 256000 - Discriminator loss: 0.3261 - 5871 samples/s
INFO - 02/22/19 02:11:51 - 0:11:52 - 260000 - Discriminator loss: 0.3261 - 4675 samples/s
INFO - 02/22/19 02:11:52 - 0:11:53 - 264000 - Discriminator loss: 0.3260 - 4906 samples/s
INFO - 02/22/19 02:11:54 - 0:11:55 - 268000 - Discriminator loss: 0.3260 - 4655 samples/s
INFO - 02/22/19 02:11:56 - 0:11:57 - 272000 - Discriminator loss: 0.3263 - 4736 samples/s
INFO - 02/22/19 02:11:57 - 0:11:58 - 276000 - Discriminator loss: 0.3263 - 4708 samples/s
INFO - 02/22/19 02:11:59 - 0:12:00 - 280000 - Discriminator loss: 0.3260 - 4828 samples/s
INFO - 02/22/19 02:12:01 - 0:12:02 - 284000 - Discriminator loss: 0.3259 - 4392 samples/s
INFO - 02/22/19 02:12:03 - 0:12:04 - 288000 - Discriminator loss: 0.3262 - 4387 samples/s
INFO - 02/22/19 02:12:04 - 0:12:06 - 292000 - Discriminator loss: 0.3260 - 4578 samples/s
INFO - 02/22/19 02:12:06 - 0:12:07 - 296000 - Discriminator loss: 0.3262 - 4816 samples/s
INFO - 02/22/19 02:12:08 - 0:12:09 - 300000 - Discriminator loss: 0.3260 - 4886 samples/s
INFO - 02/22/19 02:12:09 - 0:12:10 - 304000 - Discriminator loss: 0.3264 - 4817 samples/s
INFO - 02/22/19 02:12:11 - 0:12:12 - 308000 - Discriminator loss: 0.3263 - 4874 samples/s
INFO - 02/22/19 02:12:13 - 0:12:14 - 312000 - Discriminator loss: 0.3262 - 4838 samples/s
INFO - 02/22/19 02:12:14 - 0:12:15 - 316000 - Discriminator loss: 0.3262 - 4868 samples/s
INFO - 02/22/19 02:12:16 - 0:12:17 - 320000 - Discriminator loss: 0.3262 - 4785 samples/s
INFO - 02/22/19 02:12:18 - 0:12:19 - 324000 - Discriminator loss: 0.3263 - 4749 samples/s
INFO - 02/22/19 02:12:19 - 0:12:20 - 328000 - Discriminator loss: 0.3264 - 4907 samples/s
INFO - 02/22/19 02:12:21 - 0:12:22 - 332000 - Discriminator loss: 0.3264 - 4540 samples/s
INFO - 02/22/19 02:12:23 - 0:12:24 - 336000 - Discriminator loss: 0.3265 - 4863 samples/s
INFO - 02/22/19 02:12:24 - 0:12:25 - 340000 - Discriminator loss: 0.3265 - 4873 samples/s
INFO - 02/22/19 02:12:26 - 0:12:27 - 344000 - Discriminator loss: 0.3266 - 4866 samples/s
INFO - 02/22/19 02:12:28 - 0:12:29 - 348000 - Discriminator loss: 0.3262 - 4634 samples/s
INFO - 02/22/19 02:12:29 - 0:12:30 - 352000 - Discriminator loss: 0.3265 - 4881 samples/s
INFO - 02/22/19 02:12:31 - 0:12:32 - 356000 - Discriminator loss: 0.3265 - 4861 samples/s
INFO - 02/22/19 02:12:33 - 0:12:34 - 360000 - Discriminator loss: 0.3265 - 4474 samples/s
INFO - 02/22/19 02:12:34 - 0:12:36 - 364000 - Discriminator loss: 0.3264 - 4877 samples/s
INFO - 02/22/19 02:12:36 - 0:12:37 - 368000 - Discriminator loss: 0.3262 - 4713 samples/s
INFO - 02/22/19 02:12:38 - 0:12:39 - 372000 - Discriminator loss: 0.3264 - 4796 samples/s
INFO - 02/22/19 02:12:39 - 0:12:41 - 376000 - Discriminator loss: 0.3266 - 4757 samples/s
INFO - 02/22/19 02:12:41 - 0:12:42 - 380000 - Discriminator loss: 0.3264 - 4707 samples/s
INFO - 02/22/19 02:12:43 - 0:12:44 - 384000 - Discriminator loss: 0.3265 - 4734 samples/s
INFO - 02/22/19 02:12:45 - 0:12:46 - 388000 - Discriminator loss: 0.3265 - 4703 samples/s
INFO - 02/22/19 02:12:46 - 0:12:47 - 392000 - Discriminator loss: 0.3266 - 4672 samples/s
INFO - 02/22/19 02:12:48 - 0:12:49 - 396000 - Discriminator loss: 0.3265 - 4717 samples/s
INFO - 02/22/19 02:12:50 - 0:12:51 - 400000 - Discriminator loss: 0.3264 - 4588 samples/s
INFO - 02/22/19 02:12:51 - 0:12:52 - 404000 - Discriminator loss: 0.3264 - 4818 samples/s
INFO - 02/22/19 02:12:53 - 0:12:54 - 408000 - Discriminator loss: 0.3265 - 4783 samples/s
INFO - 02/22/19 02:12:55 - 0:12:56 - 412000 - Discriminator loss: 0.3262 - 4704 samples/s
INFO - 02/22/19 02:12:56 - 0:12:58 - 416000 - Discriminator loss: 0.3264 - 4788 samples/s
INFO - 02/22/19 02:12:58 - 0:12:59 - 420000 - Discriminator loss: 0.3264 - 4821 samples/s
INFO - 02/22/19 02:13:00 - 0:13:01 - 424000 - Discriminator loss: 0.3261 - 4908 samples/s
INFO - 02/22/19 02:13:01 - 0:13:02 - 428000 - Discriminator loss: 0.3263 - 4931 samples/s
INFO - 02/22/19 02:13:03 - 0:13:04 - 432000 - Discriminator loss: 0.3260 - 4604 samples/s
INFO - 02/22/19 02:13:05 - 0:13:06 - 436000 - Discriminator loss: 0.3262 - 4907 samples/s
INFO - 02/22/19 02:13:06 - 0:13:08 - 440000 - Discriminator loss: 0.3264 - 4597 samples/s
INFO - 02/22/19 02:13:08 - 0:13:09 - 444000 - Discriminator loss: 0.3260 - 4857 samples/s
INFO - 02/22/19 02:13:10 - 0:13:11 - 448000 - Discriminator loss: 0.3261 - 4888 samples/s
INFO - 02/22/19 02:13:11 - 0:13:12 - 452000 - Discriminator loss: 0.3261 - 4873 samples/s
INFO - 02/22/19 02:13:13 - 0:13:14 - 456000 - Discriminator loss: 0.3262 - 4818 samples/s
INFO - 02/22/19 02:13:15 - 0:13:16 - 460000 - Discriminator loss: 0.3262 - 4883 samples/s
INFO - 02/22/19 02:13:16 - 0:13:17 - 464000 - Discriminator loss: 0.3259 - 4879 samples/s
INFO - 02/22/19 02:13:18 - 0:13:19 - 468000 - Discriminator loss: 0.3261 - 4605 samples/s
INFO - 02/22/19 02:13:20 - 0:13:21 - 472000 - Discriminator loss: 0.3262 - 4786 samples/s
INFO - 02/22/19 02:13:21 - 0:13:22 - 476000 - Discriminator loss: 0.3261 - 4839 samples/s
INFO - 02/22/19 02:13:23 - 0:13:24 - 480000 - Discriminator loss: 0.3262 - 4861 samples/s
INFO - 02/22/19 02:13:25 - 0:13:26 - 484000 - Discriminator loss: 0.3262 - 5073 samples/s
INFO - 02/22/19 02:13:26 - 0:13:27 - 488000 - Discriminator loss: 0.3259 - 4507 samples/s
INFO - 02/22/19 02:13:28 - 0:13:29 - 492000 - Discriminator loss: 0.3262 - 4893 samples/s
INFO - 02/22/19 02:13:30 - 0:13:31 - 496000 - Discriminator loss: 0.3261 - 4657 samples/s
INFO - 02/22/19 02:13:31 - 0:13:32 - 500000 - Discriminator loss: 0.3261 - 4924 samples/s
INFO - 02/22/19 02:13:33 - 0:13:34 - 504000 - Discriminator loss: 0.3263 - 4862 samples/s
INFO - 02/22/19 02:13:35 - 0:13:36 - 508000 - Discriminator loss: 0.3260 - 4681 samples/s
INFO - 02/22/19 02:13:36 - 0:13:38 - 512000 - Discriminator loss: 0.3259 - 4749 samples/s
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INFO - 02/22/19 02:13:52 - 0:13:53 - 548000 - Discriminator loss: 0.3260 - 4745 samples/s
INFO - 02/22/19 02:13:53 - 0:13:54 - 552000 - Discriminator loss: 0.3259 - 4759 samples/s
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INFO - 02/22/19 02:13:57 - 0:13:58 - 560000 - Discriminator loss: 0.3258 - 4876 samples/s
INFO - 02/22/19 02:13:58 - 0:13:59 - 564000 - Discriminator loss: 0.3257 - 4858 samples/s
INFO - 02/22/19 02:14:00 - 0:14:01 - 568000 - Discriminator loss: 0.3258 - 4847 samples/s
INFO - 02/22/19 02:14:02 - 0:14:03 - 572000 - Discriminator loss: 0.3258 - 4885 samples/s
INFO - 02/22/19 02:14:03 - 0:14:04 - 576000 - Discriminator loss: 0.3258 - 4681 samples/s
INFO - 02/22/19 02:14:05 - 0:14:06 - 580000 - Discriminator loss: 0.3256 - 4802 samples/s
INFO - 02/22/19 02:14:07 - 0:14:08 - 584000 - Discriminator loss: 0.3257 - 4722 samples/s
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INFO - 02/22/19 02:14:12 - 0:14:13 - 596000 - Discriminator loss: 0.3256 - 4869 samples/s
INFO - 02/22/19 02:14:13 - 0:14:14 - 600000 - Discriminator loss: 0.3257 - 4777 samples/s
INFO - 02/22/19 02:14:15 - 0:14:16 - 604000 - Discriminator loss: 0.3257 - 4770 samples/s
INFO - 02/22/19 02:14:17 - 0:14:18 - 608000 - Discriminator loss: 0.3256 - 4666 samples/s
INFO - 02/22/19 02:14:18 - 0:14:20 - 612000 - Discriminator loss: 0.3255 - 4807 samples/s
INFO - 02/22/19 02:14:20 - 0:14:21 - 616000 - Discriminator loss: 0.3256 - 4639 samples/s
INFO - 02/22/19 02:14:22 - 0:14:23 - 620000 - Discriminator loss: 0.3255 - 4784 samples/s
INFO - 02/22/19 02:14:23 - 0:14:25 - 624000 - Discriminator loss: 0.3256 - 4640 samples/s
INFO - 02/22/19 02:14:25 - 0:14:26 - 628000 - Discriminator loss: 0.3255 - 4674 samples/s
INFO - 02/22/19 02:14:27 - 0:14:28 - 632000 - Discriminator loss: 0.3255 - 4823 samples/s
INFO - 02/22/19 02:14:29 - 0:14:30 - 636000 - Discriminator loss: 0.3255 - 4856 samples/s
INFO - 02/22/19 02:14:30 - 0:14:31 - 640000 - Discriminator loss: 0.3256 - 4893 samples/s
INFO - 02/22/19 02:14:32 - 0:14:33 - 644000 - Discriminator loss: 0.3254 - 4840 samples/s
INFO - 02/22/19 02:14:33 - 0:14:35 - 648000 - Discriminator loss: 0.3255 - 4877 samples/s
INFO - 02/22/19 02:14:35 - 0:14:36 - 652000 - Discriminator loss: 0.3256 - 4882 samples/s
INFO - 02/22/19 02:14:37 - 0:14:38 - 656000 - Discriminator loss: 0.3256 - 4953 samples/s
INFO - 02/22/19 02:14:38 - 0:14:40 - 660000 - Discriminator loss: 0.3255 - 4791 samples/s
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INFO - 02/22/19 02:14:42 - 0:14:43 - 668000 - Discriminator loss: 0.3255 - 4645 samples/s
INFO - 02/22/19 02:14:43 - 0:14:45 - 672000 - Discriminator loss: 0.3254 - 4863 samples/s
INFO - 02/22/19 02:14:45 - 0:14:46 - 676000 - Discriminator loss: 0.3255 - 4891 samples/s
INFO - 02/22/19 02:14:47 - 0:14:48 - 680000 - Discriminator loss: 0.3254 - 4818 samples/s
INFO - 02/22/19 02:14:48 - 0:14:49 - 684000 - Discriminator loss: 0.3255 - 4891 samples/s
INFO - 02/22/19 02:14:50 - 0:14:51 - 688000 - Discriminator loss: 0.3255 - 4901 samples/s
INFO - 02/22/19 02:14:52 - 0:14:53 - 692000 - Discriminator loss: 0.3255 - 4837 samples/s
INFO - 02/22/19 02:14:53 - 0:14:54 - 696000 - Discriminator loss: 0.3256 - 4876 samples/s
INFO - 02/22/19 02:14:55 - 0:14:56 - 700000 - Discriminator loss: 0.3256 - 4837 samples/s
INFO - 02/22/19 02:14:57 - 0:14:58 - 704000 - Discriminator loss: 0.3255 - 4835 samples/s
INFO - 02/22/19 02:14:58 - 0:14:59 - 708000 - Discriminator loss: 0.3256 - 4818 samples/s
INFO - 02/22/19 02:15:00 - 0:15:01 - 712000 - Discriminator loss: 0.3254 - 4775 samples/s
INFO - 02/22/19 02:15:02 - 0:15:03 - 716000 - Discriminator loss: 0.3255 - 4880 samples/s
INFO - 02/22/19 02:15:03 - 0:15:04 - 720000 - Discriminator loss: 0.3254 - 4803 samples/s
INFO - 02/22/19 02:15:05 - 0:15:06 - 724000 - Discriminator loss: 0.3254 - 4922 samples/s
INFO - 02/22/19 02:15:06 - 0:15:08 - 728000 - Discriminator loss: 0.3254 - 4880 samples/s
INFO - 02/22/19 02:15:08 - 0:15:09 - 732000 - Discriminator loss: 0.3254 - 4872 samples/s
INFO - 02/22/19 02:15:10 - 0:15:11 - 736000 - Discriminator loss: 0.3254 - 4873 samples/s
INFO - 02/22/19 02:15:11 - 0:15:13 - 740000 - Discriminator loss: 0.3254 - 4721 samples/s
INFO - 02/22/19 02:15:13 - 0:15:14 - 744000 - Discriminator loss: 0.3253 - 4905 samples/s
INFO - 02/22/19 02:15:15 - 0:15:16 - 748000 - Discriminator loss: 0.3254 - 4751 samples/s
INFO - 02/22/19 02:15:16 - 0:15:18 - 752000 - Discriminator loss: 0.3254 - 4615 samples/s
INFO - 02/22/19 02:15:18 - 0:15:19 - 756000 - Discriminator loss: 0.3254 - 4882 samples/s
INFO - 02/22/19 02:15:20 - 0:15:21 - 760000 - Discriminator loss: 0.3254 - 4900 samples/s
INFO - 02/22/19 02:15:21 - 0:15:23 - 764000 - Discriminator loss: 0.3254 - 4836 samples/s
INFO - 02/22/19 02:15:23 - 0:15:24 - 768000 - Discriminator loss: 0.3254 - 4871 samples/s
INFO - 02/22/19 02:15:25 - 0:15:26 - 772000 - Discriminator loss: 0.3254 - 4869 samples/s
INFO - 02/22/19 02:15:26 - 0:15:28 - 776000 - Discriminator loss: 0.3253 - 4893 samples/s
INFO - 02/22/19 02:15:28 - 0:15:29 - 780000 - Discriminator loss: 0.3254 - 4802 samples/s
INFO - 02/22/19 02:15:30 - 0:15:31 - 784000 - Discriminator loss: 0.3253 - 4624 samples/s
INFO - 02/22/19 02:15:31 - 0:15:33 - 788000 - Discriminator loss: 0.3253 - 4572 samples/s
INFO - 02/22/19 02:15:33 - 0:15:34 - 792000 - Discriminator loss: 0.3253 - 4815 samples/s
INFO - 02/22/19 02:15:35 - 0:15:36 - 796000 - Discriminator loss: 0.3253 - 4820 samples/s
INFO - 02/22/19 02:15:36 - 0:15:38 - 800000 - Discriminator loss: 0.3253 - 4874 samples/s
INFO - 02/22/19 02:15:38 - 0:15:39 - 804000 - Discriminator loss: 0.3252 - 4863 samples/s
INFO - 02/22/19 02:15:40 - 0:15:41 - 808000 - Discriminator loss: 0.3253 - 4831 samples/s
INFO - 02/22/19 02:15:41 - 0:15:43 - 812000 - Discriminator loss: 0.3252 - 4879 samples/s
INFO - 02/22/19 02:15:43 - 0:15:44 - 816000 - Discriminator loss: 0.3252 - 4802 samples/s
INFO - 02/22/19 02:15:45 - 0:15:46 - 820000 - Discriminator loss: 0.3252 - 4673 samples/s
INFO - 02/22/19 02:15:46 - 0:15:48 - 824000 - Discriminator loss: 0.3252 - 4904 samples/s
INFO - 02/22/19 02:15:48 - 0:15:49 - 828000 - Discriminator loss: 0.3252 - 4891 samples/s
INFO - 02/22/19 02:15:50 - 0:15:51 - 832000 - Discriminator loss: 0.3252 - 4853 samples/s
INFO - 02/22/19 02:15:51 - 0:15:52 - 836000 - Discriminator loss: 0.3252 - 4850 samples/s
INFO - 02/22/19 02:15:53 - 0:15:54 - 840000 - Discriminator loss: 0.3252 - 4897 samples/s
INFO - 02/22/19 02:15:55 - 0:15:56 - 844000 - Discriminator loss: 0.3252 - 4845 samples/s
INFO - 02/22/19 02:15:56 - 0:15:57 - 848000 - Discriminator loss: 0.3252 - 4766 samples/s
INFO - 02/22/19 02:15:58 - 0:15:59 - 852000 - Discriminator loss: 0.3252 - 4832 samples/s
INFO - 02/22/19 02:16:00 - 0:16:01 - 856000 - Discriminator loss: 0.3252 - 4894 samples/s
INFO - 02/22/19 02:16:01 - 0:16:02 - 860000 - Discriminator loss: 0.3252 - 4580 samples/s
INFO - 02/22/19 02:16:03 - 0:16:04 - 864000 - Discriminator loss: 0.3252 - 4883 samples/s
INFO - 02/22/19 02:16:05 - 0:16:06 - 868000 - Discriminator loss: 0.3252 - 4851 samples/s
INFO - 02/22/19 02:16:06 - 0:16:07 - 872000 - Discriminator loss: 0.3252 - 4893 samples/s
INFO - 02/22/19 02:16:08 - 0:16:09 - 876000 - Discriminator loss: 0.3252 - 4837 samples/s
INFO - 02/22/19 02:16:10 - 0:16:11 - 880000 - Discriminator loss: 0.3252 - 4884 samples/s
INFO - 02/22/19 02:16:11 - 0:16:12 - 884000 - Discriminator loss: 0.3252 - 4880 samples/s
INFO - 02/22/19 02:16:13 - 0:16:14 - 888000 - Discriminator loss: 0.3252 - 4786 samples/s
INFO - 02/22/19 02:16:14 - 0:16:16 - 892000 - Discriminator loss: 0.3252 - 4881 samples/s
INFO - 02/22/19 02:16:16 - 0:16:17 - 896000 - Discriminator loss: 0.3252 - 4856 samples/s
INFO - 02/22/19 02:16:18 - 0:16:19 - 900000 - Discriminator loss: 0.3252 - 4920 samples/s
INFO - 02/22/19 02:16:19 - 0:16:21 - 904000 - Discriminator loss: 0.3252 - 4794 samples/s
INFO - 02/22/19 02:16:21 - 0:16:22 - 908000 - Discriminator loss: 0.3252 - 4734 samples/s
INFO - 02/22/19 02:16:23 - 0:16:24 - 912000 - Discriminator loss: 0.3252 - 4982 samples/s
INFO - 02/22/19 02:16:24 - 0:16:25 - 916000 - Discriminator loss: 0.3252 - 5909 samples/s
INFO - 02/22/19 02:16:25 - 0:16:27 - 920000 - Discriminator loss: 0.3252 - 5996 samples/s
INFO - 02/22/19 02:16:27 - 0:16:28 - 924000 - Discriminator loss: 0.3252 - 5945 samples/s
INFO - 02/22/19 02:16:28 - 0:16:29 - 928000 - Discriminator loss: 0.3252 - 5926 samples/s
INFO - 02/22/19 02:16:29 - 0:16:31 - 932000 - Discriminator loss: 0.3252 - 5889 samples/s
INFO - 02/22/19 02:16:31 - 0:16:32 - 936000 - Discriminator loss: 0.3252 - 5859 samples/s
INFO - 02/22/19 02:16:33 - 0:16:34 - 940000 - Discriminator loss: 0.3252 - 4778 samples/s
INFO - 02/22/19 02:16:34 - 0:16:35 - 944000 - Discriminator loss: 0.3252 - 4928 samples/s
INFO - 02/22/19 02:16:36 - 0:16:37 - 948000 - Discriminator loss: 0.3252 - 5731 samples/s
INFO - 02/22/19 02:16:37 - 0:16:38 - 952000 - Discriminator loss: 0.3252 - 5966 samples/s
INFO - 02/22/19 02:16:38 - 0:16:39 - 956000 - Discriminator loss: 0.3252 - 5932 samples/s
INFO - 02/22/19 02:16:40 - 0:16:41 - 960000 - Discriminator loss: 0.3252 - 5355 samples/s
INFO - 02/22/19 02:16:41 - 0:16:43 - 964000 - Discriminator loss: 0.3252 - 4859 samples/s
INFO - 02/22/19 02:16:43 - 0:16:44 - 968000 - Discriminator loss: 0.3252 - 4427 samples/s
INFO - 02/22/19 02:16:45 - 0:16:46 - 972000 - Discriminator loss: 0.3252 - 4829 samples/s
INFO - 02/22/19 02:16:46 - 0:16:48 - 976000 - Discriminator loss: 0.3252 - 4839 samples/s
INFO - 02/22/19 02:16:48 - 0:16:49 - 980000 - Discriminator loss: 0.3252 - 4432 samples/s
INFO - 02/22/19 02:16:50 - 0:16:51 - 984000 - Discriminator loss: 0.3252 - 4709 samples/s
INFO - 02/22/19 02:16:52 - 0:16:53 - 988000 - Discriminator loss: 0.3252 - 4872 samples/s
INFO - 02/22/19 02:16:53 - 0:16:54 - 992000 - Discriminator loss: 0.3252 - 4921 samples/s
INFO - 02/22/19 02:16:55 - 0:16:56 - 996000 - Discriminator loss: 0.3252 - 4852 samples/s
INFO - 02/22/19 02:17:12 - 0:17:13 - Building the train dictionary ...
INFO - 02/22/19 02:17:12 - 0:17:13 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:17:12 - 0:17:13 - Mean cosine (nn method, S2T build, 10000 max size): 0.25991
INFO - 02/22/19 02:18:46 - 0:18:48 - Building the train dictionary ...
INFO - 02/22/19 02:18:46 - 0:18:48 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:18:46 - 0:18:48 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.25459
INFO - 02/22/19 02:18:49 - 0:18:51 - Discriminator source / target predictions: 0.90945 / 0.19593
INFO - 02/22/19 02:18:49 - 0:18:51 - Discriminator source / target / global accuracy: 0.99983 / 0.91640 / 0.99179
INFO - 02/22/19 02:18:49 - 0:18:51 - __log__:{"n_epoch": 1, "mean_cosine-nn-S2T-10000": 0.25990575551986694, "mean_cosine-csls_knn_10-S2T-10000": 0.25458818674087524, "dis_accu": 0.9917860566434579, "dis_src_pred": 0.9094523524982007, "dis_tgt_pred": 0.19593013575913243}
INFO - 02/22/19 02:18:49 - 0:18:51 - End of epoch 1.
INFO - 02/22/19 02:18:49 - 0:18:51 - Decreasing learning rate: 0.09800000 -> 0.09604000
INFO - 02/22/19 02:18:49 - 0:18:51 - Validation metric is smaller than the best: 0.25459 vs 0.41910
INFO - 02/22/19 02:18:49 - 0:18:51 - Starting adversarial training epoch 2...
INFO - 02/22/19 02:18:50 - 0:18:51 - 000000 - Discriminator loss: 0.3252 - 4583 samples/s
INFO - 02/22/19 02:18:51 - 0:18:52 - 004000 - Discriminator loss: 0.3252 - 4646 samples/s
INFO - 02/22/19 02:18:53 - 0:18:54 - 008000 - Discriminator loss: 0.3252 - 4847 samples/s
INFO - 02/22/19 02:18:55 - 0:18:56 - 012000 - Discriminator loss: 0.3252 - 4891 samples/s
INFO - 02/22/19 02:18:56 - 0:18:57 - 016000 - Discriminator loss: 0.3252 - 4899 samples/s
INFO - 02/22/19 02:18:58 - 0:18:59 - 020000 - Discriminator loss: 0.3252 - 4735 samples/s
INFO - 02/22/19 02:19:00 - 0:19:01 - 024000 - Discriminator loss: 0.3252 - 4800 samples/s
INFO - 02/22/19 02:19:01 - 0:19:02 - 028000 - Discriminator loss: 0.3252 - 4885 samples/s
INFO - 02/22/19 02:19:03 - 0:19:04 - 032000 - Discriminator loss: 0.3252 - 4779 samples/s
INFO - 02/22/19 02:19:04 - 0:19:06 - 036000 - Discriminator loss: 0.3252 - 4896 samples/s
INFO - 02/22/19 02:19:06 - 0:19:07 - 040000 - Discriminator loss: 0.3252 - 4836 samples/s
INFO - 02/22/19 02:19:08 - 0:19:09 - 044000 - Discriminator loss: 0.3252 - 4654 samples/s
INFO - 02/22/19 02:19:09 - 0:19:11 - 048000 - Discriminator loss: 0.3252 - 4885 samples/s
INFO - 02/22/19 02:19:11 - 0:19:12 - 052000 - Discriminator loss: 0.3252 - 4755 samples/s
INFO - 02/22/19 02:19:13 - 0:19:14 - 056000 - Discriminator loss: 0.3252 - 4789 samples/s
INFO - 02/22/19 02:19:14 - 0:19:16 - 060000 - Discriminator loss: 0.3252 - 4857 samples/s
INFO - 02/22/19 02:19:16 - 0:19:17 - 064000 - Discriminator loss: 0.3252 - 4872 samples/s
INFO - 02/22/19 02:19:18 - 0:19:19 - 068000 - Discriminator loss: 0.3252 - 4873 samples/s
INFO - 02/22/19 02:19:19 - 0:19:21 - 072000 - Discriminator loss: 0.3252 - 4901 samples/s
INFO - 02/22/19 02:19:21 - 0:19:22 - 076000 - Discriminator loss: 0.3252 - 4874 samples/s
INFO - 02/22/19 02:19:23 - 0:19:24 - 080000 - Discriminator loss: 0.3252 - 4866 samples/s
INFO - 02/22/19 02:19:24 - 0:19:25 - 084000 - Discriminator loss: 0.3252 - 4907 samples/s
INFO - 02/22/19 02:19:26 - 0:19:27 - 088000 - Discriminator loss: 0.3252 - 4849 samples/s
INFO - 02/22/19 02:19:28 - 0:19:29 - 092000 - Discriminator loss: 0.3252 - 4920 samples/s
INFO - 02/22/19 02:19:29 - 0:19:30 - 096000 - Discriminator loss: 0.3252 - 4937 samples/s
INFO - 02/22/19 02:19:31 - 0:19:32 - 100000 - Discriminator loss: 0.3252 - 4873 samples/s
INFO - 02/22/19 02:19:32 - 0:19:34 - 104000 - Discriminator loss: 0.3252 - 4838 samples/s
INFO - 02/22/19 02:19:34 - 0:19:35 - 108000 - Discriminator loss: 0.3252 - 4934 samples/s
INFO - 02/22/19 02:19:36 - 0:19:37 - 112000 - Discriminator loss: 0.3252 - 4836 samples/s
INFO - 02/22/19 02:19:37 - 0:19:39 - 116000 - Discriminator loss: 0.3252 - 4710 samples/s
INFO - 02/22/19 02:19:39 - 0:19:40 - 120000 - Discriminator loss: 0.3252 - 4817 samples/s
INFO - 02/22/19 02:19:41 - 0:19:42 - 124000 - Discriminator loss: 0.3252 - 4721 samples/s
INFO - 02/22/19 02:19:43 - 0:19:44 - 128000 - Discriminator loss: 0.3252 - 4701 samples/s
INFO - 02/22/19 02:19:44 - 0:19:45 - 132000 - Discriminator loss: 0.3252 - 4794 samples/s
INFO - 02/22/19 02:19:46 - 0:19:47 - 136000 - Discriminator loss: 0.3252 - 4897 samples/s
INFO - 02/22/19 02:19:47 - 0:19:49 - 140000 - Discriminator loss: 0.3252 - 4905 samples/s
INFO - 02/22/19 02:19:49 - 0:19:50 - 144000 - Discriminator loss: 0.3252 - 4920 samples/s
INFO - 02/22/19 02:19:51 - 0:19:52 - 148000 - Discriminator loss: 0.3252 - 4609 samples/s
INFO - 02/22/19 02:19:53 - 0:19:54 - 152000 - Discriminator loss: 0.3252 - 4660 samples/s
INFO - 02/22/19 02:19:54 - 0:19:55 - 156000 - Discriminator loss: 0.3252 - 4708 samples/s
INFO - 02/22/19 02:19:56 - 0:19:57 - 160000 - Discriminator loss: 0.3253 - 4839 samples/s
INFO - 02/22/19 02:19:58 - 0:19:59 - 164000 - Discriminator loss: 0.3252 - 4862 samples/s
INFO - 02/22/19 02:19:59 - 0:20:00 - 168000 - Discriminator loss: 0.3252 - 4833 samples/s
INFO - 02/22/19 02:20:01 - 0:20:02 - 172000 - Discriminator loss: 0.3252 - 4634 samples/s
INFO - 02/22/19 02:20:03 - 0:20:04 - 176000 - Discriminator loss: 0.3252 - 4822 samples/s
INFO - 02/22/19 02:20:04 - 0:20:05 - 180000 - Discriminator loss: 0.3252 - 4753 samples/s
INFO - 02/22/19 02:20:06 - 0:20:07 - 184000 - Discriminator loss: 0.3253 - 4723 samples/s
INFO - 02/22/19 02:20:08 - 0:20:09 - 188000 - Discriminator loss: 0.3252 - 4830 samples/s
INFO - 02/22/19 02:20:09 - 0:20:10 - 192000 - Discriminator loss: 0.3252 - 4701 samples/s
INFO - 02/22/19 02:20:11 - 0:20:12 - 196000 - Discriminator loss: 0.3253 - 4815 samples/s
INFO - 02/22/19 02:20:13 - 0:20:14 - 200000 - Discriminator loss: 0.3252 - 4605 samples/s
INFO - 02/22/19 02:20:14 - 0:20:15 - 204000 - Discriminator loss: 0.3252 - 5464 samples/s
INFO - 02/22/19 02:20:16 - 0:20:17 - 208000 - Discriminator loss: 0.3252 - 5940 samples/s
INFO - 02/22/19 02:20:17 - 0:20:18 - 212000 - Discriminator loss: 0.3253 - 5155 samples/s
INFO - 02/22/19 02:20:19 - 0:20:20 - 216000 - Discriminator loss: 0.3252 - 4929 samples/s
INFO - 02/22/19 02:20:20 - 0:20:21 - 220000 - Discriminator loss: 0.3253 - 4891 samples/s
INFO - 02/22/19 02:20:22 - 0:20:23 - 224000 - Discriminator loss: 0.3252 - 4802 samples/s
INFO - 02/22/19 02:20:24 - 0:20:25 - 228000 - Discriminator loss: 0.3252 - 4792 samples/s
INFO - 02/22/19 02:20:25 - 0:20:26 - 232000 - Discriminator loss: 0.3252 - 4897 samples/s
INFO - 02/22/19 02:20:27 - 0:20:28 - 236000 - Discriminator loss: 0.3252 - 4818 samples/s
INFO - 02/22/19 02:20:29 - 0:20:30 - 240000 - Discriminator loss: 0.3252 - 4902 samples/s
INFO - 02/22/19 02:20:30 - 0:20:31 - 244000 - Discriminator loss: 0.3252 - 4852 samples/s
INFO - 02/22/19 02:20:32 - 0:20:33 - 248000 - Discriminator loss: 0.3252 - 4866 samples/s
INFO - 02/22/19 02:20:34 - 0:20:35 - 252000 - Discriminator loss: 0.3252 - 4530 samples/s
INFO - 02/22/19 02:20:35 - 0:20:36 - 256000 - Discriminator loss: 0.3252 - 4855 samples/s
INFO - 02/22/19 02:20:37 - 0:20:38 - 260000 - Discriminator loss: 0.3252 - 4926 samples/s
INFO - 02/22/19 02:20:39 - 0:20:40 - 264000 - Discriminator loss: 0.3252 - 4901 samples/s
INFO - 02/22/19 02:20:40 - 0:20:41 - 268000 - Discriminator loss: 0.3252 - 4868 samples/s
INFO - 02/22/19 02:20:42 - 0:20:43 - 272000 - Discriminator loss: 0.3252 - 4819 samples/s
INFO - 02/22/19 02:20:44 - 0:20:45 - 276000 - Discriminator loss: 0.3252 - 4802 samples/s
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INFO - 02/22/19 02:24:33 - 0:24:34 - 872000 - Discriminator loss: 0.3252 - 4888 samples/s
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INFO - 02/22/19 02:24:58 - 0:24:59 - 932000 - Discriminator loss: 0.3252 - 4940 samples/s
INFO - 02/22/19 02:25:00 - 0:25:01 - 936000 - Discriminator loss: 0.3252 - 4852 samples/s
INFO - 02/22/19 02:25:02 - 0:25:03 - 940000 - Discriminator loss: 0.3252 - 4570 samples/s
INFO - 02/22/19 02:25:03 - 0:25:05 - 944000 - Discriminator loss: 0.3252 - 4644 samples/s
INFO - 02/22/19 02:25:05 - 0:25:06 - 948000 - Discriminator loss: 0.3252 - 4650 samples/s
INFO - 02/22/19 02:25:07 - 0:25:08 - 952000 - Discriminator loss: 0.3252 - 4909 samples/s
INFO - 02/22/19 02:25:08 - 0:25:10 - 956000 - Discriminator loss: 0.3252 - 4604 samples/s
INFO - 02/22/19 02:25:10 - 0:25:11 - 960000 - Discriminator loss: 0.3252 - 4833 samples/s
INFO - 02/22/19 02:25:12 - 0:25:13 - 964000 - Discriminator loss: 0.3252 - 4843 samples/s
INFO - 02/22/19 02:25:14 - 0:25:15 - 968000 - Discriminator loss: 0.3252 - 4576 samples/s
INFO - 02/22/19 02:25:15 - 0:25:16 - 972000 - Discriminator loss: 0.3252 - 4650 samples/s
INFO - 02/22/19 02:25:17 - 0:25:18 - 976000 - Discriminator loss: 0.3252 - 4770 samples/s
INFO - 02/22/19 02:25:19 - 0:25:20 - 980000 - Discriminator loss: 0.3252 - 4779 samples/s
INFO - 02/22/19 02:25:20 - 0:25:21 - 984000 - Discriminator loss: 0.3252 - 4825 samples/s
INFO - 02/22/19 02:25:22 - 0:25:23 - 988000 - Discriminator loss: 0.3252 - 4608 samples/s
INFO - 02/22/19 02:25:24 - 0:25:25 - 992000 - Discriminator loss: 0.3252 - 4727 samples/s
INFO - 02/22/19 02:25:25 - 0:25:26 - 996000 - Discriminator loss: 0.3252 - 4902 samples/s
INFO - 02/22/19 02:25:42 - 0:25:43 - Building the train dictionary ...
INFO - 02/22/19 02:25:42 - 0:25:43 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:25:42 - 0:25:43 - Mean cosine (nn method, S2T build, 10000 max size): 0.25823
INFO - 02/22/19 02:27:16 - 0:27:17 - Building the train dictionary ...
INFO - 02/22/19 02:27:16 - 0:27:17 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:27:16 - 0:27:17 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.25039
INFO - 02/22/19 02:27:19 - 0:27:20 - Discriminator source / target predictions: 0.90283 / 0.17979
INFO - 02/22/19 02:27:19 - 0:27:20 - Discriminator source / target / global accuracy: 0.99983 / 0.93383 / 0.99346
INFO - 02/22/19 02:27:19 - 0:27:20 - __log__:{"n_epoch": 2, "mean_cosine-nn-S2T-10000": 0.25822749733924866, "mean_cosine-csls_knn_10-S2T-10000": 0.25039276480674744, "dis_accu": 0.9934649696914304, "dis_src_pred": 0.9028308932798651, "dis_tgt_pred": 0.1797864910988827}
INFO - 02/22/19 02:27:19 - 0:27:20 - End of epoch 2.
INFO - 02/22/19 02:27:19 - 0:27:20 - Decreasing learning rate: 0.09604000 -> 0.09411920
INFO - 02/22/19 02:27:19 - 0:27:20 - Validation metric is smaller than the best: 0.25039 vs 0.41910
INFO - 02/22/19 02:27:19 - 0:27:20 - Shrinking the learning rate: 0.09412 -> 0.04706
INFO - 02/22/19 02:27:19 - 0:27:20 - Starting adversarial training epoch 3...
INFO - 02/22/19 02:27:19 - 0:27:20 - 000000 - Discriminator loss: 0.3251 - 4901 samples/s
INFO - 02/22/19 02:27:20 - 0:27:22 - 004000 - Discriminator loss: 0.3252 - 5396 samples/s
INFO - 02/22/19 02:27:22 - 0:27:23 - 008000 - Discriminator loss: 0.3252 - 4356 samples/s
INFO - 02/22/19 02:27:24 - 0:27:25 - 012000 - Discriminator loss: 0.3252 - 4736 samples/s
INFO - 02/22/19 02:27:26 - 0:27:27 - 016000 - Discriminator loss: 0.3252 - 4874 samples/s
INFO - 02/22/19 02:27:27 - 0:27:29 - 020000 - Discriminator loss: 0.3251 - 4603 samples/s
INFO - 02/22/19 02:27:29 - 0:27:30 - 024000 - Discriminator loss: 0.3251 - 4759 samples/s
INFO - 02/22/19 02:27:31 - 0:27:32 - 028000 - Discriminator loss: 0.3251 - 4900 samples/s
INFO - 02/22/19 02:27:32 - 0:27:34 - 032000 - Discriminator loss: 0.3251 - 4716 samples/s
INFO - 02/22/19 02:27:34 - 0:27:35 - 036000 - Discriminator loss: 0.3251 - 4851 samples/s
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INFO - 02/22/19 02:27:39 - 0:27:40 - 048000 - Discriminator loss: 0.3251 - 4613 samples/s
INFO - 02/22/19 02:27:41 - 0:27:42 - 052000 - Discriminator loss: 0.3251 - 4462 samples/s
INFO - 02/22/19 02:27:42 - 0:27:44 - 056000 - Discriminator loss: 0.3251 - 4813 samples/s
INFO - 02/22/19 02:27:44 - 0:27:45 - 060000 - Discriminator loss: 0.3251 - 4831 samples/s
INFO - 02/22/19 02:27:46 - 0:27:47 - 064000 - Discriminator loss: 0.3251 - 4888 samples/s
INFO - 02/22/19 02:27:48 - 0:27:49 - 068000 - Discriminator loss: 0.3251 - 4479 samples/s
INFO - 02/22/19 02:27:49 - 0:27:50 - 072000 - Discriminator loss: 0.3251 - 4878 samples/s
INFO - 02/22/19 02:27:51 - 0:27:52 - 076000 - Discriminator loss: 0.3251 - 4860 samples/s
INFO - 02/22/19 02:27:53 - 0:27:54 - 080000 - Discriminator loss: 0.3251 - 4709 samples/s
INFO - 02/22/19 02:27:54 - 0:27:55 - 084000 - Discriminator loss: 0.3251 - 4649 samples/s
INFO - 02/22/19 02:27:56 - 0:27:57 - 088000 - Discriminator loss: 0.3251 - 4736 samples/s
INFO - 02/22/19 02:27:58 - 0:27:59 - 092000 - Discriminator loss: 0.3251 - 4890 samples/s
INFO - 02/22/19 02:27:59 - 0:28:00 - 096000 - Discriminator loss: 0.3251 - 4762 samples/s
INFO - 02/22/19 02:28:01 - 0:28:02 - 100000 - Discriminator loss: 0.3251 - 4412 samples/s
INFO - 02/22/19 02:28:03 - 0:28:04 - 104000 - Discriminator loss: 0.3251 - 4826 samples/s
INFO - 02/22/19 02:28:04 - 0:28:06 - 108000 - Discriminator loss: 0.3251 - 4910 samples/s
INFO - 02/22/19 02:28:06 - 0:28:07 - 112000 - Discriminator loss: 0.3251 - 4706 samples/s
INFO - 02/22/19 02:28:08 - 0:28:09 - 116000 - Discriminator loss: 0.3251 - 4598 samples/s
INFO - 02/22/19 02:28:09 - 0:28:11 - 120000 - Discriminator loss: 0.3251 - 4791 samples/s
INFO - 02/22/19 02:28:11 - 0:28:12 - 124000 - Discriminator loss: 0.3251 - 4709 samples/s
INFO - 02/22/19 02:28:13 - 0:28:14 - 128000 - Discriminator loss: 0.3251 - 4802 samples/s
INFO - 02/22/19 02:28:15 - 0:28:16 - 132000 - Discriminator loss: 0.3251 - 4652 samples/s
INFO - 02/22/19 02:28:16 - 0:28:17 - 136000 - Discriminator loss: 0.3251 - 4653 samples/s
INFO - 02/22/19 02:28:18 - 0:28:19 - 140000 - Discriminator loss: 0.3251 - 4487 samples/s
INFO - 02/22/19 02:28:20 - 0:28:21 - 144000 - Discriminator loss: 0.3251 - 4733 samples/s
INFO - 02/22/19 02:28:21 - 0:28:23 - 148000 - Discriminator loss: 0.3251 - 4654 samples/s
INFO - 02/22/19 02:28:23 - 0:28:24 - 152000 - Discriminator loss: 0.3251 - 4944 samples/s
INFO - 02/22/19 02:28:25 - 0:28:26 - 156000 - Discriminator loss: 0.3251 - 4671 samples/s
INFO - 02/22/19 02:28:27 - 0:28:28 - 160000 - Discriminator loss: 0.3251 - 4475 samples/s
INFO - 02/22/19 02:28:28 - 0:28:29 - 164000 - Discriminator loss: 0.3251 - 4830 samples/s
INFO - 02/22/19 02:28:30 - 0:28:31 - 168000 - Discriminator loss: 0.3251 - 4681 samples/s
INFO - 02/22/19 02:28:32 - 0:28:33 - 172000 - Discriminator loss: 0.3251 - 4890 samples/s
INFO - 02/22/19 02:28:33 - 0:28:34 - 176000 - Discriminator loss: 0.3251 - 4751 samples/s
INFO - 02/22/19 02:28:35 - 0:28:36 - 180000 - Discriminator loss: 0.3251 - 4875 samples/s
INFO - 02/22/19 02:28:37 - 0:28:38 - 184000 - Discriminator loss: 0.3251 - 4869 samples/s
INFO - 02/22/19 02:28:38 - 0:28:39 - 188000 - Discriminator loss: 0.3251 - 4841 samples/s
INFO - 02/22/19 02:28:40 - 0:28:41 - 192000 - Discriminator loss: 0.3251 - 4952 samples/s
INFO - 02/22/19 02:28:42 - 0:28:43 - 196000 - Discriminator loss: 0.3252 - 4500 samples/s
INFO - 02/22/19 02:28:43 - 0:28:44 - 200000 - Discriminator loss: 0.3251 - 4772 samples/s
INFO - 02/22/19 02:28:45 - 0:28:46 - 204000 - Discriminator loss: 0.3251 - 4790 samples/s
INFO - 02/22/19 02:28:47 - 0:28:48 - 208000 - Discriminator loss: 0.3252 - 4527 samples/s
INFO - 02/22/19 02:28:49 - 0:28:50 - 212000 - Discriminator loss: 0.3251 - 4496 samples/s
INFO - 02/22/19 02:28:50 - 0:28:51 - 216000 - Discriminator loss: 0.3252 - 4824 samples/s
INFO - 02/22/19 02:28:52 - 0:28:53 - 220000 - Discriminator loss: 0.3252 - 4903 samples/s
INFO - 02/22/19 02:28:53 - 0:28:55 - 224000 - Discriminator loss: 0.3252 - 4782 samples/s
INFO - 02/22/19 02:28:55 - 0:28:56 - 228000 - Discriminator loss: 0.3251 - 4821 samples/s
INFO - 02/22/19 02:28:57 - 0:28:58 - 232000 - Discriminator loss: 0.3251 - 4906 samples/s
INFO - 02/22/19 02:28:58 - 0:29:00 - 236000 - Discriminator loss: 0.3252 - 4870 samples/s
INFO - 02/22/19 02:29:00 - 0:29:01 - 240000 - Discriminator loss: 0.3251 - 4845 samples/s
INFO - 02/22/19 02:29:02 - 0:29:03 - 244000 - Discriminator loss: 0.3252 - 4846 samples/s
INFO - 02/22/19 02:29:03 - 0:29:05 - 248000 - Discriminator loss: 0.3252 - 4861 samples/s
INFO - 02/22/19 02:29:05 - 0:29:06 - 252000 - Discriminator loss: 0.3252 - 4594 samples/s
INFO - 02/22/19 02:29:07 - 0:29:08 - 256000 - Discriminator loss: 0.3251 - 4749 samples/s
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INFO - 02/22/19 02:29:10 - 0:29:11 - 264000 - Discriminator loss: 0.3252 - 4554 samples/s
INFO - 02/22/19 02:29:12 - 0:29:13 - 268000 - Discriminator loss: 0.3251 - 4889 samples/s
INFO - 02/22/19 02:29:13 - 0:29:15 - 272000 - Discriminator loss: 0.3251 - 4893 samples/s
INFO - 02/22/19 02:29:15 - 0:29:16 - 276000 - Discriminator loss: 0.3252 - 4664 samples/s
INFO - 02/22/19 02:29:17 - 0:29:18 - 280000 - Discriminator loss: 0.3252 - 4952 samples/s
INFO - 02/22/19 02:29:18 - 0:29:20 - 284000 - Discriminator loss: 0.3252 - 4927 samples/s
INFO - 02/22/19 02:29:20 - 0:29:21 - 288000 - Discriminator loss: 0.3252 - 4703 samples/s
INFO - 02/22/19 02:29:22 - 0:29:23 - 292000 - Discriminator loss: 0.3252 - 4877 samples/s
INFO - 02/22/19 02:29:23 - 0:29:25 - 296000 - Discriminator loss: 0.3252 - 4879 samples/s
INFO - 02/22/19 02:29:25 - 0:29:26 - 300000 - Discriminator loss: 0.3251 - 4729 samples/s
INFO - 02/22/19 02:29:27 - 0:29:28 - 304000 - Discriminator loss: 0.3251 - 4341 samples/s
INFO - 02/22/19 02:29:29 - 0:29:30 - 308000 - Discriminator loss: 0.3252 - 4893 samples/s
INFO - 02/22/19 02:29:30 - 0:29:31 - 312000 - Discriminator loss: 0.3251 - 4878 samples/s
INFO - 02/22/19 02:29:32 - 0:29:33 - 316000 - Discriminator loss: 0.3251 - 4793 samples/s
INFO - 02/22/19 02:29:34 - 0:29:35 - 320000 - Discriminator loss: 0.3251 - 4914 samples/s
INFO - 02/22/19 02:29:35 - 0:29:36 - 324000 - Discriminator loss: 0.3251 - 4873 samples/s
INFO - 02/22/19 02:29:37 - 0:29:38 - 328000 - Discriminator loss: 0.3251 - 4831 samples/s
INFO - 02/22/19 02:29:38 - 0:29:40 - 332000 - Discriminator loss: 0.3252 - 4860 samples/s
INFO - 02/22/19 02:29:40 - 0:29:41 - 336000 - Discriminator loss: 0.3251 - 4827 samples/s
INFO - 02/22/19 02:29:42 - 0:29:43 - 340000 - Discriminator loss: 0.3251 - 4884 samples/s
INFO - 02/22/19 02:29:43 - 0:29:45 - 344000 - Discriminator loss: 0.3251 - 4626 samples/s
INFO - 02/22/19 02:29:45 - 0:29:46 - 348000 - Discriminator loss: 0.3251 - 4839 samples/s
INFO - 02/22/19 02:29:47 - 0:29:48 - 352000 - Discriminator loss: 0.3251 - 4949 samples/s
INFO - 02/22/19 02:29:48 - 0:29:49 - 356000 - Discriminator loss: 0.3251 - 5603 samples/s
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INFO - 02/22/19 02:29:51 - 0:29:52 - 364000 - Discriminator loss: 0.3251 - 5808 samples/s
INFO - 02/22/19 02:29:53 - 0:29:54 - 368000 - Discriminator loss: 0.3251 - 4649 samples/s
INFO - 02/22/19 02:29:54 - 0:29:56 - 372000 - Discriminator loss: 0.3251 - 4357 samples/s
INFO - 02/22/19 02:29:56 - 0:29:57 - 376000 - Discriminator loss: 0.3251 - 4855 samples/s
INFO - 02/22/19 02:29:58 - 0:29:59 - 380000 - Discriminator loss: 0.3251 - 4689 samples/s
INFO - 02/22/19 02:30:00 - 0:30:01 - 384000 - Discriminator loss: 0.3251 - 4670 samples/s
INFO - 02/22/19 02:30:01 - 0:30:02 - 388000 - Discriminator loss: 0.3252 - 4596 samples/s
INFO - 02/22/19 02:30:03 - 0:30:04 - 392000 - Discriminator loss: 0.3251 - 4909 samples/s
INFO - 02/22/19 02:30:05 - 0:30:06 - 396000 - Discriminator loss: 0.3252 - 4851 samples/s
INFO - 02/22/19 02:30:06 - 0:30:07 - 400000 - Discriminator loss: 0.3252 - 4873 samples/s
INFO - 02/22/19 02:30:08 - 0:30:09 - 404000 - Discriminator loss: 0.3251 - 4885 samples/s
INFO - 02/22/19 02:30:09 - 0:30:11 - 408000 - Discriminator loss: 0.3251 - 4922 samples/s
INFO - 02/22/19 02:30:11 - 0:30:12 - 412000 - Discriminator loss: 0.3252 - 4716 samples/s
INFO - 02/22/19 02:30:13 - 0:30:14 - 416000 - Discriminator loss: 0.3252 - 4835 samples/s
INFO - 02/22/19 02:30:15 - 0:30:16 - 420000 - Discriminator loss: 0.3252 - 4789 samples/s
INFO - 02/22/19 02:30:16 - 0:30:17 - 424000 - Discriminator loss: 0.3251 - 4759 samples/s
INFO - 02/22/19 02:30:18 - 0:30:19 - 428000 - Discriminator loss: 0.3252 - 4329 samples/s
INFO - 02/22/19 02:30:20 - 0:30:21 - 432000 - Discriminator loss: 0.3252 - 4739 samples/s
INFO - 02/22/19 02:30:21 - 0:30:23 - 436000 - Discriminator loss: 0.3252 - 4765 samples/s
INFO - 02/22/19 02:30:23 - 0:30:24 - 440000 - Discriminator loss: 0.3252 - 4901 samples/s
INFO - 02/22/19 02:30:25 - 0:30:26 - 444000 - Discriminator loss: 0.3251 - 4788 samples/s
INFO - 02/22/19 02:30:26 - 0:30:28 - 448000 - Discriminator loss: 0.3251 - 4794 samples/s
INFO - 02/22/19 02:30:28 - 0:30:29 - 452000 - Discriminator loss: 0.3252 - 4818 samples/s
INFO - 02/22/19 02:30:30 - 0:30:31 - 456000 - Discriminator loss: 0.3251 - 4740 samples/s
INFO - 02/22/19 02:30:31 - 0:30:33 - 460000 - Discriminator loss: 0.3251 - 4864 samples/s
INFO - 02/22/19 02:30:33 - 0:30:34 - 464000 - Discriminator loss: 0.3252 - 4813 samples/s
INFO - 02/22/19 02:30:35 - 0:30:36 - 468000 - Discriminator loss: 0.3251 - 4880 samples/s
INFO - 02/22/19 02:30:36 - 0:30:38 - 472000 - Discriminator loss: 0.3252 - 4738 samples/s
INFO - 02/22/19 02:30:38 - 0:30:39 - 476000 - Discriminator loss: 0.3252 - 4915 samples/s
INFO - 02/22/19 02:30:40 - 0:30:41 - 480000 - Discriminator loss: 0.3252 - 4893 samples/s
INFO - 02/22/19 02:30:41 - 0:30:42 - 484000 - Discriminator loss: 0.3251 - 4867 samples/s
INFO - 02/22/19 02:30:43 - 0:30:44 - 488000 - Discriminator loss: 0.3252 - 4762 samples/s
INFO - 02/22/19 02:30:45 - 0:30:46 - 492000 - Discriminator loss: 0.3252 - 4910 samples/s
INFO - 02/22/19 02:30:46 - 0:30:47 - 496000 - Discriminator loss: 0.3251 - 4836 samples/s
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INFO - 02/22/19 02:30:50 - 0:30:51 - 504000 - Discriminator loss: 0.3252 - 4849 samples/s
INFO - 02/22/19 02:30:51 - 0:30:52 - 508000 - Discriminator loss: 0.3252 - 4906 samples/s
INFO - 02/22/19 02:30:53 - 0:30:54 - 512000 - Discriminator loss: 0.3251 - 4867 samples/s
INFO - 02/22/19 02:30:54 - 0:30:56 - 516000 - Discriminator loss: 0.3252 - 4740 samples/s
INFO - 02/22/19 02:30:56 - 0:30:57 - 520000 - Discriminator loss: 0.3252 - 4649 samples/s
INFO - 02/22/19 02:30:58 - 0:30:59 - 524000 - Discriminator loss: 0.3252 - 4635 samples/s
INFO - 02/22/19 02:31:00 - 0:31:01 - 528000 - Discriminator loss: 0.3251 - 4694 samples/s
INFO - 02/22/19 02:31:01 - 0:31:02 - 532000 - Discriminator loss: 0.3252 - 4759 samples/s
INFO - 02/22/19 02:31:03 - 0:31:04 - 536000 - Discriminator loss: 0.3252 - 4796 samples/s
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INFO - 02/22/19 02:31:06 - 0:31:08 - 544000 - Discriminator loss: 0.3251 - 4637 samples/s
INFO - 02/22/19 02:31:08 - 0:31:09 - 548000 - Discriminator loss: 0.3252 - 4848 samples/s
INFO - 02/22/19 02:31:10 - 0:31:11 - 552000 - Discriminator loss: 0.3251 - 4887 samples/s
INFO - 02/22/19 02:31:11 - 0:31:12 - 556000 - Discriminator loss: 0.3251 - 4904 samples/s
INFO - 02/22/19 02:31:13 - 0:31:14 - 560000 - Discriminator loss: 0.3251 - 4831 samples/s
INFO - 02/22/19 02:31:15 - 0:31:16 - 564000 - Discriminator loss: 0.3252 - 4899 samples/s
INFO - 02/22/19 02:31:16 - 0:31:17 - 568000 - Discriminator loss: 0.3252 - 4855 samples/s
INFO - 02/22/19 02:31:18 - 0:31:19 - 572000 - Discriminator loss: 0.3252 - 4594 samples/s
INFO - 02/22/19 02:31:20 - 0:31:21 - 576000 - Discriminator loss: 0.3252 - 4850 samples/s
INFO - 02/22/19 02:31:21 - 0:31:23 - 580000 - Discriminator loss: 0.3252 - 4576 samples/s
INFO - 02/22/19 02:31:23 - 0:31:24 - 584000 - Discriminator loss: 0.3252 - 4766 samples/s
INFO - 02/22/19 02:31:25 - 0:31:26 - 588000 - Discriminator loss: 0.3251 - 4742 samples/s
INFO - 02/22/19 02:31:26 - 0:31:28 - 592000 - Discriminator loss: 0.3252 - 4814 samples/s
INFO - 02/22/19 02:31:28 - 0:31:29 - 596000 - Discriminator loss: 0.3251 - 4658 samples/s
INFO - 02/22/19 02:31:30 - 0:31:31 - 600000 - Discriminator loss: 0.3251 - 4888 samples/s
INFO - 02/22/19 02:31:31 - 0:31:33 - 604000 - Discriminator loss: 0.3251 - 4848 samples/s
INFO - 02/22/19 02:31:33 - 0:31:34 - 608000 - Discriminator loss: 0.3252 - 4834 samples/s
INFO - 02/22/19 02:31:35 - 0:31:36 - 612000 - Discriminator loss: 0.3252 - 4869 samples/s
INFO - 02/22/19 02:31:36 - 0:31:38 - 616000 - Discriminator loss: 0.3251 - 4942 samples/s
INFO - 02/22/19 02:31:38 - 0:31:39 - 620000 - Discriminator loss: 0.3251 - 4879 samples/s
INFO - 02/22/19 02:31:40 - 0:31:41 - 624000 - Discriminator loss: 0.3251 - 4917 samples/s
INFO - 02/22/19 02:31:41 - 0:31:42 - 628000 - Discriminator loss: 0.3251 - 4903 samples/s
INFO - 02/22/19 02:31:43 - 0:31:44 - 632000 - Discriminator loss: 0.3251 - 4473 samples/s
INFO - 02/22/19 02:31:45 - 0:31:46 - 636000 - Discriminator loss: 0.3251 - 4843 samples/s
INFO - 02/22/19 02:31:46 - 0:31:47 - 640000 - Discriminator loss: 0.3251 - 4875 samples/s
INFO - 02/22/19 02:31:48 - 0:31:49 - 644000 - Discriminator loss: 0.3251 - 4892 samples/s
INFO - 02/22/19 02:31:50 - 0:31:51 - 648000 - Discriminator loss: 0.3251 - 4834 samples/s
INFO - 02/22/19 02:31:51 - 0:31:52 - 652000 - Discriminator loss: 0.3251 - 4916 samples/s
INFO - 02/22/19 02:31:53 - 0:31:54 - 656000 - Discriminator loss: 0.3252 - 4849 samples/s
INFO - 02/22/19 02:31:55 - 0:31:56 - 660000 - Discriminator loss: 0.3251 - 4667 samples/s
INFO - 02/22/19 02:31:56 - 0:31:57 - 664000 - Discriminator loss: 0.3251 - 4880 samples/s
INFO - 02/22/19 02:31:58 - 0:31:59 - 668000 - Discriminator loss: 0.3251 - 4892 samples/s
INFO - 02/22/19 02:32:00 - 0:32:01 - 672000 - Discriminator loss: 0.3251 - 4798 samples/s
INFO - 02/22/19 02:32:01 - 0:32:02 - 676000 - Discriminator loss: 0.3251 - 4570 samples/s
INFO - 02/22/19 02:32:03 - 0:32:04 - 680000 - Discriminator loss: 0.3251 - 4535 samples/s
INFO - 02/22/19 02:32:05 - 0:32:06 - 684000 - Discriminator loss: 0.3251 - 4862 samples/s
INFO - 02/22/19 02:32:06 - 0:32:08 - 688000 - Discriminator loss: 0.3251 - 4674 samples/s
INFO - 02/22/19 02:32:08 - 0:32:09 - 692000 - Discriminator loss: 0.3251 - 4800 samples/s
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INFO - 02/22/19 02:32:12 - 0:32:13 - 700000 - Discriminator loss: 0.3251 - 4912 samples/s
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INFO - 02/22/19 02:32:27 - 0:32:28 - 736000 - Discriminator loss: 0.3251 - 4876 samples/s
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INFO - 02/22/19 02:33:17 - 0:33:19 - 856000 - Discriminator loss: 0.3251 - 4811 samples/s
INFO - 02/22/19 02:33:19 - 0:33:20 - 860000 - Discriminator loss: 0.3251 - 4967 samples/s
INFO - 02/22/19 02:33:21 - 0:33:22 - 864000 - Discriminator loss: 0.3251 - 4850 samples/s
INFO - 02/22/19 02:33:22 - 0:33:23 - 868000 - Discriminator loss: 0.3251 - 4848 samples/s
INFO - 02/22/19 02:33:24 - 0:33:25 - 872000 - Discriminator loss: 0.3251 - 4814 samples/s
INFO - 02/22/19 02:33:26 - 0:33:27 - 876000 - Discriminator loss: 0.3251 - 4906 samples/s
INFO - 02/22/19 02:33:27 - 0:33:28 - 880000 - Discriminator loss: 0.3251 - 4651 samples/s
INFO - 02/22/19 02:33:29 - 0:33:30 - 884000 - Discriminator loss: 0.3251 - 4880 samples/s
INFO - 02/22/19 02:33:31 - 0:33:32 - 888000 - Discriminator loss: 0.3251 - 4899 samples/s
INFO - 02/22/19 02:33:32 - 0:33:33 - 892000 - Discriminator loss: 0.3251 - 4736 samples/s
INFO - 02/22/19 02:33:34 - 0:33:35 - 896000 - Discriminator loss: 0.3251 - 4624 samples/s
INFO - 02/22/19 02:33:36 - 0:33:37 - 900000 - Discriminator loss: 0.3251 - 4749 samples/s
INFO - 02/22/19 02:33:37 - 0:33:39 - 904000 - Discriminator loss: 0.3251 - 4664 samples/s
INFO - 02/22/19 02:33:39 - 0:33:40 - 908000 - Discriminator loss: 0.3251 - 4735 samples/s
INFO - 02/22/19 02:33:41 - 0:33:42 - 912000 - Discriminator loss: 0.3251 - 4683 samples/s
INFO - 02/22/19 02:33:42 - 0:33:44 - 916000 - Discriminator loss: 0.3251 - 4717 samples/s
INFO - 02/22/19 02:33:44 - 0:33:45 - 920000 - Discriminator loss: 0.3251 - 4864 samples/s
INFO - 02/22/19 02:33:46 - 0:33:47 - 924000 - Discriminator loss: 0.3251 - 4758 samples/s
INFO - 02/22/19 02:33:47 - 0:33:49 - 928000 - Discriminator loss: 0.3251 - 4901 samples/s
INFO - 02/22/19 02:33:49 - 0:33:50 - 932000 - Discriminator loss: 0.3251 - 4855 samples/s
INFO - 02/22/19 02:33:51 - 0:33:52 - 936000 - Discriminator loss: 0.3251 - 4949 samples/s
INFO - 02/22/19 02:33:52 - 0:33:54 - 940000 - Discriminator loss: 0.3251 - 4883 samples/s
INFO - 02/22/19 02:33:54 - 0:33:55 - 944000 - Discriminator loss: 0.3251 - 4894 samples/s
INFO - 02/22/19 02:33:56 - 0:33:57 - 948000 - Discriminator loss: 0.3251 - 4958 samples/s
INFO - 02/22/19 02:33:57 - 0:33:58 - 952000 - Discriminator loss: 0.3251 - 4646 samples/s
INFO - 02/22/19 02:33:59 - 0:34:00 - 956000 - Discriminator loss: 0.3251 - 4748 samples/s
INFO - 02/22/19 02:34:01 - 0:34:02 - 960000 - Discriminator loss: 0.3251 - 4908 samples/s
INFO - 02/22/19 02:34:02 - 0:34:04 - 964000 - Discriminator loss: 0.3251 - 4665 samples/s
INFO - 02/22/19 02:34:04 - 0:34:05 - 968000 - Discriminator loss: 0.3251 - 4713 samples/s
INFO - 02/22/19 02:34:06 - 0:34:07 - 972000 - Discriminator loss: 0.3251 - 4731 samples/s
INFO - 02/22/19 02:34:07 - 0:34:09 - 976000 - Discriminator loss: 0.3251 - 4953 samples/s
INFO - 02/22/19 02:34:09 - 0:34:10 - 980000 - Discriminator loss: 0.3251 - 4841 samples/s
INFO - 02/22/19 02:34:11 - 0:34:12 - 984000 - Discriminator loss: 0.3251 - 4639 samples/s
INFO - 02/22/19 02:34:12 - 0:34:14 - 988000 - Discriminator loss: 0.3251 - 4724 samples/s
INFO - 02/22/19 02:34:14 - 0:34:15 - 992000 - Discriminator loss: 0.3251 - 4889 samples/s
INFO - 02/22/19 02:34:16 - 0:34:17 - 996000 - Discriminator loss: 0.3251 - 4857 samples/s
INFO - 02/22/19 02:34:32 - 0:34:33 - Building the train dictionary ...
INFO - 02/22/19 02:34:32 - 0:34:33 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:34:32 - 0:34:33 - Mean cosine (nn method, S2T build, 10000 max size): 0.25105
INFO - 02/22/19 02:36:06 - 0:36:08 - Building the train dictionary ...
INFO - 02/22/19 02:36:06 - 0:36:08 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:36:06 - 0:36:08 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.24749
INFO - 02/22/19 02:36:09 - 0:36:11 - Discriminator source / target predictions: 0.90224 / 0.18974
INFO - 02/22/19 02:36:10 - 0:36:11 - Discriminator source / target / global accuracy: 0.99979 / 0.91672 / 0.99178
INFO - 02/22/19 02:36:10 - 0:36:11 - __log__:{"n_epoch": 3, "mean_cosine-nn-S2T-10000": 0.251048743724823, "mean_cosine-csls_knn_10-S2T-10000": 0.24749144911766052, "dis_accu": 0.99178170430892, "dis_src_pred": 0.9022433165898411, "dis_tgt_pred": 0.18973754009578145}
INFO - 02/22/19 02:36:10 - 0:36:11 - End of epoch 3.
INFO - 02/22/19 02:36:10 - 0:36:11 - Decreasing learning rate: 0.04705960 -> 0.04611841
INFO - 02/22/19 02:36:10 - 0:36:11 - Validation metric is smaller than the best: 0.24749 vs 0.41910
INFO - 02/22/19 02:36:10 - 0:36:11 - Shrinking the learning rate: 0.04612 -> 0.02306
INFO - 02/22/19 02:36:10 - 0:36:11 - Starting adversarial training epoch 4...
INFO - 02/22/19 02:36:10 - 0:36:11 - 000000 - Discriminator loss: 0.3251 - 4952 samples/s
INFO - 02/22/19 02:36:11 - 0:36:12 - 004000 - Discriminator loss: 0.3251 - 4660 samples/s
INFO - 02/22/19 02:36:13 - 0:36:14 - 008000 - Discriminator loss: 0.3251 - 4887 samples/s
INFO - 02/22/19 02:36:15 - 0:36:16 - 012000 - Discriminator loss: 0.3251 - 4613 samples/s
INFO - 02/22/19 02:36:16 - 0:36:17 - 016000 - Discriminator loss: 0.3251 - 4870 samples/s
INFO - 02/22/19 02:36:18 - 0:36:19 - 020000 - Discriminator loss: 0.3251 - 4872 samples/s
INFO - 02/22/19 02:36:20 - 0:36:21 - 024000 - Discriminator loss: 0.3251 - 4752 samples/s
INFO - 02/22/19 02:36:21 - 0:36:22 - 028000 - Discriminator loss: 0.3251 - 4835 samples/s
INFO - 02/22/19 02:36:23 - 0:36:24 - 032000 - Discriminator loss: 0.3251 - 4959 samples/s
INFO - 02/22/19 02:36:25 - 0:36:26 - 036000 - Discriminator loss: 0.3251 - 4862 samples/s
INFO - 02/22/19 02:36:26 - 0:36:27 - 040000 - Discriminator loss: 0.3251 - 4845 samples/s
INFO - 02/22/19 02:36:28 - 0:36:29 - 044000 - Discriminator loss: 0.3251 - 4611 samples/s
INFO - 02/22/19 02:36:30 - 0:36:31 - 048000 - Discriminator loss: 0.3251 - 4928 samples/s
INFO - 02/22/19 02:36:31 - 0:36:32 - 052000 - Discriminator loss: 0.3251 - 4805 samples/s
INFO - 02/22/19 02:36:33 - 0:36:34 - 056000 - Discriminator loss: 0.3251 - 4896 samples/s
INFO - 02/22/19 02:36:34 - 0:36:36 - 060000 - Discriminator loss: 0.3251 - 4883 samples/s
INFO - 02/22/19 02:36:36 - 0:36:37 - 064000 - Discriminator loss: 0.3251 - 4776 samples/s
INFO - 02/22/19 02:36:38 - 0:36:39 - 068000 - Discriminator loss: 0.3251 - 4853 samples/s
INFO - 02/22/19 02:36:39 - 0:36:41 - 072000 - Discriminator loss: 0.3251 - 4806 samples/s
INFO - 02/22/19 02:36:41 - 0:36:42 - 076000 - Discriminator loss: 0.3251 - 4738 samples/s
INFO - 02/22/19 02:36:43 - 0:36:44 - 080000 - Discriminator loss: 0.3251 - 4729 samples/s
INFO - 02/22/19 02:36:44 - 0:36:46 - 084000 - Discriminator loss: 0.3251 - 4955 samples/s
INFO - 02/22/19 02:36:46 - 0:36:47 - 088000 - Discriminator loss: 0.3251 - 4774 samples/s
INFO - 02/22/19 02:36:48 - 0:36:49 - 092000 - Discriminator loss: 0.3251 - 4735 samples/s
INFO - 02/22/19 02:36:49 - 0:36:51 - 096000 - Discriminator loss: 0.3251 - 4884 samples/s
INFO - 02/22/19 02:36:51 - 0:36:52 - 100000 - Discriminator loss: 0.3251 - 4904 samples/s
INFO - 02/22/19 02:36:53 - 0:36:54 - 104000 - Discriminator loss: 0.3251 - 4743 samples/s
INFO - 02/22/19 02:36:54 - 0:36:56 - 108000 - Discriminator loss: 0.3251 - 4713 samples/s
INFO - 02/22/19 02:36:56 - 0:36:57 - 112000 - Discriminator loss: 0.3251 - 4854 samples/s
INFO - 02/22/19 02:36:58 - 0:36:59 - 116000 - Discriminator loss: 0.3251 - 4885 samples/s
INFO - 02/22/19 02:36:59 - 0:37:01 - 120000 - Discriminator loss: 0.3251 - 4685 samples/s
INFO - 02/22/19 02:37:01 - 0:37:02 - 124000 - Discriminator loss: 0.3251 - 4966 samples/s
INFO - 02/22/19 02:37:03 - 0:37:04 - 128000 - Discriminator loss: 0.3251 - 4911 samples/s
INFO - 02/22/19 02:37:04 - 0:37:06 - 132000 - Discriminator loss: 0.3251 - 4875 samples/s
INFO - 02/22/19 02:37:06 - 0:37:07 - 136000 - Discriminator loss: 0.3251 - 4411 samples/s
INFO - 02/22/19 02:37:08 - 0:37:09 - 140000 - Discriminator loss: 0.3251 - 5038 samples/s
INFO - 02/22/19 02:37:09 - 0:37:10 - 144000 - Discriminator loss: 0.3251 - 5396 samples/s
INFO - 02/22/19 02:37:11 - 0:37:12 - 148000 - Discriminator loss: 0.3251 - 5177 samples/s
INFO - 02/22/19 02:37:12 - 0:37:14 - 152000 - Discriminator loss: 0.3251 - 4771 samples/s
INFO - 02/22/19 02:37:14 - 0:37:15 - 156000 - Discriminator loss: 0.3251 - 5769 samples/s
INFO - 02/22/19 02:37:15 - 0:37:16 - 160000 - Discriminator loss: 0.3251 - 5563 samples/s
INFO - 02/22/19 02:37:17 - 0:37:18 - 164000 - Discriminator loss: 0.3251 - 4644 samples/s
INFO - 02/22/19 02:37:19 - 0:37:20 - 168000 - Discriminator loss: 0.3251 - 4870 samples/s
INFO - 02/22/19 02:37:20 - 0:37:21 - 172000 - Discriminator loss: 0.3251 - 4735 samples/s
INFO - 02/22/19 02:37:22 - 0:37:23 - 176000 - Discriminator loss: 0.3251 - 4749 samples/s
INFO - 02/22/19 02:37:24 - 0:37:25 - 180000 - Discriminator loss: 0.3251 - 4888 samples/s
INFO - 02/22/19 02:37:25 - 0:37:26 - 184000 - Discriminator loss: 0.3251 - 4795 samples/s
INFO - 02/22/19 02:37:27 - 0:37:28 - 188000 - Discriminator loss: 0.3251 - 4732 samples/s
INFO - 02/22/19 02:37:29 - 0:37:30 - 192000 - Discriminator loss: 0.3251 - 4820 samples/s
INFO - 02/22/19 02:37:30 - 0:37:31 - 196000 - Discriminator loss: 0.3251 - 4855 samples/s
INFO - 02/22/19 02:37:32 - 0:37:33 - 200000 - Discriminator loss: 0.3251 - 4841 samples/s
INFO - 02/22/19 02:37:34 - 0:37:35 - 204000 - Discriminator loss: 0.3251 - 4833 samples/s
INFO - 02/22/19 02:37:35 - 0:37:36 - 208000 - Discriminator loss: 0.3251 - 4886 samples/s
INFO - 02/22/19 02:37:37 - 0:37:38 - 212000 - Discriminator loss: 0.3251 - 4758 samples/s
INFO - 02/22/19 02:37:39 - 0:37:40 - 216000 - Discriminator loss: 0.3251 - 4653 samples/s
INFO - 02/22/19 02:37:40 - 0:37:41 - 220000 - Discriminator loss: 0.3251 - 4863 samples/s
INFO - 02/22/19 02:37:42 - 0:37:43 - 224000 - Discriminator loss: 0.3251 - 4797 samples/s
INFO - 02/22/19 02:37:44 - 0:37:45 - 228000 - Discriminator loss: 0.3251 - 4857 samples/s
INFO - 02/22/19 02:37:45 - 0:37:46 - 232000 - Discriminator loss: 0.3251 - 4761 samples/s
INFO - 02/22/19 02:37:47 - 0:37:48 - 236000 - Discriminator loss: 0.3251 - 4678 samples/s
INFO - 02/22/19 02:37:49 - 0:37:50 - 240000 - Discriminator loss: 0.3251 - 4908 samples/s
INFO - 02/22/19 02:37:50 - 0:37:52 - 244000 - Discriminator loss: 0.3251 - 4681 samples/s
INFO - 02/22/19 02:37:52 - 0:37:53 - 248000 - Discriminator loss: 0.3251 - 5028 samples/s
INFO - 02/22/19 02:37:54 - 0:37:55 - 252000 - Discriminator loss: 0.3251 - 4978 samples/s
INFO - 02/22/19 02:37:55 - 0:37:56 - 256000 - Discriminator loss: 0.3251 - 4858 samples/s
INFO - 02/22/19 02:37:57 - 0:37:58 - 260000 - Discriminator loss: 0.3251 - 4619 samples/s
INFO - 02/22/19 02:37:59 - 0:38:00 - 264000 - Discriminator loss: 0.3251 - 4767 samples/s
INFO - 02/22/19 02:38:00 - 0:38:01 - 268000 - Discriminator loss: 0.3251 - 4785 samples/s
INFO - 02/22/19 02:38:02 - 0:38:03 - 272000 - Discriminator loss: 0.3251 - 4778 samples/s
INFO - 02/22/19 02:38:04 - 0:38:05 - 276000 - Discriminator loss: 0.3251 - 4819 samples/s
INFO - 02/22/19 02:38:05 - 0:38:06 - 280000 - Discriminator loss: 0.3251 - 4684 samples/s
INFO - 02/22/19 02:38:07 - 0:38:08 - 284000 - Discriminator loss: 0.3251 - 4351 samples/s
INFO - 02/22/19 02:38:09 - 0:38:10 - 288000 - Discriminator loss: 0.3251 - 4823 samples/s
INFO - 02/22/19 02:38:10 - 0:38:12 - 292000 - Discriminator loss: 0.3251 - 4821 samples/s
INFO - 02/22/19 02:38:12 - 0:38:13 - 296000 - Discriminator loss: 0.3251 - 4798 samples/s
INFO - 02/22/19 02:38:14 - 0:38:15 - 300000 - Discriminator loss: 0.3251 - 4899 samples/s
INFO - 02/22/19 02:38:15 - 0:38:17 - 304000 - Discriminator loss: 0.3251 - 4859 samples/s
INFO - 02/22/19 02:38:17 - 0:38:18 - 308000 - Discriminator loss: 0.3251 - 4852 samples/s
INFO - 02/22/19 02:38:19 - 0:38:20 - 312000 - Discriminator loss: 0.3251 - 4727 samples/s
INFO - 02/22/19 02:38:20 - 0:38:22 - 316000 - Discriminator loss: 0.3251 - 4740 samples/s
INFO - 02/22/19 02:38:22 - 0:38:23 - 320000 - Discriminator loss: 0.3251 - 4857 samples/s
INFO - 02/22/19 02:38:24 - 0:38:25 - 324000 - Discriminator loss: 0.3251 - 4332 samples/s
INFO - 02/22/19 02:38:26 - 0:38:27 - 328000 - Discriminator loss: 0.3251 - 4657 samples/s
INFO - 02/22/19 02:38:27 - 0:38:29 - 332000 - Discriminator loss: 0.3251 - 4606 samples/s
INFO - 02/22/19 02:38:29 - 0:38:30 - 336000 - Discriminator loss: 0.3251 - 5238 samples/s
INFO - 02/22/19 02:38:31 - 0:38:32 - 340000 - Discriminator loss: 0.3251 - 4853 samples/s
INFO - 02/22/19 02:38:32 - 0:38:33 - 344000 - Discriminator loss: 0.3251 - 4724 samples/s
INFO - 02/22/19 02:38:34 - 0:38:35 - 348000 - Discriminator loss: 0.3251 - 4744 samples/s
INFO - 02/22/19 02:38:36 - 0:38:37 - 352000 - Discriminator loss: 0.3251 - 4590 samples/s
INFO - 02/22/19 02:38:37 - 0:38:39 - 356000 - Discriminator loss: 0.3251 - 4787 samples/s
INFO - 02/22/19 02:38:39 - 0:38:40 - 360000 - Discriminator loss: 0.3251 - 4783 samples/s
INFO - 02/22/19 02:38:41 - 0:38:42 - 364000 - Discriminator loss: 0.3251 - 4906 samples/s
INFO - 02/22/19 02:38:42 - 0:38:44 - 368000 - Discriminator loss: 0.3251 - 4791 samples/s
INFO - 02/22/19 02:38:44 - 0:38:45 - 372000 - Discriminator loss: 0.3251 - 4602 samples/s
INFO - 02/22/19 02:38:46 - 0:38:47 - 376000 - Discriminator loss: 0.3251 - 4796 samples/s
INFO - 02/22/19 02:38:47 - 0:38:49 - 380000 - Discriminator loss: 0.3251 - 4583 samples/s
INFO - 02/22/19 02:38:49 - 0:38:50 - 384000 - Discriminator loss: 0.3251 - 4766 samples/s
INFO - 02/22/19 02:38:51 - 0:38:52 - 388000 - Discriminator loss: 0.3251 - 4805 samples/s
INFO - 02/22/19 02:38:52 - 0:38:54 - 392000 - Discriminator loss: 0.3251 - 4903 samples/s
INFO - 02/22/19 02:38:54 - 0:38:55 - 396000 - Discriminator loss: 0.3251 - 4922 samples/s
INFO - 02/22/19 02:38:56 - 0:38:57 - 400000 - Discriminator loss: 0.3251 - 4672 samples/s
INFO - 02/22/19 02:38:57 - 0:38:58 - 404000 - Discriminator loss: 0.3251 - 5854 samples/s
INFO - 02/22/19 02:38:59 - 0:39:00 - 408000 - Discriminator loss: 0.3251 - 5408 samples/s
INFO - 02/22/19 02:39:00 - 0:39:02 - 412000 - Discriminator loss: 0.3251 - 4651 samples/s
INFO - 02/22/19 02:39:02 - 0:39:03 - 416000 - Discriminator loss: 0.3251 - 4872 samples/s
INFO - 02/22/19 02:39:04 - 0:39:05 - 420000 - Discriminator loss: 0.3251 - 4785 samples/s
INFO - 02/22/19 02:39:05 - 0:39:07 - 424000 - Discriminator loss: 0.3251 - 4576 samples/s
INFO - 02/22/19 02:39:07 - 0:39:08 - 428000 - Discriminator loss: 0.3251 - 4575 samples/s
INFO - 02/22/19 02:39:09 - 0:39:10 - 432000 - Discriminator loss: 0.3251 - 4393 samples/s
INFO - 02/22/19 02:39:11 - 0:39:12 - 436000 - Discriminator loss: 0.3251 - 4843 samples/s
INFO - 02/22/19 02:39:12 - 0:39:13 - 440000 - Discriminator loss: 0.3251 - 4789 samples/s
INFO - 02/22/19 02:39:14 - 0:39:15 - 444000 - Discriminator loss: 0.3251 - 4594 samples/s
INFO - 02/22/19 02:39:16 - 0:39:17 - 448000 - Discriminator loss: 0.3251 - 4891 samples/s
INFO - 02/22/19 02:39:17 - 0:39:19 - 452000 - Discriminator loss: 0.3251 - 4740 samples/s
INFO - 02/22/19 02:39:19 - 0:39:20 - 456000 - Discriminator loss: 0.3251 - 4553 samples/s
INFO - 02/22/19 02:39:21 - 0:39:22 - 460000 - Discriminator loss: 0.3251 - 4696 samples/s
INFO - 02/22/19 02:39:23 - 0:39:24 - 464000 - Discriminator loss: 0.3251 - 4762 samples/s
INFO - 02/22/19 02:39:24 - 0:39:25 - 468000 - Discriminator loss: 0.3251 - 4677 samples/s
INFO - 02/22/19 02:39:26 - 0:39:27 - 472000 - Discriminator loss: 0.3251 - 4452 samples/s
INFO - 02/22/19 02:39:28 - 0:39:29 - 476000 - Discriminator loss: 0.3251 - 4646 samples/s
INFO - 02/22/19 02:39:29 - 0:39:31 - 480000 - Discriminator loss: 0.3251 - 4659 samples/s
INFO - 02/22/19 02:39:31 - 0:39:32 - 484000 - Discriminator loss: 0.3251 - 4579 samples/s
INFO - 02/22/19 02:39:33 - 0:39:34 - 488000 - Discriminator loss: 0.3251 - 4830 samples/s
INFO - 02/22/19 02:39:35 - 0:39:36 - 492000 - Discriminator loss: 0.3251 - 4837 samples/s
INFO - 02/22/19 02:39:36 - 0:39:37 - 496000 - Discriminator loss: 0.3251 - 4573 samples/s
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INFO - 02/22/19 02:40:00 - 0:40:01 - 552000 - Discriminator loss: 0.3251 - 4734 samples/s
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INFO - 02/22/19 02:40:29 - 0:40:30 - 620000 - Discriminator loss: 0.3251 - 4650 samples/s
INFO - 02/22/19 02:40:30 - 0:40:31 - 624000 - Discriminator loss: 0.3251 - 4767 samples/s
INFO - 02/22/19 02:40:32 - 0:40:33 - 628000 - Discriminator loss: 0.3251 - 4544 samples/s
INFO - 02/22/19 02:40:34 - 0:40:35 - 632000 - Discriminator loss: 0.3251 - 4592 samples/s
INFO - 02/22/19 02:40:35 - 0:40:37 - 636000 - Discriminator loss: 0.3251 - 4888 samples/s
INFO - 02/22/19 02:40:37 - 0:40:38 - 640000 - Discriminator loss: 0.3251 - 4624 samples/s
INFO - 02/22/19 02:40:39 - 0:40:40 - 644000 - Discriminator loss: 0.3251 - 5168 samples/s
INFO - 02/22/19 02:40:40 - 0:40:42 - 648000 - Discriminator loss: 0.3251 - 4636 samples/s
INFO - 02/22/19 02:40:42 - 0:40:43 - 652000 - Discriminator loss: 0.3251 - 4874 samples/s
INFO - 02/22/19 02:40:44 - 0:40:45 - 656000 - Discriminator loss: 0.3251 - 4563 samples/s
INFO - 02/22/19 02:40:45 - 0:40:47 - 660000 - Discriminator loss: 0.3251 - 4770 samples/s
INFO - 02/22/19 02:40:47 - 0:40:48 - 664000 - Discriminator loss: 0.3251 - 4792 samples/s
INFO - 02/22/19 02:40:49 - 0:40:50 - 668000 - Discriminator loss: 0.3251 - 4694 samples/s
INFO - 02/22/19 02:40:50 - 0:40:52 - 672000 - Discriminator loss: 0.3251 - 4849 samples/s
INFO - 02/22/19 02:40:52 - 0:40:53 - 676000 - Discriminator loss: 0.3251 - 4684 samples/s
INFO - 02/22/19 02:40:54 - 0:40:55 - 680000 - Discriminator loss: 0.3251 - 4801 samples/s
INFO - 02/22/19 02:40:56 - 0:40:57 - 684000 - Discriminator loss: 0.3251 - 4551 samples/s
INFO - 02/22/19 02:40:57 - 0:40:58 - 688000 - Discriminator loss: 0.3251 - 4873 samples/s
INFO - 02/22/19 02:40:59 - 0:41:00 - 692000 - Discriminator loss: 0.3251 - 4657 samples/s
INFO - 02/22/19 02:41:01 - 0:41:02 - 696000 - Discriminator loss: 0.3251 - 4564 samples/s
INFO - 02/22/19 02:41:02 - 0:41:04 - 700000 - Discriminator loss: 0.3251 - 4922 samples/s
INFO - 02/22/19 02:41:04 - 0:41:05 - 704000 - Discriminator loss: 0.3251 - 4867 samples/s
INFO - 02/22/19 02:41:06 - 0:41:07 - 708000 - Discriminator loss: 0.3251 - 4886 samples/s
INFO - 02/22/19 02:41:07 - 0:41:08 - 712000 - Discriminator loss: 0.3251 - 4880 samples/s
INFO - 02/22/19 02:41:09 - 0:41:10 - 716000 - Discriminator loss: 0.3251 - 4810 samples/s
INFO - 02/22/19 02:41:11 - 0:41:12 - 720000 - Discriminator loss: 0.3251 - 4557 samples/s
INFO - 02/22/19 02:41:12 - 0:41:14 - 724000 - Discriminator loss: 0.3251 - 4872 samples/s
INFO - 02/22/19 02:41:14 - 0:41:15 - 728000 - Discriminator loss: 0.3251 - 4350 samples/s
INFO - 02/22/19 02:41:16 - 0:41:17 - 732000 - Discriminator loss: 0.3251 - 4748 samples/s
INFO - 02/22/19 02:41:18 - 0:41:19 - 736000 - Discriminator loss: 0.3251 - 4898 samples/s
INFO - 02/22/19 02:41:19 - 0:41:20 - 740000 - Discriminator loss: 0.3251 - 4814 samples/s
INFO - 02/22/19 02:41:21 - 0:41:22 - 744000 - Discriminator loss: 0.3251 - 4559 samples/s
INFO - 02/22/19 02:41:23 - 0:41:24 - 748000 - Discriminator loss: 0.3251 - 4884 samples/s
INFO - 02/22/19 02:41:24 - 0:41:25 - 752000 - Discriminator loss: 0.3251 - 5524 samples/s
INFO - 02/22/19 02:41:25 - 0:41:27 - 756000 - Discriminator loss: 0.3251 - 5887 samples/s
INFO - 02/22/19 02:41:27 - 0:41:28 - 760000 - Discriminator loss: 0.3251 - 5865 samples/s
INFO - 02/22/19 02:41:28 - 0:41:29 - 764000 - Discriminator loss: 0.3251 - 5253 samples/s
INFO - 02/22/19 02:41:30 - 0:41:31 - 768000 - Discriminator loss: 0.3251 - 4622 samples/s
INFO - 02/22/19 02:41:32 - 0:41:33 - 772000 - Discriminator loss: 0.3251 - 4686 samples/s
INFO - 02/22/19 02:41:33 - 0:41:35 - 776000 - Discriminator loss: 0.3251 - 4574 samples/s
INFO - 02/22/19 02:41:35 - 0:41:36 - 780000 - Discriminator loss: 0.3251 - 4857 samples/s
INFO - 02/22/19 02:41:37 - 0:41:38 - 784000 - Discriminator loss: 0.3251 - 4859 samples/s
INFO - 02/22/19 02:41:38 - 0:41:40 - 788000 - Discriminator loss: 0.3251 - 4867 samples/s
INFO - 02/22/19 02:41:40 - 0:41:41 - 792000 - Discriminator loss: 0.3251 - 4620 samples/s
INFO - 02/22/19 02:41:42 - 0:41:43 - 796000 - Discriminator loss: 0.3251 - 4739 samples/s
INFO - 02/22/19 02:41:43 - 0:41:45 - 800000 - Discriminator loss: 0.3251 - 4845 samples/s
INFO - 02/22/19 02:41:45 - 0:41:46 - 804000 - Discriminator loss: 0.3251 - 4663 samples/s
INFO - 02/22/19 02:41:47 - 0:41:48 - 808000 - Discriminator loss: 0.3251 - 4670 samples/s
INFO - 02/22/19 02:41:49 - 0:41:50 - 812000 - Discriminator loss: 0.3251 - 4518 samples/s
INFO - 02/22/19 02:41:50 - 0:41:51 - 816000 - Discriminator loss: 0.3251 - 4871 samples/s
INFO - 02/22/19 02:41:52 - 0:41:53 - 820000 - Discriminator loss: 0.3251 - 4542 samples/s
INFO - 02/22/19 02:41:54 - 0:41:55 - 824000 - Discriminator loss: 0.3251 - 4246 samples/s
INFO - 02/22/19 02:41:56 - 0:41:57 - 828000 - Discriminator loss: 0.3251 - 4894 samples/s
INFO - 02/22/19 02:41:57 - 0:41:58 - 832000 - Discriminator loss: 0.3251 - 4795 samples/s
INFO - 02/22/19 02:41:59 - 0:42:00 - 836000 - Discriminator loss: 0.3251 - 4676 samples/s
INFO - 02/22/19 02:42:01 - 0:42:02 - 840000 - Discriminator loss: 0.3251 - 4810 samples/s
INFO - 02/22/19 02:42:02 - 0:42:03 - 844000 - Discriminator loss: 0.3251 - 4701 samples/s
INFO - 02/22/19 02:42:04 - 0:42:05 - 848000 - Discriminator loss: 0.3251 - 4880 samples/s
INFO - 02/22/19 02:42:06 - 0:42:07 - 852000 - Discriminator loss: 0.3251 - 4608 samples/s
INFO - 02/22/19 02:42:07 - 0:42:09 - 856000 - Discriminator loss: 0.3251 - 4816 samples/s
INFO - 02/22/19 02:42:09 - 0:42:10 - 860000 - Discriminator loss: 0.3251 - 4853 samples/s
INFO - 02/22/19 02:42:11 - 0:42:12 - 864000 - Discriminator loss: 0.3251 - 4566 samples/s
INFO - 02/22/19 02:42:13 - 0:42:14 - 868000 - Discriminator loss: 0.3251 - 4465 samples/s
INFO - 02/22/19 02:42:14 - 0:42:15 - 872000 - Discriminator loss: 0.3251 - 4770 samples/s
INFO - 02/22/19 02:42:16 - 0:42:17 - 876000 - Discriminator loss: 0.3251 - 4447 samples/s
INFO - 02/22/19 02:42:18 - 0:42:19 - 880000 - Discriminator loss: 0.3251 - 4609 samples/s
INFO - 02/22/19 02:42:20 - 0:42:21 - 884000 - Discriminator loss: 0.3251 - 4412 samples/s
INFO - 02/22/19 02:42:21 - 0:42:22 - 888000 - Discriminator loss: 0.3251 - 4662 samples/s
INFO - 02/22/19 02:42:23 - 0:42:24 - 892000 - Discriminator loss: 0.3251 - 4808 samples/s
INFO - 02/22/19 02:42:25 - 0:42:26 - 896000 - Discriminator loss: 0.3251 - 4856 samples/s
INFO - 02/22/19 02:42:26 - 0:42:27 - 900000 - Discriminator loss: 0.3251 - 4861 samples/s
INFO - 02/22/19 02:42:28 - 0:42:29 - 904000 - Discriminator loss: 0.3251 - 4263 samples/s
INFO - 02/22/19 02:42:30 - 0:42:31 - 908000 - Discriminator loss: 0.3251 - 4817 samples/s
INFO - 02/22/19 02:42:32 - 0:42:33 - 912000 - Discriminator loss: 0.3251 - 4582 samples/s
INFO - 02/22/19 02:42:33 - 0:42:34 - 916000 - Discriminator loss: 0.3251 - 4839 samples/s
INFO - 02/22/19 02:42:35 - 0:42:36 - 920000 - Discriminator loss: 0.3251 - 4824 samples/s
INFO - 02/22/19 02:42:37 - 0:42:38 - 924000 - Discriminator loss: 0.3251 - 4588 samples/s
INFO - 02/22/19 02:42:38 - 0:42:39 - 928000 - Discriminator loss: 0.3251 - 4630 samples/s
INFO - 02/22/19 02:42:40 - 0:42:41 - 932000 - Discriminator loss: 0.3251 - 4808 samples/s
INFO - 02/22/19 02:42:42 - 0:42:43 - 936000 - Discriminator loss: 0.3251 - 4759 samples/s
INFO - 02/22/19 02:42:43 - 0:42:44 - 940000 - Discriminator loss: 0.3251 - 4979 samples/s
INFO - 02/22/19 02:42:45 - 0:42:46 - 944000 - Discriminator loss: 0.3251 - 4544 samples/s
INFO - 02/22/19 02:42:47 - 0:42:48 - 948000 - Discriminator loss: 0.3251 - 4641 samples/s
INFO - 02/22/19 02:42:48 - 0:42:50 - 952000 - Discriminator loss: 0.3251 - 4902 samples/s
INFO - 02/22/19 02:42:50 - 0:42:51 - 956000 - Discriminator loss: 0.3251 - 4662 samples/s
INFO - 02/22/19 02:42:52 - 0:42:53 - 960000 - Discriminator loss: 0.3251 - 4863 samples/s
INFO - 02/22/19 02:42:53 - 0:42:55 - 964000 - Discriminator loss: 0.3251 - 4595 samples/s
INFO - 02/22/19 02:42:55 - 0:42:56 - 968000 - Discriminator loss: 0.3251 - 4403 samples/s
INFO - 02/22/19 02:42:57 - 0:42:58 - 972000 - Discriminator loss: 0.3251 - 4845 samples/s
INFO - 02/22/19 02:42:59 - 0:43:00 - 976000 - Discriminator loss: 0.3251 - 4744 samples/s
INFO - 02/22/19 02:43:00 - 0:43:01 - 980000 - Discriminator loss: 0.3251 - 4917 samples/s
INFO - 02/22/19 02:43:02 - 0:43:03 - 984000 - Discriminator loss: 0.3251 - 4932 samples/s
INFO - 02/22/19 02:43:04 - 0:43:05 - 988000 - Discriminator loss: 0.3251 - 4890 samples/s
INFO - 02/22/19 02:43:05 - 0:43:06 - 992000 - Discriminator loss: 0.3251 - 4897 samples/s
INFO - 02/22/19 02:43:07 - 0:43:08 - 996000 - Discriminator loss: 0.3251 - 4628 samples/s
INFO - 02/22/19 02:43:23 - 0:43:25 - Building the train dictionary ...
INFO - 02/22/19 02:43:23 - 0:43:25 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:43:23 - 0:43:25 - Mean cosine (nn method, S2T build, 10000 max size): 0.25173
INFO - 02/22/19 02:44:57 - 0:44:59 - Building the train dictionary ...
INFO - 02/22/19 02:44:57 - 0:44:59 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:44:57 - 0:44:59 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.24678
INFO - 02/22/19 02:45:00 - 0:45:02 - Discriminator source / target predictions: 0.90055 / 0.18490
INFO - 02/22/19 02:45:01 - 0:45:02 - Discriminator source / target / global accuracy: 0.99978 / 0.92456 / 0.99253
INFO - 02/22/19 02:45:01 - 0:45:02 - __log__:{"n_epoch": 4, "mean_cosine-nn-S2T-10000": 0.2517326772212982, "mean_cosine-csls_knn_10-S2T-10000": 0.2467823177576065, "dis_accu": 0.9925281296821599, "dis_src_pred": 0.9005503580721241, "dis_tgt_pred": 0.18490251071443795}
INFO - 02/22/19 02:45:01 - 0:45:02 - End of epoch 4.
INFO - 02/22/19 02:45:01 - 0:45:02 - Decreasing learning rate: 0.02305920 -> 0.02259802
INFO - 02/22/19 02:45:01 - 0:45:02 - Validation metric is smaller than the best: 0.24678 vs 0.41910
INFO - 02/22/19 02:45:01 - 0:45:02 - Shrinking the learning rate: 0.02260 -> 0.01130
INFO - 02/22/19 02:45:01 - 0:45:02 - ----> ITERATIVE PROCRUSTES REFINEMENT <----
INFO - 02/22/19 02:45:01 - 0:45:02 - * Reloading the best model from data/masked_exps/v0mh1v198i/best_mapping.pth ...
INFO - 02/22/19 02:45:01 - 0:45:02 - Starting refinement iteration 0...
INFO - 02/22/19 02:45:01 - 0:45:02 - Building the train dictionary ...
INFO - 02/22/19 02:47:18 - 0:47:19 - New train dictionary of 830461 pairs.
INFO - 02/22/19 02:47:33 - 0:47:34 - Building the train dictionary ...
INFO - 02/22/19 02:47:33 - 0:47:34 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:47:33 - 0:47:34 - Mean cosine (nn method, S2T build, 10000 max size): 0.37498
INFO - 02/22/19 02:49:08 - 0:49:09 - Building the train dictionary ...
INFO - 02/22/19 02:49:08 - 0:49:09 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:49:08 - 0:49:09 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.33931
INFO - 02/22/19 02:49:08 - 0:49:09 - __log__:{"n_iter": 0, "mean_cosine-nn-S2T-10000": 0.37497684359550476, "mean_cosine-csls_knn_10-S2T-10000": 0.33931273221969604}
INFO - 02/22/19 02:49:08 - 0:49:09 - End of refinement iteration 0.
INFO - 02/22/19 02:49:08 - 0:49:09 - Starting refinement iteration 1...
INFO - 02/22/19 02:49:08 - 0:49:09 - Building the train dictionary ...
INFO - 02/22/19 02:51:25 - 0:51:26 - New train dictionary of 830461 pairs.
INFO - 02/22/19 02:51:40 - 0:51:41 - Building the train dictionary ...
INFO - 02/22/19 02:51:40 - 0:51:41 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:51:40 - 0:51:41 - Mean cosine (nn method, S2T build, 10000 max size): 0.36811
INFO - 02/22/19 02:53:15 - 0:53:17 - Building the train dictionary ...
INFO - 02/22/19 02:53:15 - 0:53:17 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:53:15 - 0:53:17 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.34041
INFO - 02/22/19 02:53:15 - 0:53:17 - __log__:{"n_iter": 1, "mean_cosine-nn-S2T-10000": 0.3681105077266693, "mean_cosine-csls_knn_10-S2T-10000": 0.34040942788124084}
INFO - 02/22/19 02:53:15 - 0:53:17 - End of refinement iteration 1.
INFO - 02/22/19 02:53:15 - 0:53:17 - Starting refinement iteration 2...
INFO - 02/22/19 02:53:15 - 0:53:17 - Building the train dictionary ...
INFO - 02/22/19 02:55:33 - 0:55:34 - New train dictionary of 830461 pairs.
INFO - 02/22/19 02:55:48 - 0:55:50 - Building the train dictionary ...
INFO - 02/22/19 02:55:48 - 0:55:50 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:55:48 - 0:55:50 - Mean cosine (nn method, S2T build, 10000 max size): 0.36648
INFO - 02/22/19 02:57:24 - 0:57:25 - Building the train dictionary ...
INFO - 02/22/19 02:57:24 - 0:57:25 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:57:24 - 0:57:25 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.34177
INFO - 02/22/19 02:57:24 - 0:57:26 - __log__:{"n_iter": 2, "mean_cosine-nn-S2T-10000": 0.36648139357566833, "mean_cosine-csls_knn_10-S2T-10000": 0.3417667746543884}
INFO - 02/22/19 02:57:24 - 0:57:26 - End of refinement iteration 2.
INFO - 02/22/19 02:57:24 - 0:57:26 - Starting refinement iteration 3...
INFO - 02/22/19 02:57:24 - 0:57:26 - Building the train dictionary ...
INFO - 02/22/19 02:59:42 - 0:59:43 - New train dictionary of 830461 pairs.
INFO - 02/22/19 02:59:58 - 0:59:59 - Building the train dictionary ...
INFO - 02/22/19 02:59:58 - 0:59:59 - New train dictionary of 10000 pairs.
INFO - 02/22/19 02:59:58 - 0:59:59 - Mean cosine (nn method, S2T build, 10000 max size): 0.36713
INFO - 02/22/19 03:01:33 - 1:01:34 - Building the train dictionary ...
INFO - 02/22/19 03:01:33 - 1:01:34 - New train dictionary of 10000 pairs.
INFO - 02/22/19 03:01:33 - 1:01:34 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.34305
INFO - 02/22/19 03:01:33 - 1:01:34 - __log__:{"n_iter": 3, "mean_cosine-nn-S2T-10000": 0.3671324849128723, "mean_cosine-csls_knn_10-S2T-10000": 0.3430549204349518}
INFO - 02/22/19 03:01:33 - 1:01:34 - End of refinement iteration 3.
INFO - 02/22/19 03:01:33 - 1:01:34 - Starting refinement iteration 4...
INFO - 02/22/19 03:01:33 - 1:01:34 - Building the train dictionary ...
INFO - 02/22/19 03:03:51 - 1:03:52 - New train dictionary of 830461 pairs.
INFO - 02/22/19 03:04:06 - 1:04:08 - Building the train dictionary ...
INFO - 02/22/19 03:04:06 - 1:04:08 - New train dictionary of 10000 pairs.
INFO - 02/22/19 03:04:07 - 1:04:08 - Mean cosine (nn method, S2T build, 10000 max size): 0.36807
INFO - 02/22/19 03:05:42 - 1:05:43 - Building the train dictionary ...
INFO - 02/22/19 03:05:42 - 1:05:43 - New train dictionary of 10000 pairs.
INFO - 02/22/19 03:05:42 - 1:05:43 - Mean cosine (csls_knn_10 method, S2T build, 10000 max size): 0.34439
INFO - 02/22/19 03:05:42 - 1:05:43 - __log__:{"n_iter": 4, "mean_cosine-nn-S2T-10000": 0.3680688738822937, "mean_cosine-csls_knn_10-S2T-10000": 0.34438517689704895}
INFO - 02/22/19 03:05:42 - 1:05:43 - End of refinement iteration 4.
INFO - 02/22/19 03:05:42 - 1:05:43 - * Reloading the best model from data/masked_exps/v0mh1v198i/best_mapping.pth ...
INFO - 02/22/19 03:05:42 - 1:05:43 - Reloading all embeddings for mapping ...
INFO - 02/22/19 03:06:44 - 1:06:46 - Loaded 999994 pre-trained word embeddings.
INFO - 02/22/19 03:06:54 - 1:06:55 - Loaded 88586 pre-trained word embeddings.
INFO - 02/22/19 03:06:54 - 1:06:55 - Map source embeddings to the target space ...
INFO - 02/22/19 03:06:55 - 1:06:56 - Writing source embeddings to data/masked_exps/v0mh1v198i/vectors-en.txt ...
INFO - 02/22/19 03:18:18 - 1:18:19 - Writing target embeddings to data/masked_exps/v0mh1v198i/vectors-meme.txt ...
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