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tripadviosr.1.log
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-----------------------------ARGUMENTS-----------------------------
gpu_device 0
data_path ../data/TripAdvisor/reviews.pickle
data_ratio 8:1:1
index_dir ../data/TripAdvisor/1/
rating_layer_num 4
latent_dim 200
word_dim 200
rnn_dim 256
seq_max_len 15
max_word_num 20000
dropout_keep 0.8
max_epoch_num 100
batch_size 128
learning_rate 0.0001
reg_rate 0.0001
use_predicted_feature 0
prediction_path tripadvisor.1
top_k 5
-----------------------------ARGUMENTS-----------------------------
[2020-08-12 15:36:47.399983]: iteration 1
[2020-08-12 15:37:00.599668]: loss on train set: 1.130553807747136
[2020-08-12 15:37:01.158575]: loss on validation set: 0.9264054888915616
[2020-08-12 15:37:01.817642]: iteration 2
[2020-08-12 15:37:14.195880]: loss on train set: 0.8360102910338537
[2020-08-12 15:37:14.697749]: loss on validation set: 0.8101324167175447
[2020-08-12 15:37:15.318053]: iteration 3
[2020-08-12 15:37:27.707913]: loss on train set: 0.7715903631915892
[2020-08-12 15:37:28.241750]: loss on validation set: 0.7963375362275011
[2020-08-12 15:37:28.897900]: iteration 4
[2020-08-12 15:37:41.930881]: loss on train set: 0.7522262064405173
[2020-08-12 15:37:42.414709]: loss on validation set: 0.7842284015611324
[2020-08-12 15:37:43.015418]: iteration 5
[2020-08-12 15:37:56.073890]: loss on train set: 0.7402424369317894
[2020-08-12 15:37:56.593781]: loss on validation set: 0.7734414771097718
[2020-08-12 15:37:57.246574]: iteration 6
[2020-08-12 15:38:10.545366]: loss on train set: 0.7298189917608205
[2020-08-12 15:38:11.090095]: loss on validation set: 0.7650007148935127
[2020-08-12 15:38:11.745065]: iteration 7
[2020-08-12 15:38:24.998353]: loss on train set: 0.7211827758253322
[2020-08-12 15:38:25.550074]: loss on validation set: 0.7645158852072748
[2020-08-12 15:38:26.224618]: iteration 8
[2020-08-12 15:38:39.106285]: loss on train set: 0.7140957626780978
[2020-08-12 15:38:39.584158]: loss on validation set: 0.748384203030075
[2020-08-12 15:38:40.106112]: iteration 9
[2020-08-12 15:38:52.939533]: loss on train set: 0.70633038810948
[2020-08-12 15:38:53.488027]: loss on validation set: 0.7752407275824299
[2020-08-12 15:38:53.488198]: early stopped
[2020-08-12 15:38:53.840877]: RMSE on test set: 0.7919474844253149
[2020-08-12 15:38:54.161398]: MAE on test set: 0.6060067049969704
[2020-08-12 15:54:29.921824]: NDCG on test set: 0.0009998090745070702
[2020-08-12 15:54:29.947348]: Precision on test set: 0.0009581881533101046
[2020-08-12 15:54:29.947475]: HR on test set: 0.0013135335434987002
[2020-08-12 15:54:29.947507]: F1 on test set: 0.0010351981061911381
[2020-08-12 15:54:33.260223]: iteration 1
[2020-08-12 15:56:43.480705]: loss on train set: 5.928447370844536
[2020-08-12 15:56:50.025059]: loss on validation set: 5.266956607324393
[2020-08-12 15:57:00.352093]: iteration 2
[2020-08-12 15:59:10.134453]: loss on train set: 5.0373267139414875
[2020-08-12 15:59:16.607376]: loss on validation set: 4.845521304080072
[2020-08-12 15:59:26.768525]: iteration 3
[2020-08-12 16:01:36.658872]: loss on train set: 4.753875388043001
[2020-08-12 16:01:43.094468]: loss on validation set: 4.654811049511966
[2020-08-12 16:01:53.309214]: iteration 4
[2020-08-12 16:04:03.224136]: loss on train set: 4.58572408112193
[2020-08-12 16:04:09.697834]: loss on validation set: 4.5283577242953115
[2020-08-12 16:04:19.904706]: iteration 5
[2020-08-12 16:06:29.364457]: loss on train set: 4.456819274648654
[2020-08-12 16:06:35.959144]: loss on validation set: 4.42231089669044
[2020-08-12 16:06:46.151573]: iteration 6
[2020-08-12 16:08:55.505748]: loss on train set: 4.308668853165489
[2020-08-12 16:09:02.009652]: loss on validation set: 4.2606889665011325
[2020-08-12 16:09:12.293672]: iteration 7
[2020-08-12 16:11:21.191471]: loss on train set: 4.155090634838807
[2020-08-12 16:11:27.667848]: loss on validation set: 4.1422799995009445
[2020-08-12 16:11:37.987579]: iteration 8
[2020-08-12 16:13:47.751501]: loss on train set: 4.042737207253363
[2020-08-12 16:13:54.229551]: loss on validation set: 4.059697506524765
[2020-08-12 16:14:04.389852]: iteration 9
[2020-08-12 16:16:14.527614]: loss on train set: 3.9564651890193794
[2020-08-12 16:16:21.061588]: loss on validation set: 3.999866931440383
[2020-08-12 16:16:31.260563]: iteration 10
[2020-08-12 16:18:41.802634]: loss on train set: 3.8869119161036307
[2020-08-12 16:18:48.304391]: loss on validation set: 3.951555372111448
[2020-08-12 16:18:58.512138]: iteration 11
[2020-08-12 16:21:08.301805]: loss on train set: 3.8277145468110017
[2020-08-12 16:21:14.823091]: loss on validation set: 3.913284335551534
[2020-08-12 16:21:25.057006]: iteration 12
[2020-08-12 16:23:35.471299]: loss on train set: 3.7767417527374545
[2020-08-12 16:23:41.976348]: loss on validation set: 3.8812884721791145
[2020-08-12 16:23:52.170948]: iteration 13
[2020-08-12 16:26:02.448685]: loss on train set: 3.730880811417852
[2020-08-12 16:26:08.988774]: loss on validation set: 3.855218724111983
[2020-08-12 16:26:19.181489]: iteration 14
[2020-08-12 16:28:29.674196]: loss on train set: 3.689661892686568
[2020-08-12 16:28:36.079625]: loss on validation set: 3.8323904388018395
[2020-08-12 16:28:46.293977]: iteration 15
[2020-08-12 16:30:56.544454]: loss on train set: 3.652248691205586
[2020-08-12 16:31:03.050660]: loss on validation set: 3.813087768267411
[2020-08-12 16:31:13.297895]: iteration 16
[2020-08-12 16:33:23.370258]: loss on train set: 3.6171105885828077
[2020-08-12 16:33:29.853473]: loss on validation set: 3.7961530413942617
[2020-08-12 16:33:40.096176]: iteration 17
[2020-08-12 16:35:49.606092]: loss on train set: 3.584955030690831
[2020-08-12 16:35:56.155881]: loss on validation set: 3.782277455144238
[2020-08-12 16:36:06.368091]: iteration 18
[2020-08-12 16:38:16.533380]: loss on train set: 3.554867918110349
[2020-08-12 16:38:23.060930]: loss on validation set: 3.7694379940799427
[2020-08-12 16:38:33.317122]: iteration 19
[2020-08-12 16:40:43.370435]: loss on train set: 3.5265016311293893
[2020-08-12 16:40:49.836934]: loss on validation set: 3.7576595243755917
[2020-08-12 16:41:00.088695]: iteration 20
[2020-08-12 16:43:10.173988]: loss on train set: 3.4997820997321227
[2020-08-12 16:43:16.727458]: loss on validation set: 3.7482998682241067
[2020-08-12 16:43:27.015578]: iteration 21
[2020-08-12 16:45:37.291316]: loss on train set: 3.474292882142971
[2020-08-12 16:45:43.754707]: loss on validation set: 3.7400107956492867
[2020-08-12 16:45:53.999205]: iteration 22
[2020-08-12 16:48:04.125008]: loss on train set: 3.4502589394546352
[2020-08-12 16:48:10.632847]: loss on validation set: 3.7330596909494105
[2020-08-12 16:48:20.880893]: iteration 23
[2020-08-12 16:50:30.862362]: loss on train set: 3.427186363668619
[2020-08-12 16:50:37.398473]: loss on validation set: 3.7275455890242126
[2020-08-12 16:50:47.636085]: iteration 24
[2020-08-12 16:52:57.333892]: loss on train set: 3.405634684494478
[2020-08-12 16:53:03.909844]: loss on validation set: 3.723139159746911
[2020-08-12 16:53:14.264055]: iteration 25
[2020-08-12 16:55:23.852366]: loss on train set: 3.3840863628597693
[2020-08-12 16:55:30.388124]: loss on validation set: 3.717286692791511
[2020-08-12 16:55:40.696269]: iteration 26
[2020-08-12 16:57:50.706508]: loss on train set: 3.3639047734453866
[2020-08-12 16:57:57.227518]: loss on validation set: 3.7142539676089084
[2020-08-12 16:58:07.511384]: iteration 27
[2020-08-12 17:00:17.933427]: loss on train set: 3.3447995540567876
[2020-08-12 17:00:24.449332]: loss on validation set: 3.711165109639406
[2020-08-12 17:00:34.642097]: iteration 28
[2020-08-12 17:02:44.594669]: loss on train set: 3.325935606958009
[2020-08-12 17:02:51.020012]: loss on validation set: 3.7098418644730518
[2020-08-12 17:03:01.251482]: iteration 29
[2020-08-12 17:05:11.172983]: loss on train set: 3.3075255159409447
[2020-08-12 17:05:17.749538]: loss on validation set: 3.70795406254297
[2020-08-12 17:05:27.987486]: iteration 30
[2020-08-12 17:07:38.448194]: loss on train set: 3.289891774751109
[2020-08-12 17:07:44.917608]: loss on validation set: 3.7071932347057297
[2020-08-12 17:07:55.121610]: iteration 31
[2020-08-12 17:10:04.157634]: loss on train set: 3.272759637982462
[2020-08-12 17:10:10.677628]: loss on validation set: 3.7060183536469227
[2020-08-12 17:10:20.886247]: iteration 32
[2020-08-12 17:12:27.726612]: loss on train set: 3.2560920481214
[2020-08-12 17:12:34.050944]: loss on validation set: 3.7054396682467714
[2020-08-12 17:12:44.267500]: iteration 33
[2020-08-12 17:14:49.848877]: loss on train set: 3.239693456444874
[2020-08-12 17:14:56.132534]: loss on validation set: 3.705630825248467
[2020-08-12 17:14:56.133115]: early stopped
[2020-08-12 17:15:53.490967]: USN on test set: 18725
[2020-08-12 17:15:53.491487]: USR on test set: 0.5851013967440553
[2020-08-12 17:34:14.648193]: DIV on test set: 2.242828951084817
[2020-08-12 17:34:14.667225]: FCR on test set: 0.2811832875876792
[2020-08-12 17:34:14.948827]: FMR on test set: 0.7701153016904665
[2020-08-12 17:34:16.299148]: BLEU-1 on test set: 22.439736218717286
[2020-08-12 17:34:20.134335]: BLEU-4 on test set: 3.5679012138761306
[2020-08-12 17:34:23.482678]: ROUGE on test set:
rouge_1/f_score: 27.499900945288005
rouge_1/r_score: 24.872329356596456
rouge_1/p_score: 34.95033509821185
rouge_2/f_score: 7.424527714540482
rouge_2/r_score: 6.800076084830639
rouge_2/p_score: 9.800007562561072
rouge_l/f_score: 20.862521528885274
rouge_l/r_score: 21.823924564292653
rouge_l/p_score: 28.284305018204964
[2020-08-12 17:34:24.405509]: saved predicted text on test set