aitech-sd-lab/slot-model-pl/training.log
2022-06-15 11:45:20 +02:00

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29 KiB
Plaintext

2022-06-08 12:31:41,621 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:41,621 Model: "SequenceTagger(
(embeddings): StackedEmbeddings(
(list_embedding_0): WordEmbeddings('pl')
(list_embedding_1): FlairEmbeddings(
(lm): LanguageModel(
(drop): Dropout(p=0.25, inplace=False)
(encoder): Embedding(1602, 100)
(rnn): LSTM(100, 2048)
(decoder): Linear(in_features=2048, out_features=1602, bias=True)
)
)
(list_embedding_2): FlairEmbeddings(
(lm): LanguageModel(
(drop): Dropout(p=0.25, inplace=False)
(encoder): Embedding(1602, 100)
(rnn): LSTM(100, 2048)
(decoder): Linear(in_features=2048, out_features=1602, bias=True)
)
)
(list_embedding_3): CharacterEmbeddings(
(char_embedding): Embedding(275, 25)
(char_rnn): LSTM(25, 25, bidirectional=True)
)
)
(word_dropout): WordDropout(p=0.05)
(locked_dropout): LockedDropout(p=0.5)
(embedding2nn): Linear(in_features=4446, out_features=4446, bias=True)
(rnn): LSTM(4446, 512, batch_first=True, bidirectional=True)
(linear): Linear(in_features=1024, out_features=29, bias=True)
(beta): 1.0
(weights): None
(weight_tensor) None
)"
2022-06-08 12:31:41,621 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:41,621 Corpus: "Corpus: 257 train + 28 dev + 285 test sentences"
2022-06-08 12:31:41,621 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:41,621 Parameters:
2022-06-08 12:31:41,621 - learning_rate: "0.1"
2022-06-08 12:31:41,621 - mini_batch_size: "32"
2022-06-08 12:31:41,621 - patience: "3"
2022-06-08 12:31:41,621 - anneal_factor: "0.5"
2022-06-08 12:31:41,621 - max_epochs: "20"
2022-06-08 12:31:41,621 - shuffle: "True"
2022-06-08 12:31:41,621 - train_with_dev: "True"
2022-06-08 12:31:41,621 - batch_growth_annealing: "False"
2022-06-08 12:31:41,621 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:41,621 Model training base path: "slot-model-pl"
2022-06-08 12:31:41,621 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:41,621 Device: cpu
2022-06-08 12:31:41,621 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:41,621 Embeddings storage mode: cpu
2022-06-08 12:31:41,622 ----------------------------------------------------------------------------------------------------
2022-06-08 12:31:46,029 epoch 1 - iter 1/9 - loss 3.53092505 - samples/sec: 7.26 - lr: 0.100000
2022-06-08 12:31:48,148 epoch 1 - iter 2/9 - loss 3.28223744 - samples/sec: 15.10 - lr: 0.100000
2022-06-08 12:31:50,661 epoch 1 - iter 3/9 - loss 2.76742561 - samples/sec: 12.73 - lr: 0.100000
2022-06-08 12:31:52,558 epoch 1 - iter 4/9 - loss 2.53094379 - samples/sec: 16.87 - lr: 0.100000
2022-06-08 12:31:54,728 epoch 1 - iter 5/9 - loss 2.46356121 - samples/sec: 14.75 - lr: 0.100000
2022-06-08 12:31:56,671 epoch 1 - iter 6/9 - loss 2.29996612 - samples/sec: 16.48 - lr: 0.100000
2022-06-08 12:31:59,234 epoch 1 - iter 7/9 - loss 2.13210413 - samples/sec: 12.48 - lr: 0.100000
2022-06-08 12:32:01,032 epoch 1 - iter 8/9 - loss 2.00977425 - samples/sec: 17.80 - lr: 0.100000
2022-06-08 12:32:02,765 epoch 1 - iter 9/9 - loss 1.96897361 - samples/sec: 18.47 - lr: 0.100000
2022-06-08 12:32:02,765 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:02,765 EPOCH 1 done: loss 1.9690 - lr 0.1000000
2022-06-08 12:32:02,765 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:02,766 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:03,476 epoch 2 - iter 1/9 - loss 1.13049648 - samples/sec: 45.10 - lr: 0.100000
2022-06-08 12:32:03,903 epoch 2 - iter 2/9 - loss 1.25789759 - samples/sec: 75.01 - lr: 0.100000
2022-06-08 12:32:04,434 epoch 2 - iter 3/9 - loss 1.22197871 - samples/sec: 60.37 - lr: 0.100000
2022-06-08 12:32:04,835 epoch 2 - iter 4/9 - loss 1.16841447 - samples/sec: 79.95 - lr: 0.100000
2022-06-08 12:32:05,316 epoch 2 - iter 5/9 - loss 1.16483816 - samples/sec: 66.46 - lr: 0.100000
2022-06-08 12:32:05,801 epoch 2 - iter 6/9 - loss 1.08971261 - samples/sec: 66.12 - lr: 0.100000
2022-06-08 12:32:06,195 epoch 2 - iter 7/9 - loss 1.03693444 - samples/sec: 81.21 - lr: 0.100000
2022-06-08 12:32:06,644 epoch 2 - iter 8/9 - loss 1.07878369 - samples/sec: 71.44 - lr: 0.100000
2022-06-08 12:32:07,111 epoch 2 - iter 9/9 - loss 1.05801050 - samples/sec: 68.48 - lr: 0.100000
2022-06-08 12:32:07,112 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:07,112 EPOCH 2 done: loss 1.0580 - lr 0.1000000
2022-06-08 12:32:07,112 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:07,112 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:07,549 epoch 3 - iter 1/9 - loss 0.99441444 - samples/sec: 73.34 - lr: 0.100000
2022-06-08 12:32:07,937 epoch 3 - iter 2/9 - loss 0.82194135 - samples/sec: 82.38 - lr: 0.100000
2022-06-08 12:32:08,448 epoch 3 - iter 3/9 - loss 0.89983319 - samples/sec: 62.70 - lr: 0.100000
2022-06-08 12:32:08,879 epoch 3 - iter 4/9 - loss 0.97584199 - samples/sec: 74.36 - lr: 0.100000
2022-06-08 12:32:09,398 epoch 3 - iter 5/9 - loss 0.98664173 - samples/sec: 61.73 - lr: 0.100000
2022-06-08 12:32:09,824 epoch 3 - iter 6/9 - loss 0.99321442 - samples/sec: 75.04 - lr: 0.100000
2022-06-08 12:32:10,473 epoch 3 - iter 7/9 - loss 0.94558628 - samples/sec: 49.32 - lr: 0.100000
2022-06-08 12:32:10,978 epoch 3 - iter 8/9 - loss 0.93600205 - samples/sec: 63.42 - lr: 0.100000
2022-06-08 12:32:11,418 epoch 3 - iter 9/9 - loss 0.92674317 - samples/sec: 72.88 - lr: 0.100000
2022-06-08 12:32:11,418 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:11,418 EPOCH 3 done: loss 0.9267 - lr 0.1000000
2022-06-08 12:32:11,419 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:11,419 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:11,853 epoch 4 - iter 1/9 - loss 0.91832127 - samples/sec: 73.79 - lr: 0.100000
2022-06-08 12:32:12,372 epoch 4 - iter 2/9 - loss 0.74006183 - samples/sec: 61.71 - lr: 0.100000
2022-06-08 12:32:12,874 epoch 4 - iter 3/9 - loss 0.68836276 - samples/sec: 63.77 - lr: 0.100000
2022-06-08 12:32:13,296 epoch 4 - iter 4/9 - loss 0.83504161 - samples/sec: 75.91 - lr: 0.100000
2022-06-08 12:32:13,973 epoch 4 - iter 5/9 - loss 0.75973124 - samples/sec: 47.27 - lr: 0.100000
2022-06-08 12:32:14,482 epoch 4 - iter 6/9 - loss 0.80884847 - samples/sec: 62.96 - lr: 0.100000
2022-06-08 12:32:15,009 epoch 4 - iter 7/9 - loss 0.80230532 - samples/sec: 60.74 - lr: 0.100000
2022-06-08 12:32:15,493 epoch 4 - iter 8/9 - loss 0.79063920 - samples/sec: 66.16 - lr: 0.100000
2022-06-08 12:32:15,984 epoch 4 - iter 9/9 - loss 0.79269722 - samples/sec: 65.18 - lr: 0.100000
2022-06-08 12:32:15,986 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:15,986 EPOCH 4 done: loss 0.7927 - lr 0.1000000
2022-06-08 12:32:15,986 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:15,987 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:16,497 epoch 5 - iter 1/9 - loss 0.82565074 - samples/sec: 62.76 - lr: 0.100000
2022-06-08 12:32:17,186 epoch 5 - iter 2/9 - loss 0.59513923 - samples/sec: 46.46 - lr: 0.100000
2022-06-08 12:32:17,613 epoch 5 - iter 3/9 - loss 0.57884253 - samples/sec: 75.17 - lr: 0.100000
2022-06-08 12:32:18,116 epoch 5 - iter 4/9 - loss 0.57740939 - samples/sec: 63.57 - lr: 0.100000
2022-06-08 12:32:18,666 epoch 5 - iter 5/9 - loss 0.58957181 - samples/sec: 58.30 - lr: 0.100000
2022-06-08 12:32:19,100 epoch 5 - iter 6/9 - loss 0.65262207 - samples/sec: 73.77 - lr: 0.100000
2022-06-08 12:32:19,483 epoch 5 - iter 7/9 - loss 0.69092686 - samples/sec: 83.63 - lr: 0.100000
2022-06-08 12:32:20,002 epoch 5 - iter 8/9 - loss 0.68317870 - samples/sec: 61.71 - lr: 0.100000
2022-06-08 12:32:20,435 epoch 5 - iter 9/9 - loss 0.70337522 - samples/sec: 73.87 - lr: 0.100000
2022-06-08 12:32:20,436 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:20,436 EPOCH 5 done: loss 0.7034 - lr 0.1000000
2022-06-08 12:32:20,436 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:20,436 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:20,882 epoch 6 - iter 1/9 - loss 1.03175259 - samples/sec: 71.80 - lr: 0.100000
2022-06-08 12:32:21,369 epoch 6 - iter 2/9 - loss 0.86526726 - samples/sec: 65.76 - lr: 0.100000
2022-06-08 12:32:21,872 epoch 6 - iter 3/9 - loss 0.74045897 - samples/sec: 63.72 - lr: 0.100000
2022-06-08 12:32:22,573 epoch 6 - iter 4/9 - loss 0.58234262 - samples/sec: 45.65 - lr: 0.100000
2022-06-08 12:32:23,105 epoch 6 - iter 5/9 - loss 0.59896642 - samples/sec: 60.20 - lr: 0.100000
2022-06-08 12:32:23,486 epoch 6 - iter 6/9 - loss 0.62850347 - samples/sec: 84.13 - lr: 0.100000
2022-06-08 12:32:23,929 epoch 6 - iter 7/9 - loss 0.60722084 - samples/sec: 72.25 - lr: 0.100000
2022-06-08 12:32:24,461 epoch 6 - iter 8/9 - loss 0.61184406 - samples/sec: 60.24 - lr: 0.100000
2022-06-08 12:32:24,870 epoch 6 - iter 9/9 - loss 0.62090710 - samples/sec: 78.39 - lr: 0.100000
2022-06-08 12:32:24,870 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:24,870 EPOCH 6 done: loss 0.6209 - lr 0.1000000
2022-06-08 12:32:24,870 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:24,870 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:25,393 epoch 7 - iter 1/9 - loss 0.42996832 - samples/sec: 61.22 - lr: 0.100000
2022-06-08 12:32:25,811 epoch 7 - iter 2/9 - loss 0.47978256 - samples/sec: 76.70 - lr: 0.100000
2022-06-08 12:32:26,337 epoch 7 - iter 3/9 - loss 0.46259552 - samples/sec: 60.82 - lr: 0.100000
2022-06-08 12:32:26,836 epoch 7 - iter 4/9 - loss 0.52414271 - samples/sec: 64.29 - lr: 0.100000
2022-06-08 12:32:27,271 epoch 7 - iter 5/9 - loss 0.56707858 - samples/sec: 73.59 - lr: 0.100000
2022-06-08 12:32:27,702 epoch 7 - iter 6/9 - loss 0.58077874 - samples/sec: 74.19 - lr: 0.100000
2022-06-08 12:32:28,106 epoch 7 - iter 7/9 - loss 0.58184246 - samples/sec: 79.34 - lr: 0.100000
2022-06-08 12:32:28,506 epoch 7 - iter 8/9 - loss 0.63482697 - samples/sec: 80.11 - lr: 0.100000
2022-06-08 12:32:29,129 epoch 7 - iter 9/9 - loss 0.61201910 - samples/sec: 51.41 - lr: 0.100000
2022-06-08 12:32:29,129 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:29,129 EPOCH 7 done: loss 0.6120 - lr 0.1000000
2022-06-08 12:32:29,129 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:29,130 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:29,639 epoch 8 - iter 1/9 - loss 0.64527700 - samples/sec: 62.87 - lr: 0.100000
2022-06-08 12:32:30,032 epoch 8 - iter 2/9 - loss 0.54730425 - samples/sec: 81.42 - lr: 0.100000
2022-06-08 12:32:30,513 epoch 8 - iter 3/9 - loss 0.50647674 - samples/sec: 66.58 - lr: 0.100000
2022-06-08 12:32:30,978 epoch 8 - iter 4/9 - loss 0.49661767 - samples/sec: 68.95 - lr: 0.100000
2022-06-08 12:32:31,669 epoch 8 - iter 5/9 - loss 0.53143074 - samples/sec: 46.32 - lr: 0.100000
2022-06-08 12:32:32,219 epoch 8 - iter 6/9 - loss 0.52587329 - samples/sec: 58.26 - lr: 0.100000
2022-06-08 12:32:32,675 epoch 8 - iter 7/9 - loss 0.54822063 - samples/sec: 70.17 - lr: 0.100000
2022-06-08 12:32:33,098 epoch 8 - iter 8/9 - loss 0.54919305 - samples/sec: 75.80 - lr: 0.100000
2022-06-08 12:32:33,467 epoch 8 - iter 9/9 - loss 0.54912585 - samples/sec: 86.62 - lr: 0.100000
2022-06-08 12:32:33,468 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:33,468 EPOCH 8 done: loss 0.5491 - lr 0.1000000
2022-06-08 12:32:33,468 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:33,468 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:33,969 epoch 9 - iter 1/9 - loss 0.47611675 - samples/sec: 63.93 - lr: 0.100000
2022-06-08 12:32:34,369 epoch 9 - iter 2/9 - loss 0.47816365 - samples/sec: 80.02 - lr: 0.100000
2022-06-08 12:32:34,822 epoch 9 - iter 3/9 - loss 0.58236918 - samples/sec: 70.75 - lr: 0.100000
2022-06-08 12:32:35,283 epoch 9 - iter 4/9 - loss 0.51142342 - samples/sec: 69.48 - lr: 0.100000
2022-06-08 12:32:35,815 epoch 9 - iter 5/9 - loss 0.51114643 - samples/sec: 60.22 - lr: 0.100000
2022-06-08 12:32:36,253 epoch 9 - iter 6/9 - loss 0.49820023 - samples/sec: 72.98 - lr: 0.100000
2022-06-08 12:32:36,688 epoch 9 - iter 7/9 - loss 0.46126831 - samples/sec: 73.70 - lr: 0.100000
2022-06-08 12:32:37,182 epoch 9 - iter 8/9 - loss 0.48042074 - samples/sec: 64.86 - lr: 0.100000
2022-06-08 12:32:37,814 epoch 9 - iter 9/9 - loss 0.49285321 - samples/sec: 50.63 - lr: 0.100000
2022-06-08 12:32:37,815 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:37,815 EPOCH 9 done: loss 0.4929 - lr 0.1000000
2022-06-08 12:32:37,815 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:37,815 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:38,267 epoch 10 - iter 1/9 - loss 0.31153137 - samples/sec: 70.80 - lr: 0.100000
2022-06-08 12:32:38,941 epoch 10 - iter 2/9 - loss 0.30746583 - samples/sec: 47.54 - lr: 0.100000
2022-06-08 12:32:39,417 epoch 10 - iter 3/9 - loss 0.38094732 - samples/sec: 67.21 - lr: 0.100000
2022-06-08 12:32:39,823 epoch 10 - iter 4/9 - loss 0.36053228 - samples/sec: 78.95 - lr: 0.100000
2022-06-08 12:32:40,308 epoch 10 - iter 5/9 - loss 0.37448425 - samples/sec: 66.09 - lr: 0.100000
2022-06-08 12:32:40,850 epoch 10 - iter 6/9 - loss 0.40578274 - samples/sec: 59.06 - lr: 0.100000
2022-06-08 12:32:41,328 epoch 10 - iter 7/9 - loss 0.44711766 - samples/sec: 67.00 - lr: 0.100000
2022-06-08 12:32:41,810 epoch 10 - iter 8/9 - loss 0.45301928 - samples/sec: 66.43 - lr: 0.100000
2022-06-08 12:32:42,189 epoch 10 - iter 9/9 - loss 0.46390399 - samples/sec: 84.59 - lr: 0.100000
2022-06-08 12:32:42,189 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:42,190 EPOCH 10 done: loss 0.4639 - lr 0.1000000
2022-06-08 12:32:42,191 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:42,191 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:42,844 epoch 11 - iter 1/9 - loss 0.48031266 - samples/sec: 49.03 - lr: 0.100000
2022-06-08 12:32:43,380 epoch 11 - iter 2/9 - loss 0.55838617 - samples/sec: 59.71 - lr: 0.100000
2022-06-08 12:32:43,869 epoch 11 - iter 3/9 - loss 0.50382959 - samples/sec: 65.58 - lr: 0.100000
2022-06-08 12:32:44,341 epoch 11 - iter 4/9 - loss 0.45667103 - samples/sec: 67.85 - lr: 0.100000
2022-06-08 12:32:44,834 epoch 11 - iter 5/9 - loss 0.42142408 - samples/sec: 64.96 - lr: 0.100000
2022-06-08 12:32:45,240 epoch 11 - iter 6/9 - loss 0.40860629 - samples/sec: 78.90 - lr: 0.100000
2022-06-08 12:32:45,728 epoch 11 - iter 7/9 - loss 0.42365533 - samples/sec: 65.63 - lr: 0.100000
2022-06-08 12:32:46,154 epoch 11 - iter 8/9 - loss 0.40978381 - samples/sec: 75.23 - lr: 0.100000
2022-06-08 12:32:46,591 epoch 11 - iter 9/9 - loss 0.41781582 - samples/sec: 73.25 - lr: 0.100000
2022-06-08 12:32:46,591 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:46,592 EPOCH 11 done: loss 0.4178 - lr 0.1000000
2022-06-08 12:32:46,592 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:46,592 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:46,988 epoch 12 - iter 1/9 - loss 0.54559433 - samples/sec: 80.81 - lr: 0.100000
2022-06-08 12:32:47,441 epoch 12 - iter 2/9 - loss 0.44864207 - samples/sec: 70.71 - lr: 0.100000
2022-06-08 12:32:47,932 epoch 12 - iter 3/9 - loss 0.52948530 - samples/sec: 65.17 - lr: 0.100000
2022-06-08 12:32:48,336 epoch 12 - iter 4/9 - loss 0.48952658 - samples/sec: 79.33 - lr: 0.100000
2022-06-08 12:32:48,776 epoch 12 - iter 5/9 - loss 0.48488877 - samples/sec: 72.86 - lr: 0.100000
2022-06-08 12:32:49,267 epoch 12 - iter 6/9 - loss 0.43026232 - samples/sec: 65.19 - lr: 0.100000
2022-06-08 12:32:49,951 epoch 12 - iter 7/9 - loss 0.38224156 - samples/sec: 46.77 - lr: 0.100000
2022-06-08 12:32:50,441 epoch 12 - iter 8/9 - loss 0.40093438 - samples/sec: 65.47 - lr: 0.100000
2022-06-08 12:32:50,855 epoch 12 - iter 9/9 - loss 0.41922607 - samples/sec: 77.23 - lr: 0.100000
2022-06-08 12:32:50,856 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:50,856 EPOCH 12 done: loss 0.4192 - lr 0.1000000
2022-06-08 12:32:50,856 BAD EPOCHS (no improvement): 1
2022-06-08 12:32:50,856 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:51,536 epoch 13 - iter 1/9 - loss 0.31159168 - samples/sec: 47.05 - lr: 0.100000
2022-06-08 12:32:51,957 epoch 13 - iter 2/9 - loss 0.38716744 - samples/sec: 76.12 - lr: 0.100000
2022-06-08 12:32:52,341 epoch 13 - iter 3/9 - loss 0.33405638 - samples/sec: 83.50 - lr: 0.100000
2022-06-08 12:32:52,738 epoch 13 - iter 4/9 - loss 0.35984076 - samples/sec: 80.66 - lr: 0.100000
2022-06-08 12:32:53,234 epoch 13 - iter 5/9 - loss 0.36767183 - samples/sec: 64.53 - lr: 0.100000
2022-06-08 12:32:53,689 epoch 13 - iter 6/9 - loss 0.38457662 - samples/sec: 70.42 - lr: 0.100000
2022-06-08 12:32:54,193 epoch 13 - iter 7/9 - loss 0.38993635 - samples/sec: 63.51 - lr: 0.100000
2022-06-08 12:32:54,716 epoch 13 - iter 8/9 - loss 0.39294463 - samples/sec: 61.29 - lr: 0.100000
2022-06-08 12:32:55,067 epoch 13 - iter 9/9 - loss 0.37855191 - samples/sec: 91.24 - lr: 0.100000
2022-06-08 12:32:55,067 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:55,068 EPOCH 13 done: loss 0.3786 - lr 0.1000000
2022-06-08 12:32:55,068 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:55,068 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:55,451 epoch 14 - iter 1/9 - loss 0.30355526 - samples/sec: 83.48 - lr: 0.100000
2022-06-08 12:32:55,990 epoch 14 - iter 2/9 - loss 0.33328859 - samples/sec: 59.41 - lr: 0.100000
2022-06-08 12:32:56,492 epoch 14 - iter 3/9 - loss 0.30427931 - samples/sec: 63.88 - lr: 0.100000
2022-06-08 12:32:56,949 epoch 14 - iter 4/9 - loss 0.37132272 - samples/sec: 70.11 - lr: 0.100000
2022-06-08 12:32:57,337 epoch 14 - iter 5/9 - loss 0.35030109 - samples/sec: 82.49 - lr: 0.100000
2022-06-08 12:32:58,016 epoch 14 - iter 6/9 - loss 0.32296200 - samples/sec: 47.16 - lr: 0.100000
2022-06-08 12:32:58,529 epoch 14 - iter 7/9 - loss 0.35116036 - samples/sec: 62.40 - lr: 0.100000
2022-06-08 12:32:58,943 epoch 14 - iter 8/9 - loss 0.35482794 - samples/sec: 77.42 - lr: 0.100000
2022-06-08 12:32:59,298 epoch 14 - iter 9/9 - loss 0.35575370 - samples/sec: 90.24 - lr: 0.100000
2022-06-08 12:32:59,298 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:59,298 EPOCH 14 done: loss 0.3558 - lr 0.1000000
2022-06-08 12:32:59,298 BAD EPOCHS (no improvement): 0
2022-06-08 12:32:59,298 ----------------------------------------------------------------------------------------------------
2022-06-08 12:32:59,776 epoch 15 - iter 1/9 - loss 0.31286285 - samples/sec: 67.00 - lr: 0.100000
2022-06-08 12:33:00,275 epoch 15 - iter 2/9 - loss 0.25396872 - samples/sec: 64.25 - lr: 0.100000
2022-06-08 12:33:00,963 epoch 15 - iter 3/9 - loss 0.22052628 - samples/sec: 46.56 - lr: 0.100000
2022-06-08 12:33:01,477 epoch 15 - iter 4/9 - loss 0.23660956 - samples/sec: 62.21 - lr: 0.100000
2022-06-08 12:33:01,912 epoch 15 - iter 5/9 - loss 0.29349516 - samples/sec: 73.75 - lr: 0.100000
2022-06-08 12:33:02,342 epoch 15 - iter 6/9 - loss 0.34446268 - samples/sec: 74.46 - lr: 0.100000
2022-06-08 12:33:02,820 epoch 15 - iter 7/9 - loss 0.35994147 - samples/sec: 66.98 - lr: 0.100000
2022-06-08 12:33:03,333 epoch 15 - iter 8/9 - loss 0.34855257 - samples/sec: 62.40 - lr: 0.100000
2022-06-08 12:33:03,743 epoch 15 - iter 9/9 - loss 0.35364645 - samples/sec: 78.20 - lr: 0.100000
2022-06-08 12:33:03,743 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:03,743 EPOCH 15 done: loss 0.3536 - lr 0.1000000
2022-06-08 12:33:03,743 BAD EPOCHS (no improvement): 0
2022-06-08 12:33:03,744 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:04,126 epoch 16 - iter 1/9 - loss 0.28729343 - samples/sec: 83.81 - lr: 0.100000
2022-06-08 12:33:04,639 epoch 16 - iter 2/9 - loss 0.33799034 - samples/sec: 62.41 - lr: 0.100000
2022-06-08 12:33:05,003 epoch 16 - iter 3/9 - loss 0.34162027 - samples/sec: 87.98 - lr: 0.100000
2022-06-08 12:33:05,484 epoch 16 - iter 4/9 - loss 0.30522357 - samples/sec: 66.58 - lr: 0.100000
2022-06-08 12:33:05,974 epoch 16 - iter 5/9 - loss 0.28432292 - samples/sec: 65.29 - lr: 0.100000
2022-06-08 12:33:06,658 epoch 16 - iter 6/9 - loss 0.28570045 - samples/sec: 46.81 - lr: 0.100000
2022-06-08 12:33:07,177 epoch 16 - iter 7/9 - loss 0.28308125 - samples/sec: 61.78 - lr: 0.100000
2022-06-08 12:33:07,661 epoch 16 - iter 8/9 - loss 0.30916664 - samples/sec: 66.19 - lr: 0.100000
2022-06-08 12:33:08,080 epoch 16 - iter 9/9 - loss 0.32331857 - samples/sec: 76.39 - lr: 0.100000
2022-06-08 12:33:08,080 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:08,080 EPOCH 16 done: loss 0.3233 - lr 0.1000000
2022-06-08 12:33:08,080 BAD EPOCHS (no improvement): 0
2022-06-08 12:33:08,081 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:08,453 epoch 17 - iter 1/9 - loss 0.30244277 - samples/sec: 85.97 - lr: 0.100000
2022-06-08 12:33:08,945 epoch 17 - iter 2/9 - loss 0.25602389 - samples/sec: 65.03 - lr: 0.100000
2022-06-08 12:33:09,369 epoch 17 - iter 3/9 - loss 0.34607508 - samples/sec: 75.65 - lr: 0.100000
2022-06-08 12:33:09,829 epoch 17 - iter 4/9 - loss 0.34229970 - samples/sec: 69.56 - lr: 0.100000
2022-06-08 12:33:10,280 epoch 17 - iter 5/9 - loss 0.31807536 - samples/sec: 71.11 - lr: 0.100000
2022-06-08 12:33:10,812 epoch 17 - iter 6/9 - loss 0.31284894 - samples/sec: 60.11 - lr: 0.100000
2022-06-08 12:33:11,290 epoch 17 - iter 7/9 - loss 0.31391356 - samples/sec: 67.03 - lr: 0.100000
2022-06-08 12:33:11,756 epoch 17 - iter 8/9 - loss 0.30151306 - samples/sec: 68.68 - lr: 0.100000
2022-06-08 12:33:12,391 epoch 17 - iter 9/9 - loss 0.28364693 - samples/sec: 50.46 - lr: 0.100000
2022-06-08 12:33:12,391 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:12,391 EPOCH 17 done: loss 0.2836 - lr 0.1000000
2022-06-08 12:33:12,391 BAD EPOCHS (no improvement): 0
2022-06-08 12:33:12,392 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:12,752 epoch 18 - iter 1/9 - loss 0.20885737 - samples/sec: 88.87 - lr: 0.100000
2022-06-08 12:33:13,431 epoch 18 - iter 2/9 - loss 0.22186524 - samples/sec: 47.12 - lr: 0.100000
2022-06-08 12:33:13,900 epoch 18 - iter 3/9 - loss 0.27817430 - samples/sec: 68.35 - lr: 0.100000
2022-06-08 12:33:14,432 epoch 18 - iter 4/9 - loss 0.30294052 - samples/sec: 60.15 - lr: 0.100000
2022-06-08 12:33:14,804 epoch 18 - iter 5/9 - loss 0.30746071 - samples/sec: 86.18 - lr: 0.100000
2022-06-08 12:33:15,281 epoch 18 - iter 6/9 - loss 0.33365668 - samples/sec: 67.16 - lr: 0.100000
2022-06-08 12:33:15,739 epoch 18 - iter 7/9 - loss 0.31930171 - samples/sec: 69.94 - lr: 0.100000
2022-06-08 12:33:16,182 epoch 18 - iter 8/9 - loss 0.29281456 - samples/sec: 72.28 - lr: 0.100000
2022-06-08 12:33:16,668 epoch 18 - iter 9/9 - loss 0.28747182 - samples/sec: 65.85 - lr: 0.100000
2022-06-08 12:33:16,669 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:16,669 EPOCH 18 done: loss 0.2875 - lr 0.1000000
2022-06-08 12:33:16,669 BAD EPOCHS (no improvement): 1
2022-06-08 12:33:16,669 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:17,046 epoch 19 - iter 1/9 - loss 0.24014797 - samples/sec: 84.92 - lr: 0.100000
2022-06-08 12:33:17,738 epoch 19 - iter 2/9 - loss 0.22314876 - samples/sec: 46.25 - lr: 0.100000
2022-06-08 12:33:18,166 epoch 19 - iter 3/9 - loss 0.25412370 - samples/sec: 74.96 - lr: 0.100000
2022-06-08 12:33:18,669 epoch 19 - iter 4/9 - loss 0.26213705 - samples/sec: 63.69 - lr: 0.100000
2022-06-08 12:33:19,187 epoch 19 - iter 5/9 - loss 0.22226194 - samples/sec: 61.81 - lr: 0.100000
2022-06-08 12:33:19,676 epoch 19 - iter 6/9 - loss 0.22840251 - samples/sec: 65.48 - lr: 0.100000
2022-06-08 12:33:20,051 epoch 19 - iter 7/9 - loss 0.23390501 - samples/sec: 85.35 - lr: 0.100000
2022-06-08 12:33:20,499 epoch 19 - iter 8/9 - loss 0.23054385 - samples/sec: 71.55 - lr: 0.100000
2022-06-08 12:33:20,928 epoch 19 - iter 9/9 - loss 0.23232295 - samples/sec: 74.69 - lr: 0.100000
2022-06-08 12:33:20,928 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:20,928 EPOCH 19 done: loss 0.2323 - lr 0.1000000
2022-06-08 12:33:20,928 BAD EPOCHS (no improvement): 0
2022-06-08 12:33:20,928 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:21,405 epoch 20 - iter 1/9 - loss 0.25521260 - samples/sec: 67.18 - lr: 0.100000
2022-06-08 12:33:21,948 epoch 20 - iter 2/9 - loss 0.24103518 - samples/sec: 58.94 - lr: 0.100000
2022-06-08 12:33:22,439 epoch 20 - iter 3/9 - loss 0.20574912 - samples/sec: 65.28 - lr: 0.100000
2022-06-08 12:33:23,081 epoch 20 - iter 4/9 - loss 0.20291896 - samples/sec: 49.89 - lr: 0.100000
2022-06-08 12:33:23,505 epoch 20 - iter 5/9 - loss 0.21600028 - samples/sec: 75.44 - lr: 0.100000
2022-06-08 12:33:23,925 epoch 20 - iter 6/9 - loss 0.22897579 - samples/sec: 76.29 - lr: 0.100000
2022-06-08 12:33:24,419 epoch 20 - iter 7/9 - loss 0.21609014 - samples/sec: 64.82 - lr: 0.100000
2022-06-08 12:33:24,854 epoch 20 - iter 8/9 - loss 0.23529377 - samples/sec: 73.66 - lr: 0.100000
2022-06-08 12:33:25,240 epoch 20 - iter 9/9 - loss 0.23821406 - samples/sec: 82.98 - lr: 0.100000
2022-06-08 12:33:25,240 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:25,240 EPOCH 20 done: loss 0.2382 - lr 0.1000000
2022-06-08 12:33:25,240 BAD EPOCHS (no improvement): 1
2022-06-08 12:33:49,710 ----------------------------------------------------------------------------------------------------
2022-06-08 12:33:49,717 Testing using last state of model ...
2022-06-08 12:34:10,642 0.7471 0.8089 0.7768 0.6791
2022-06-08 12:34:10,642
Results:
- F-score (micro) 0.7768
- F-score (macro) 0.451
- Accuracy 0.6791
By class:
precision recall f1-score support
movie 0.7241 0.9130 0.8077 23
quantity 0.6923 0.9474 0.8000 19
seat 0.7222 0.7647 0.7429 17
tickettype 0.7000 1.0000 0.8235 14
hour 0.9333 0.8750 0.9032 16
date 0.6667 0.7143 0.6897 14
e-mail 0.8000 1.0000 0.8889 12
name 1.0000 1.0000 1.0000 13
row 0.5000 0.4286 0.4615 14
phone 1.0000 1.0000 1.0000 6
ticketType 0.0000 0.0000 0.0000 2
issue 0.0000 0.0000 0.0000 1
bankAccountNumber 0.0000 0.0000 0.0000 1
email 0.0000 0.0000 0.0000 1
itickettype 0.0000 0.0000 0.0000 1
details 0.0000 0.0000 0.0000 1
purchaseType 0.0000 0.0000 0.0000 1
genre 0.0000 0.0000 0.0000 1
micro avg 0.7471 0.8089 0.7768 157
macro avg 0.4299 0.4802 0.4510 157
weighted avg 0.7118 0.8089 0.7527 157
samples avg 0.6791 0.6791 0.6791 157
2022-06-08 12:34:10,642 ----------------------------------------------------------------------------------------------------