From 993e635b8a067708354721234d0c1d43434af70f Mon Sep 17 00:00:00 2001 From: Anna Nowak Date: Sun, 16 May 2021 19:26:52 +0200 Subject: [PATCH] Zmiany w notebooku --- 07-parsing-semantyczny-uczenie.ipynb | 1047 +++++++++++++++++++++----- 1 file changed, 843 insertions(+), 204 deletions(-) diff --git a/07-parsing-semantyczny-uczenie.ipynb b/07-parsing-semantyczny-uczenie.ipynb index 05e001f..b6ca1e9 100644 --- a/07-parsing-semantyczny-uczenie.ipynb +++ b/07-parsing-semantyczny-uczenie.ipynb @@ -66,23 +66,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "C:\\Users\\Ania\\Desktop\\System_Dialogowy_Janet\\l07\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "A subdirectory or file -p already exists.\n", - "Error occurred while processing: -p.\n", - "A subdirectory or file l07 already exists.\n", - "Error occurred while processing: l07.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "C:\\Users\\Ania\\Desktop\\System_Dialogowy_Janet\\l07\n", "C:\\Users\\Ania\\Desktop\\System_Dialogowy_Janet\n" ] }, @@ -90,15 +74,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "** Resuming transfer from byte position 8923190\n", " % Total % Received % Xferd Average Speed Time Time Time Current\n", " Dload Upload Total Spent Left Speed\n", "\n", " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n", " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n", - "\n", " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n", - "100 49 100 49 0 0 56 0 --:--:-- --:--:-- --:--:-- 742\n" + "\n", + " 0 8714k 0 1656 0 0 886 0 2:47:51 0:00:01 2:47:50 886\n", + " 4 8714k 4 406k 0 0 167k 0 0:00:52 0:00:02 0:00:50 721k\n", + " 33 8714k 33 2957k 0 0 863k 0 0:00:10 0:00:03 0:00:07 1898k\n", + " 69 8714k 69 6035k 0 0 1387k 0 0:00:06 0:00:04 0:00:02 2429k\n", + "100 8714k 100 8714k 0 0 1703k 0 0:00:05 0:00:05 --:--:-- 2683k\n" ] } ], @@ -138,9 +125,9 @@ "def nolabel2o(line, i):\n", " return 'O' if line[i] == 'NoLabel' else line[i]\n", "\n", - "with open('Janet_test.conllu', encoding='utf-8') as trainfile:\n", + "with open('Janet.conllu', encoding='utf-8') as trainfile:\n", " trainset = list(parse_incr(trainfile, fields=fields, field_parsers={'slot': nolabel2o}))\n", - "with open('Janet_test.conllu', encoding='utf-8') as testfile:\n", + "with open('Janet.conllu', encoding='utf-8') as testfile:\n", " testset = list(parse_incr(testfile, fields=fields, field_parsers={'slot': nolabel2o}))" ] }, @@ -168,12 +155,20 @@ "text/html": [ "\n", "\n", - "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", "\n", "
1hejgreetingO
1chciałem appointment/request_prescriptionO
2prosić appointment/request_prescriptionO
3o appointment/request_prescriptionO
4wypisanieappointment/request_prescriptionO
5kolejnej appointment/request_prescriptionO
6recepty appointment/request_prescriptionB-prescription
7na appointment/request_prescriptionO
8lek appointment/request_prescriptionB-prescription/type
9x appointment/request_prescriptionI-prescription/type
" ], "text/plain": [ - "'\\n\\n\\n\\n
1hejgreetingO
'" + "'\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n
1chciałem appointment/request_prescriptionO
2prosić appointment/request_prescriptionO
3o appointment/request_prescriptionO
4wypisanieappointment/request_prescriptionO
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6recepty appointment/request_prescriptionB-prescription
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'" ] }, "execution_count": 3, @@ -214,58 +209,58 @@ "output_type": "stream", "text": [ "Requirement already satisfied: flair in c:\\programdata\\anaconda3\\lib\\site-packages (0.8.0.post1)\n", - "Requirement already satisfied: huggingface-hub in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (0.0.8)\n", - "Requirement already satisfied: mpld3==0.3 in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (0.3)\n", + "Requirement already satisfied: deprecated>=1.2.4 in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (1.2.12)\n", + "Requirement already satisfied: janome in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (0.4.1)\n", "Requirement already satisfied: langdetect in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (1.0.9)\n", "Requirement already satisfied: hyperopt>=0.1.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (0.2.5)\n", - "Requirement already satisfied: tabulate in c:\\programdata\\anaconda3\\lib\\site-packages (from flair) (0.8.9)\n", - 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"Requirement already satisfied: typing-extensions in c:\\programdata\\anaconda3\\lib\\site-packages (from torch) (3.7.4.3)\n", - "Requirement already satisfied: numpy in c:\\programdata\\anaconda3\\lib\\site-packages (from torch) (1.19.2)\n" + "Requirement already satisfied: numpy in c:\\programdata\\anaconda3\\lib\\site-packages (from torch) (1.19.2)\n", + "Requirement already satisfied: typing-extensions in c:\\programdata\\anaconda3\\lib\\site-packages (from torch) (3.7.4.3)\n" ] } ], @@ -331,8 +326,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Corpus: 36 train + 4 dev + 40 test sentences\n", - "Dictionary with 13 tags: , O, B-appoinment/doctor, I-appoinment/doctor, B-datetime, I-datetime, B-login/id, B-appointment/type, I-appointment/type, B-prescription/type, B-login/password, , \n" + "Corpus: 99 train + 11 dev + 110 test sentences\n", + "Dictionary with 31 tags: , O, B-prescription, B-prescription/type, I-prescription/type, B-end_conversation, B-deny, I-end_conversation, B-greeting, I-greeting, B-appointment, B-appointment/doctor, I-appointment/doctor, B-datetime, NoLabel I-end_conversation, I-datetime, B-affirm, B-appointment/office, I-B-datetime, B-results, B-appointment/type, I-appointment/type, B-register/email, B-doctor, I-affirm, B-appoinment/doctor, B-appoinment, B-register/name, I-register/name, \n" ] } ], @@ -432,7 +427,7 @@ " (locked_dropout): LockedDropout(p=0.5)\n", " (embedding2nn): Linear(in_features=4446, out_features=4446, bias=True)\n", " (rnn): LSTM(4446, 256, batch_first=True, bidirectional=True)\n", - " (linear): Linear(in_features=512, out_features=13, bias=True)\n", + " (linear): Linear(in_features=512, out_features=31, bias=True)\n", " (beta): 1.0\n", " (weights): None\n", " (weight_tensor) None\n", @@ -460,8 +455,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "2021-05-16 11:40:14,273 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:14,274 Model: \"SequenceTagger(\n", + "2021-05-16 19:11:09,838 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:09,846 Model: \"SequenceTagger(\n", " (embeddings): StackedEmbeddings(\n", " (list_embedding_0): WordEmbeddings('pl')\n", " (list_embedding_1): FlairEmbeddings(\n", @@ -489,154 +484,783 @@ " (locked_dropout): LockedDropout(p=0.5)\n", " (embedding2nn): Linear(in_features=4446, out_features=4446, bias=True)\n", " (rnn): LSTM(4446, 256, batch_first=True, bidirectional=True)\n", - " (linear): Linear(in_features=512, out_features=13, bias=True)\n", + " (linear): Linear(in_features=512, out_features=31, bias=True)\n", " (beta): 1.0\n", " (weights): None\n", " (weight_tensor) None\n", ")\"\n", - "2021-05-16 11:40:14,275 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:14,277 Corpus: \"Corpus: 36 train + 4 dev + 40 test sentences\"\n", - "2021-05-16 11:40:14,277 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:14,278 Parameters:\n", - "2021-05-16 11:40:14,279 - learning_rate: \"0.1\"\n", - "2021-05-16 11:40:14,280 - mini_batch_size: \"32\"\n", - "2021-05-16 11:40:14,280 - patience: \"3\"\n", - "2021-05-16 11:40:14,281 - anneal_factor: \"0.5\"\n", - "2021-05-16 11:40:14,282 - max_epochs: \"10\"\n", - "2021-05-16 11:40:14,283 - shuffle: \"True\"\n", - "2021-05-16 11:40:14,285 - train_with_dev: \"False\"\n", - "2021-05-16 11:40:14,286 - batch_growth_annealing: \"False\"\n", - "2021-05-16 11:40:14,287 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:14,288 Model training base path: \"slot-model\"\n", - "2021-05-16 11:40:14,288 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:14,289 Device: cpu\n", - "2021-05-16 11:40:14,290 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:14,292 Embeddings storage mode: cpu\n", - "2021-05-16 11:40:14,295 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:18,737 epoch 1 - iter 1/2 - loss 13.17695141 - samples/sec: 7.21 - lr: 0.100000\n", - "2021-05-16 11:40:19,989 epoch 1 - iter 2/2 - loss 11.51309586 - samples/sec: 25.57 - lr: 0.100000\n", - "2021-05-16 11:40:19,989 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:19,989 EPOCH 1 done: loss 11.5131 - lr 0.1000000\n", - "2021-05-16 11:40:20,670 DEV : loss 5.320306777954102 - score 0.0\n", - "2021-05-16 11:40:20,671 BAD EPOCHS (no improvement): 0\n", + "2021-05-16 19:11:09,846 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:09,846 Corpus: \"Corpus: 99 train + 11 dev + 110 test sentences\"\n", + "2021-05-16 19:11:09,846 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:09,846 Parameters:\n", + "2021-05-16 19:11:09,854 - learning_rate: \"0.1\"\n", + "2021-05-16 19:11:09,854 - mini_batch_size: \"32\"\n", + "2021-05-16 19:11:09,854 - patience: \"3\"\n", + "2021-05-16 19:11:09,854 - anneal_factor: \"0.5\"\n", + "2021-05-16 19:11:09,854 - max_epochs: \"100\"\n", + "2021-05-16 19:11:09,854 - shuffle: \"True\"\n", + "2021-05-16 19:11:09,854 - train_with_dev: \"False\"\n", + "2021-05-16 19:11:09,854 - batch_growth_annealing: \"False\"\n", + "2021-05-16 19:11:09,862 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:09,862 Model training base path: \"slot-model\"\n", + "2021-05-16 19:11:09,862 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:09,862 Device: cpu\n", + "2021-05-16 19:11:09,862 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:09,862 Embeddings storage mode: cpu\n", + "2021-05-16 19:11:09,870 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:12,779 epoch 1 - iter 1/4 - loss 23.51556206 - samples/sec: 11.00 - lr: 0.100000\n", + "2021-05-16 19:11:16,270 epoch 1 - iter 2/4 - loss 19.95522118 - samples/sec: 9.17 - lr: 0.100000\n", + "2021-05-16 19:11:19,989 epoch 1 - iter 3/4 - loss 18.64025307 - samples/sec: 8.64 - lr: 0.100000\n", + "2021-05-16 19:11:20,665 epoch 1 - iter 4/4 - loss 16.56225991 - samples/sec: 47.34 - lr: 0.100000\n", + "2021-05-16 19:11:20,665 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:20,665 EPOCH 1 done: loss 16.5623 - lr 0.1000000\n", + "2021-05-16 19:11:23,175 DEV : loss 12.217952728271484 - score 0.0\n", + "2021-05-16 19:11:23,175 BAD EPOCHS (no improvement): 0\n", "saving best model\n", - "2021-05-16 11:40:30,073 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:30,802 epoch 2 - iter 1/2 - loss 8.20096970 - samples/sec: 45.04 - lr: 0.100000\n", - "2021-05-16 11:40:31,005 epoch 2 - iter 2/2 - loss 5.87843704 - samples/sec: 157.40 - lr: 0.100000\n", - "2021-05-16 11:40:31,006 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:31,008 EPOCH 2 done: loss 5.8784 - lr 0.1000000\n", - "2021-05-16 11:40:31,020 DEV : loss 2.201185703277588 - score 0.0\n", - "2021-05-16 11:40:31,038 BAD EPOCHS (no improvement): 0\n", + "2021-05-16 19:11:31,472 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:32,200 epoch 2 - iter 1/4 - loss 13.48146439 - samples/sec: 44.15 - lr: 0.100000\n", + "2021-05-16 19:11:32,902 epoch 2 - iter 2/4 - loss 13.13387251 - samples/sec: 45.60 - lr: 0.100000\n", + "2021-05-16 19:11:33,485 epoch 2 - iter 3/4 - loss 12.05493037 - samples/sec: 54.92 - lr: 0.100000\n", + "2021-05-16 19:11:33,672 epoch 2 - iter 4/4 - loss 10.83767450 - samples/sec: 170.46 - lr: 0.100000\n", + "2021-05-16 19:11:33,672 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:33,672 EPOCH 2 done: loss 10.8377 - lr 0.1000000\n", + "2021-05-16 19:11:33,768 DEV : loss 8.176359176635742 - score 0.0\n", + "2021-05-16 19:11:33,771 BAD EPOCHS (no improvement): 0\n", "saving best model\n", - "2021-05-16 11:40:40,878 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:41,800 epoch 3 - iter 1/2 - loss 3.59802794 - samples/sec: 34.83 - lr: 0.100000\n", - "2021-05-16 11:40:42,230 epoch 3 - iter 2/2 - loss 7.24588382 - samples/sec: 74.64 - lr: 0.100000\n", - "2021-05-16 11:40:42,231 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:42,233 EPOCH 3 done: loss 7.2459 - lr 0.1000000\n", - "2021-05-16 11:40:42,290 DEV : loss 2.3815672397613525 - score 0.0\n", - "2021-05-16 11:40:42,295 BAD EPOCHS (no improvement): 1\n", - "2021-05-16 11:40:42,300 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:43,662 epoch 4 - iter 1/2 - loss 4.05115032 - samples/sec: 23.57 - lr: 0.100000\n", - "2021-05-16 11:40:44,013 epoch 4 - iter 2/2 - loss 3.16846037 - samples/sec: 91.53 - lr: 0.100000\n", - "2021-05-16 11:40:44,015 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:44,018 EPOCH 4 done: loss 3.1685 - lr 0.1000000\n", - "2021-05-16 11:40:44,072 DEV : loss 1.7660648822784424 - score 0.0\n", - "2021-05-16 11:40:44,075 BAD EPOCHS (no improvement): 0\n", + "2021-05-16 19:11:42,363 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:43,054 epoch 3 - iter 1/4 - loss 9.78410912 - samples/sec: 46.31 - lr: 0.100000\n", + "2021-05-16 19:11:43,672 epoch 3 - iter 2/4 - loss 9.88690376 - samples/sec: 51.75 - lr: 0.100000\n", + "2021-05-16 19:11:44,405 epoch 3 - iter 3/4 - loss 9.67457644 - samples/sec: 43.69 - lr: 0.100000\n", + "2021-05-16 19:11:44,589 epoch 3 - iter 4/4 - loss 8.94925010 - samples/sec: 173.35 - lr: 0.100000\n", + "2021-05-16 19:11:44,589 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:44,589 EPOCH 3 done: loss 8.9493 - lr 0.1000000\n", + "2021-05-16 19:11:44,693 DEV : loss 7.451809883117676 - score 0.0\n", + "2021-05-16 19:11:44,693 BAD EPOCHS (no improvement): 0\n", "saving best model\n", - "2021-05-16 11:40:53,620 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:54,419 epoch 5 - iter 1/2 - loss 3.52825356 - samples/sec: 40.10 - lr: 0.100000\n", - "2021-05-16 11:40:54,594 epoch 5 - iter 2/2 - loss 3.12245941 - samples/sec: 183.91 - lr: 0.100000\n", - "2021-05-16 11:40:54,595 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:54,596 EPOCH 5 done: loss 3.1225 - lr 0.1000000\n", - "2021-05-16 11:40:54,624 DEV : loss 1.8835055828094482 - score 0.0\n", - "2021-05-16 11:40:54,626 BAD EPOCHS (no improvement): 1\n", - "2021-05-16 11:40:54,627 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:55,393 epoch 6 - iter 1/2 - loss 2.84318709 - samples/sec: 41.88 - lr: 0.100000\n", - "2021-05-16 11:40:55,648 epoch 6 - iter 2/2 - loss 4.79819477 - samples/sec: 125.98 - lr: 0.100000\n", - "2021-05-16 11:40:55,649 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:55,650 EPOCH 6 done: loss 4.7982 - lr 0.1000000\n", - "2021-05-16 11:40:55,675 DEV : loss 1.9106686115264893 - score 0.0\n", - "2021-05-16 11:40:55,677 BAD EPOCHS (no improvement): 2\n", - "2021-05-16 11:40:55,678 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:56,467 epoch 7 - iter 1/2 - loss 3.35292196 - samples/sec: 40.66 - lr: 0.100000\n", - "2021-05-16 11:40:56,661 epoch 7 - iter 2/2 - loss 1.90253919 - samples/sec: 165.80 - lr: 0.100000\n", - "2021-05-16 11:40:56,662 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:40:56,663 EPOCH 7 done: loss 1.9025 - lr 0.1000000\n", - "2021-05-16 11:40:56,689 DEV : loss 1.5785303115844727 - score 0.0\n", - "2021-05-16 11:40:56,691 BAD EPOCHS (no improvement): 0\n", + "2021-05-16 19:11:53,845 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:54,437 epoch 4 - iter 1/4 - loss 8.59626198 - samples/sec: 55.55 - lr: 0.100000\n", + "2021-05-16 19:11:55,150 epoch 4 - iter 2/4 - loss 8.40540457 - samples/sec: 44.85 - lr: 0.100000\n", + "2021-05-16 19:11:55,995 epoch 4 - iter 3/4 - loss 8.39408366 - samples/sec: 37.88 - lr: 0.100000\n", + "2021-05-16 19:11:56,222 epoch 4 - iter 4/4 - loss 7.31822419 - samples/sec: 141.22 - lr: 0.100000\n", + "2021-05-16 19:11:56,222 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:56,222 EPOCH 4 done: loss 7.3182 - lr 0.1000000\n", + "2021-05-16 19:11:56,309 DEV : loss 7.464598178863525 - score 0.0\n", + "2021-05-16 19:11:56,309 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:11:56,309 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:57,036 epoch 5 - iter 1/4 - loss 7.71572590 - samples/sec: 44.96 - lr: 0.100000\n", + "2021-05-16 19:11:57,744 epoch 5 - iter 2/4 - loss 8.43728781 - samples/sec: 45.20 - lr: 0.100000\n", + "2021-05-16 19:11:58,488 epoch 5 - iter 3/4 - loss 7.66639407 - samples/sec: 43.01 - lr: 0.100000\n", + "2021-05-16 19:11:58,705 epoch 5 - iter 4/4 - loss 8.57210910 - samples/sec: 147.23 - lr: 0.100000\n", + "2021-05-16 19:11:58,705 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:11:58,705 EPOCH 5 done: loss 8.5721 - lr 0.1000000\n", + "2021-05-16 19:11:58,801 DEV : loss 7.330676555633545 - score 0.0645\n", + "2021-05-16 19:11:58,809 BAD EPOCHS (no improvement): 0\n", "saving best model\n", - "2021-05-16 11:41:09,226 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:10,375 epoch 8 - iter 1/2 - loss 3.24992299 - samples/sec: 27.87 - lr: 0.100000\n", - "2021-05-16 11:41:10,744 epoch 8 - iter 2/2 - loss 3.30123496 - samples/sec: 87.17 - lr: 0.100000\n", - "2021-05-16 11:41:10,745 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:10,746 EPOCH 8 done: loss 3.3012 - lr 0.1000000\n", - "2021-05-16 11:41:10,798 DEV : loss 1.590420126914978 - score 0.0\n", - "2021-05-16 11:41:10,802 BAD EPOCHS (no improvement): 1\n", - "2021-05-16 11:41:10,807 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:12,175 epoch 9 - iter 1/2 - loss 2.74546242 - samples/sec: 23.41 - lr: 0.100000\n", - "2021-05-16 11:41:12,515 epoch 9 - iter 2/2 - loss 2.34704965 - samples/sec: 94.40 - lr: 0.100000\n", - "2021-05-16 11:41:12,518 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:12,520 EPOCH 9 done: loss 2.3470 - lr 0.1000000\n", - "2021-05-16 11:41:12,573 DEV : loss 1.6068150997161865 - score 0.0\n" + "2021-05-16 19:12:09,132 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:10,066 epoch 6 - iter 1/4 - loss 6.82695341 - samples/sec: 34.26 - lr: 0.100000\n", + "2021-05-16 19:12:10,923 epoch 6 - iter 2/4 - loss 6.71814942 - samples/sec: 37.31 - lr: 0.100000\n", + "2021-05-16 19:12:11,835 epoch 6 - iter 3/4 - loss 7.02111626 - samples/sec: 35.09 - lr: 0.100000\n", + "2021-05-16 19:12:12,029 epoch 6 - iter 4/4 - loss 8.55612421 - samples/sec: 165.49 - lr: 0.100000\n", + "2021-05-16 19:12:12,029 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:12,029 EPOCH 6 done: loss 8.5561 - lr 0.1000000\n", + "2021-05-16 19:12:12,117 DEV : loss 5.898077011108398 - score 0.0\n", + "2021-05-16 19:12:12,117 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:12:12,117 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:12,829 epoch 7 - iter 1/4 - loss 3.95063305 - samples/sec: 45.47 - lr: 0.100000\n", + "2021-05-16 19:12:13,605 epoch 7 - iter 2/4 - loss 4.73969674 - samples/sec: 41.22 - lr: 0.100000\n", + "2021-05-16 19:12:14,424 epoch 7 - iter 3/4 - loss 6.22298797 - samples/sec: 39.08 - lr: 0.100000\n", + "2021-05-16 19:12:14,648 epoch 7 - iter 4/4 - loss 7.01634419 - samples/sec: 142.74 - lr: 0.100000\n", + "2021-05-16 19:12:14,648 ----------------------------------------------------------------------------------------------------\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "2021-05-16 11:41:12,575 BAD EPOCHS (no improvement): 2\n", - "2021-05-16 11:41:12,577 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:13,690 epoch 10 - iter 1/2 - loss 2.63941884 - samples/sec: 28.79 - lr: 0.100000\n", - "2021-05-16 11:41:13,878 epoch 10 - iter 2/2 - loss 2.18226165 - samples/sec: 171.12 - lr: 0.100000\n", - "2021-05-16 11:41:13,879 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:13,880 EPOCH 10 done: loss 2.1823 - lr 0.1000000\n", - "2021-05-16 11:41:13,906 DEV : loss 1.458857536315918 - score 0.0\n", - "2021-05-16 11:41:13,907 BAD EPOCHS (no improvement): 0\n", + "2021-05-16 19:12:14,648 EPOCH 7 done: loss 7.0163 - lr 0.1000000\n", + "2021-05-16 19:12:14,745 DEV : loss 5.496520519256592 - score 0.1538\n", + "2021-05-16 19:12:14,745 BAD EPOCHS (no improvement): 0\n", "saving best model\n", - "2021-05-16 11:41:33,558 ----------------------------------------------------------------------------------------------------\n", - "2021-05-16 11:41:33,559 Testing using best model ...\n", - "2021-05-16 11:41:33,560 loading file slot-model\\best-model.pt\n", - "2021-05-16 11:41:45,502 0.1765\t0.1667\t0.1714\n", - "2021-05-16 11:41:45,503 \n", + "2021-05-16 19:12:24,553 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:25,305 epoch 8 - iter 1/4 - loss 5.84166050 - samples/sec: 43.01 - lr: 0.100000\n", + "2021-05-16 19:12:26,009 epoch 8 - iter 2/4 - loss 5.58190751 - samples/sec: 45.43 - lr: 0.100000\n", + "2021-05-16 19:12:26,803 epoch 8 - iter 3/4 - loss 6.09121291 - samples/sec: 40.28 - lr: 0.100000\n", + "2021-05-16 19:12:27,011 epoch 8 - iter 4/4 - loss 5.20219183 - samples/sec: 153.85 - lr: 0.100000\n", + "2021-05-16 19:12:27,011 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:27,011 EPOCH 8 done: loss 5.2022 - lr 0.1000000\n", + "2021-05-16 19:12:27,099 DEV : loss 5.2129292488098145 - score 0.3478\n", + "2021-05-16 19:12:27,099 BAD EPOCHS (no improvement): 0\n", + "saving best model\n", + "2021-05-16 19:12:37,200 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:37,968 epoch 9 - iter 1/4 - loss 6.38291883 - samples/sec: 41.64 - lr: 0.100000\n", + "2021-05-16 19:12:38,703 epoch 9 - iter 2/4 - loss 6.26358747 - samples/sec: 43.56 - lr: 0.100000\n", + "2021-05-16 19:12:39,284 epoch 9 - iter 3/4 - loss 5.50593615 - samples/sec: 55.03 - lr: 0.100000\n", + "2021-05-16 19:12:39,476 epoch 9 - iter 4/4 - loss 4.59320381 - samples/sec: 166.66 - lr: 0.100000\n", + "2021-05-16 19:12:39,476 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:39,476 EPOCH 9 done: loss 4.5932 - lr 0.1000000\n", + "2021-05-16 19:12:39,580 DEV : loss 4.9869303703308105 - score 0.2609\n", + "2021-05-16 19:12:39,580 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:12:39,590 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:40,387 epoch 10 - iter 1/4 - loss 4.83267832 - samples/sec: 40.15 - lr: 0.100000\n", + "2021-05-16 19:12:41,158 epoch 10 - iter 2/4 - loss 4.78956985 - samples/sec: 41.52 - lr: 0.100000\n", + "2021-05-16 19:12:41,792 epoch 10 - iter 3/4 - loss 4.80196079 - samples/sec: 50.47 - lr: 0.100000\n", + "2021-05-16 19:12:41,993 epoch 10 - iter 4/4 - loss 4.40808117 - samples/sec: 158.79 - lr: 0.100000\n", + "2021-05-16 19:12:42,001 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:42,001 EPOCH 10 done: loss 4.4081 - lr 0.1000000\n", + "2021-05-16 19:12:42,089 DEV : loss 4.855195045471191 - score 0.3077\n", + "2021-05-16 19:12:42,089 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:12:42,097 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:42,780 epoch 11 - iter 1/4 - loss 3.66451931 - samples/sec: 46.87 - lr: 0.100000\n", + "2021-05-16 19:12:43,666 epoch 11 - iter 2/4 - loss 4.65244174 - samples/sec: 36.16 - lr: 0.100000\n", + "2021-05-16 19:12:44,456 epoch 11 - iter 3/4 - loss 4.58611314 - samples/sec: 40.51 - lr: 0.100000\n", + "2021-05-16 19:12:44,648 epoch 11 - iter 4/4 - loss 4.86016536 - samples/sec: 166.85 - lr: 0.100000\n", + "2021-05-16 19:12:44,656 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:44,656 EPOCH 11 done: loss 4.8602 - lr 0.1000000\n", + "2021-05-16 19:12:44,737 DEV : loss 4.352779865264893 - score 0.3478\n", + "2021-05-16 19:12:44,745 BAD EPOCHS (no improvement): 0\n", + "saving best model\n", + "2021-05-16 19:12:53,094 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:53,668 epoch 12 - iter 1/4 - loss 3.02415586 - samples/sec: 55.76 - lr: 0.100000\n", + "2021-05-16 19:12:54,381 epoch 12 - iter 2/4 - loss 3.78920162 - samples/sec: 44.90 - lr: 0.100000\n", + "2021-05-16 19:12:55,097 epoch 12 - iter 3/4 - loss 4.02983785 - samples/sec: 44.67 - lr: 0.100000\n", + "2021-05-16 19:12:55,304 epoch 12 - iter 4/4 - loss 3.44744644 - samples/sec: 154.91 - lr: 0.100000\n", + "2021-05-16 19:12:55,304 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:55,304 EPOCH 12 done: loss 3.4474 - lr 0.1000000\n", + "2021-05-16 19:12:55,402 DEV : loss 4.364665508270264 - score 0.3333\n", + "2021-05-16 19:12:55,402 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:12:55,414 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:56,003 epoch 13 - iter 1/4 - loss 4.21208715 - samples/sec: 54.32 - lr: 0.100000\n", + "2021-05-16 19:12:56,765 epoch 13 - iter 2/4 - loss 4.02075458 - samples/sec: 42.01 - lr: 0.100000\n", + "2021-05-16 19:12:57,528 epoch 13 - iter 3/4 - loss 3.93069355 - samples/sec: 41.92 - lr: 0.100000\n", + "2021-05-16 19:12:57,757 epoch 13 - iter 4/4 - loss 4.47141653 - samples/sec: 139.66 - lr: 0.100000\n", + "2021-05-16 19:12:57,757 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:12:57,757 EPOCH 13 done: loss 4.4714 - lr 0.1000000\n", + "2021-05-16 19:12:57,856 DEV : loss 4.251131057739258 - score 0.4615\n", + "2021-05-16 19:12:57,856 BAD EPOCHS (no improvement): 0\n", + "saving best model\n", + "2021-05-16 19:13:07,766 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:08,603 epoch 14 - iter 1/4 - loss 4.07004356 - samples/sec: 38.23 - lr: 0.100000\n", + "2021-05-16 19:13:09,137 epoch 14 - iter 2/4 - loss 3.58775365 - samples/sec: 60.00 - lr: 0.100000\n", + "2021-05-16 19:13:09,805 epoch 14 - iter 3/4 - loss 3.37540340 - samples/sec: 49.04 - lr: 0.100000\n", + "2021-05-16 19:13:10,017 epoch 14 - iter 4/4 - loss 3.30140239 - samples/sec: 150.99 - lr: 0.100000\n", + "2021-05-16 19:13:10,017 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:10,017 EPOCH 14 done: loss 3.3014 - lr 0.1000000\n", + "2021-05-16 19:13:10,108 DEV : loss 3.9291062355041504 - score 0.4348\n", + "2021-05-16 19:13:10,108 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:13:10,126 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:10,799 epoch 15 - iter 1/4 - loss 4.12087154 - samples/sec: 47.53 - lr: 0.100000\n", + "2021-05-16 19:13:11,479 epoch 15 - iter 2/4 - loss 3.45777619 - samples/sec: 47.09 - lr: 0.100000\n", + "2021-05-16 19:13:12,230 epoch 15 - iter 3/4 - loss 3.44035808 - samples/sec: 42.59 - lr: 0.100000\n", + "2021-05-16 19:13:12,392 epoch 15 - iter 4/4 - loss 2.90269253 - samples/sec: 197.83 - lr: 0.100000\n", + "2021-05-16 19:13:12,408 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:12,408 EPOCH 15 done: loss 2.9027 - lr 0.1000000\n", + "2021-05-16 19:13:12,498 DEV : loss 4.368889808654785 - score 0.6923\n", + "2021-05-16 19:13:12,498 BAD EPOCHS (no improvement): 0\n", + "saving best model\n", + "2021-05-16 19:13:22,020 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:22,716 epoch 16 - iter 1/4 - loss 2.49819446 - samples/sec: 45.95 - lr: 0.100000\n", + "2021-05-16 19:13:23,466 epoch 16 - iter 2/4 - loss 3.36824119 - samples/sec: 43.59 - lr: 0.100000\n", + "2021-05-16 19:13:24,067 epoch 16 - iter 3/4 - loss 3.36522110 - samples/sec: 53.20 - lr: 0.100000\n", + "2021-05-16 19:13:24,253 epoch 16 - iter 4/4 - loss 3.36765742 - samples/sec: 188.42 - lr: 0.100000\n", + "2021-05-16 19:13:24,253 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:24,253 EPOCH 16 done: loss 3.3677 - lr 0.1000000\n", + "2021-05-16 19:13:24,348 DEV : loss 3.6790337562561035 - score 0.5833\n", + "2021-05-16 19:13:24,348 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:13:24,356 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:24,905 epoch 17 - iter 1/4 - loss 3.17663288 - samples/sec: 58.35 - lr: 0.100000\n", + "2021-05-16 19:13:25,620 epoch 17 - iter 2/4 - loss 3.24819005 - samples/sec: 44.73 - lr: 0.100000\n", + "2021-05-16 19:13:26,267 epoch 17 - iter 3/4 - loss 2.86507106 - samples/sec: 49.44 - lr: 0.100000\n", + "2021-05-16 19:13:26,483 epoch 17 - iter 4/4 - loss 4.03450483 - samples/sec: 160.21 - lr: 0.100000\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2021-05-16 19:13:26,483 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:26,483 EPOCH 17 done: loss 4.0345 - lr 0.1000000\n", + "2021-05-16 19:13:26,579 DEV : loss 3.864961862564087 - score 0.6154\n", + "2021-05-16 19:13:26,580 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:13:26,583 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:27,322 epoch 18 - iter 1/4 - loss 3.06332946 - samples/sec: 43.30 - lr: 0.100000\n", + "2021-05-16 19:13:27,901 epoch 18 - iter 2/4 - loss 3.11640310 - samples/sec: 55.27 - lr: 0.100000\n", + "2021-05-16 19:13:28,698 epoch 18 - iter 3/4 - loss 2.99107130 - samples/sec: 40.18 - lr: 0.100000\n", + "2021-05-16 19:13:28,898 epoch 18 - iter 4/4 - loss 2.94846284 - samples/sec: 160.00 - lr: 0.100000\n", + "2021-05-16 19:13:28,898 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:28,898 EPOCH 18 done: loss 2.9485 - lr 0.1000000\n", + "2021-05-16 19:13:28,986 DEV : loss 3.8492608070373535 - score 0.48\n", + "2021-05-16 19:13:28,994 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:13:28,994 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:29,622 epoch 19 - iter 1/4 - loss 2.81688428 - samples/sec: 50.89 - lr: 0.100000\n", + "2021-05-16 19:13:30,354 epoch 19 - iter 2/4 - loss 2.99261010 - samples/sec: 44.72 - lr: 0.100000\n", + "2021-05-16 19:13:30,979 epoch 19 - iter 3/4 - loss 2.85697055 - samples/sec: 51.15 - lr: 0.100000\n", + "2021-05-16 19:13:31,139 epoch 19 - iter 4/4 - loss 2.25571273 - samples/sec: 200.02 - lr: 0.100000\n", + "2021-05-16 19:13:31,139 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:31,139 EPOCH 19 done: loss 2.2557 - lr 0.1000000\n", + "2021-05-16 19:13:31,235 DEV : loss 3.9649171829223633 - score 0.5185\n", + "Epoch 19: reducing learning rate of group 0 to 5.0000e-02.\n", + "2021-05-16 19:13:31,235 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:13:31,242 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:31,906 epoch 20 - iter 1/4 - loss 3.35270214 - samples/sec: 48.22 - lr: 0.050000\n", + "2021-05-16 19:13:32,555 epoch 20 - iter 2/4 - loss 2.56608105 - samples/sec: 49.28 - lr: 0.050000\n", + "2021-05-16 19:13:33,131 epoch 20 - iter 3/4 - loss 2.33327313 - samples/sec: 56.37 - lr: 0.050000\n", + "2021-05-16 19:13:33,332 epoch 20 - iter 4/4 - loss 2.89689222 - samples/sec: 165.52 - lr: 0.050000\n", + "2021-05-16 19:13:33,340 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:33,340 EPOCH 20 done: loss 2.8969 - lr 0.0500000\n", + "2021-05-16 19:13:33,421 DEV : loss 3.6375184059143066 - score 0.56\n", + "2021-05-16 19:13:33,421 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:13:33,421 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:34,102 epoch 21 - iter 1/4 - loss 2.03401089 - samples/sec: 47.65 - lr: 0.050000\n", + "2021-05-16 19:13:34,750 epoch 21 - iter 2/4 - loss 2.45254445 - samples/sec: 49.40 - lr: 0.050000\n", + "2021-05-16 19:13:35,405 epoch 21 - iter 3/4 - loss 2.02827569 - samples/sec: 48.84 - lr: 0.050000\n", + "2021-05-16 19:13:35,652 epoch 21 - iter 4/4 - loss 2.53652957 - samples/sec: 129.49 - lr: 0.050000\n", + "2021-05-16 19:13:35,652 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:35,652 EPOCH 21 done: loss 2.5365 - lr 0.0500000\n", + "2021-05-16 19:13:35,756 DEV : loss 3.636472463607788 - score 0.56\n", + "2021-05-16 19:13:35,756 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:13:35,763 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:36,461 epoch 22 - iter 1/4 - loss 2.35593867 - samples/sec: 45.85 - lr: 0.050000\n", + "2021-05-16 19:13:37,157 epoch 22 - iter 2/4 - loss 1.78290999 - samples/sec: 45.97 - lr: 0.050000\n", + "2021-05-16 19:13:37,821 epoch 22 - iter 3/4 - loss 2.12207437 - samples/sec: 48.21 - lr: 0.050000\n", + "2021-05-16 19:13:38,014 epoch 22 - iter 4/4 - loss 2.15731788 - samples/sec: 165.55 - lr: 0.050000\n", + "2021-05-16 19:13:38,014 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:38,021 EPOCH 22 done: loss 2.1573 - lr 0.0500000\n", + "2021-05-16 19:13:38,108 DEV : loss 3.7137885093688965 - score 0.6667\n", + "2021-05-16 19:13:38,116 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:13:38,116 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:38,822 epoch 23 - iter 1/4 - loss 1.83278751 - samples/sec: 45.53 - lr: 0.050000\n", + "2021-05-16 19:13:39,736 epoch 23 - iter 2/4 - loss 2.04161525 - samples/sec: 35.03 - lr: 0.050000\n", + "2021-05-16 19:13:40,684 epoch 23 - iter 3/4 - loss 2.19689337 - samples/sec: 33.76 - lr: 0.050000\n", + "2021-05-16 19:13:40,933 epoch 23 - iter 4/4 - loss 1.73538903 - samples/sec: 128.34 - lr: 0.050000\n", + "2021-05-16 19:13:40,934 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:40,934 EPOCH 23 done: loss 1.7354 - lr 0.0500000\n", + "2021-05-16 19:13:41,043 DEV : loss 3.495877265930176 - score 0.5833\n", + "Epoch 23: reducing learning rate of group 0 to 2.5000e-02.\n", + "2021-05-16 19:13:41,043 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:13:41,051 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:41,949 epoch 24 - iter 1/4 - loss 2.58249235 - samples/sec: 35.62 - lr: 0.025000\n", + "2021-05-16 19:13:42,545 epoch 24 - iter 2/4 - loss 2.33847690 - samples/sec: 53.73 - lr: 0.025000\n", + "2021-05-16 19:13:43,209 epoch 24 - iter 3/4 - loss 2.05386758 - samples/sec: 48.20 - lr: 0.025000\n", + "2021-05-16 19:13:43,426 epoch 24 - iter 4/4 - loss 1.69814771 - samples/sec: 147.27 - lr: 0.025000\n", + "2021-05-16 19:13:43,426 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:43,426 EPOCH 24 done: loss 1.6981 - lr 0.0250000\n", + "2021-05-16 19:13:43,514 DEV : loss 3.547339677810669 - score 0.5833\n", + "2021-05-16 19:13:43,514 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:13:43,514 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:44,502 epoch 25 - iter 1/4 - loss 2.63612175 - samples/sec: 32.67 - lr: 0.025000\n", + "2021-05-16 19:13:45,551 epoch 25 - iter 2/4 - loss 2.28528547 - samples/sec: 30.49 - lr: 0.025000\n", + "2021-05-16 19:13:46,368 epoch 25 - iter 3/4 - loss 2.18019919 - samples/sec: 39.20 - lr: 0.025000\n", + "2021-05-16 19:13:46,585 epoch 25 - iter 4/4 - loss 1.82882562 - samples/sec: 147.22 - lr: 0.025000\n", + "2021-05-16 19:13:46,585 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:46,585 EPOCH 25 done: loss 1.8288 - lr 0.0250000\n", + "2021-05-16 19:13:46,681 DEV : loss 3.695451259613037 - score 0.6667\n", + "2021-05-16 19:13:46,681 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:13:46,681 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:47,435 epoch 26 - iter 1/4 - loss 2.46649575 - samples/sec: 42.90 - lr: 0.025000\n", + "2021-05-16 19:13:48,195 epoch 26 - iter 2/4 - loss 1.86319947 - samples/sec: 42.09 - lr: 0.025000\n", + "2021-05-16 19:13:49,101 epoch 26 - iter 3/4 - loss 1.99375129 - samples/sec: 35.34 - lr: 0.025000\n", + "2021-05-16 19:13:49,350 epoch 26 - iter 4/4 - loss 2.51209539 - samples/sec: 132.64 - lr: 0.025000\n", + "2021-05-16 19:13:49,350 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:49,350 EPOCH 26 done: loss 2.5121 - lr 0.0250000\n", + "2021-05-16 19:13:49,454 DEV : loss 3.5949974060058594 - score 0.6667\n", + "2021-05-16 19:13:49,457 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:13:49,457 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:50,194 epoch 27 - iter 1/4 - loss 1.67152703 - samples/sec: 43.40 - lr: 0.025000\n", + "2021-05-16 19:13:50,906 epoch 27 - iter 2/4 - loss 1.81827271 - samples/sec: 44.95 - lr: 0.025000\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2021-05-16 19:13:51,642 epoch 27 - iter 3/4 - loss 1.91284267 - samples/sec: 43.46 - lr: 0.025000\n", + "2021-05-16 19:13:51,834 epoch 27 - iter 4/4 - loss 2.51718122 - samples/sec: 166.65 - lr: 0.025000\n", + "2021-05-16 19:13:51,834 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:51,834 EPOCH 27 done: loss 2.5172 - lr 0.0250000\n", + "2021-05-16 19:13:51,930 DEV : loss 3.624786376953125 - score 0.6667\n", + "Epoch 27: reducing learning rate of group 0 to 1.2500e-02.\n", + "2021-05-16 19:13:51,930 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:13:51,930 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:52,650 epoch 28 - iter 1/4 - loss 2.06657982 - samples/sec: 44.45 - lr: 0.012500\n", + "2021-05-16 19:13:53,405 epoch 28 - iter 2/4 - loss 2.16739893 - samples/sec: 42.42 - lr: 0.012500\n", + "2021-05-16 19:13:54,234 epoch 28 - iter 3/4 - loss 1.87206562 - samples/sec: 38.60 - lr: 0.012500\n", + "2021-05-16 19:13:54,402 epoch 28 - iter 4/4 - loss 1.53354126 - samples/sec: 190.48 - lr: 0.012500\n", + "2021-05-16 19:13:54,410 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:54,410 EPOCH 28 done: loss 1.5335 - lr 0.0125000\n", + "2021-05-16 19:13:54,498 DEV : loss 3.486685276031494 - score 0.6667\n", + "2021-05-16 19:13:54,498 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:13:54,498 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:55,514 epoch 29 - iter 1/4 - loss 1.94683826 - samples/sec: 31.74 - lr: 0.012500\n", + "2021-05-16 19:13:56,355 epoch 29 - iter 2/4 - loss 1.87296987 - samples/sec: 38.03 - lr: 0.012500\n", + "2021-05-16 19:13:57,018 epoch 29 - iter 3/4 - loss 1.93602276 - samples/sec: 48.88 - lr: 0.012500\n", + "2021-05-16 19:13:57,202 epoch 29 - iter 4/4 - loss 1.87588742 - samples/sec: 173.70 - lr: 0.012500\n", + "2021-05-16 19:13:57,202 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:57,202 EPOCH 29 done: loss 1.8759 - lr 0.0125000\n", + "2021-05-16 19:13:57,298 DEV : loss 3.5309135913848877 - score 0.6667\n", + "2021-05-16 19:13:57,298 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:13:57,298 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:58,250 epoch 30 - iter 1/4 - loss 2.16732407 - samples/sec: 33.90 - lr: 0.012500\n", + "2021-05-16 19:13:58,931 epoch 30 - iter 2/4 - loss 1.72622716 - samples/sec: 46.96 - lr: 0.012500\n", + "2021-05-16 19:13:59,781 epoch 30 - iter 3/4 - loss 1.93175316 - samples/sec: 37.65 - lr: 0.012500\n", + "2021-05-16 19:13:59,982 epoch 30 - iter 4/4 - loss 1.60670690 - samples/sec: 159.08 - lr: 0.012500\n", + "2021-05-16 19:13:59,990 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:13:59,990 EPOCH 30 done: loss 1.6067 - lr 0.0125000\n", + "2021-05-16 19:14:00,088 DEV : loss 3.4875831604003906 - score 0.6667\n", + "2021-05-16 19:14:00,096 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:14:00,096 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:01,011 epoch 31 - iter 1/4 - loss 2.39419317 - samples/sec: 34.99 - lr: 0.012500\n", + "2021-05-16 19:14:01,826 epoch 31 - iter 2/4 - loss 1.94124657 - samples/sec: 39.64 - lr: 0.012500\n", + "2021-05-16 19:14:02,676 epoch 31 - iter 3/4 - loss 1.81396655 - samples/sec: 37.62 - lr: 0.012500\n", + "2021-05-16 19:14:02,876 epoch 31 - iter 4/4 - loss 1.78971809 - samples/sec: 166.69 - lr: 0.012500\n", + "2021-05-16 19:14:02,884 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:02,884 EPOCH 31 done: loss 1.7897 - lr 0.0125000\n", + "2021-05-16 19:14:02,961 DEV : loss 3.4355287551879883 - score 0.5833\n", + "Epoch 31: reducing learning rate of group 0 to 6.2500e-03.\n", + "2021-05-16 19:14:02,961 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:14:02,976 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:03,838 epoch 32 - iter 1/4 - loss 1.18405724 - samples/sec: 37.13 - lr: 0.006250\n", + "2021-05-16 19:14:04,727 epoch 32 - iter 2/4 - loss 1.78029823 - samples/sec: 35.98 - lr: 0.006250\n", + "2021-05-16 19:14:05,416 epoch 32 - iter 3/4 - loss 1.71468850 - samples/sec: 46.96 - lr: 0.006250\n", + "2021-05-16 19:14:05,673 epoch 32 - iter 4/4 - loss 1.98795196 - samples/sec: 124.99 - lr: 0.006250\n", + "2021-05-16 19:14:05,673 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:05,673 EPOCH 32 done: loss 1.9880 - lr 0.0062500\n", + "2021-05-16 19:14:05,768 DEV : loss 3.4302756786346436 - score 0.5833\n", + "2021-05-16 19:14:05,776 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:14:05,776 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:06,493 epoch 33 - iter 1/4 - loss 1.43548059 - samples/sec: 44.69 - lr: 0.006250\n", + "2021-05-16 19:14:07,307 epoch 33 - iter 2/4 - loss 1.70211828 - samples/sec: 39.28 - lr: 0.006250\n", + "2021-05-16 19:14:08,082 epoch 33 - iter 3/4 - loss 1.72906860 - samples/sec: 41.30 - lr: 0.006250\n", + "2021-05-16 19:14:08,343 epoch 33 - iter 4/4 - loss 2.12577587 - samples/sec: 122.39 - lr: 0.006250\n", + "2021-05-16 19:14:08,343 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:08,343 EPOCH 33 done: loss 2.1258 - lr 0.0062500\n", + "2021-05-16 19:14:08,431 DEV : loss 3.4519147872924805 - score 0.6667\n", + "2021-05-16 19:14:08,439 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:14:08,439 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:09,154 epoch 34 - iter 1/4 - loss 1.07441115 - samples/sec: 44.79 - lr: 0.006250\n", + "2021-05-16 19:14:09,975 epoch 34 - iter 2/4 - loss 1.89638603 - samples/sec: 38.96 - lr: 0.006250\n", + "2021-05-16 19:14:10,993 epoch 34 - iter 3/4 - loss 1.81038960 - samples/sec: 31.45 - lr: 0.006250\n", + "2021-05-16 19:14:11,289 epoch 34 - iter 4/4 - loss 1.82815674 - samples/sec: 108.11 - lr: 0.006250\n", + "2021-05-16 19:14:11,289 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:11,289 EPOCH 34 done: loss 1.8282 - lr 0.0062500\n", + "2021-05-16 19:14:11,393 DEV : loss 3.4468681812286377 - score 0.6667\n", + "2021-05-16 19:14:11,393 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:14:11,393 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:12,314 epoch 35 - iter 1/4 - loss 1.71202326 - samples/sec: 34.74 - lr: 0.006250\n", + "2021-05-16 19:14:13,347 epoch 35 - iter 2/4 - loss 2.02234995 - samples/sec: 30.99 - lr: 0.006250\n", + "2021-05-16 19:14:13,977 epoch 35 - iter 3/4 - loss 1.83293974 - samples/sec: 51.40 - lr: 0.006250\n", + "2021-05-16 19:14:14,155 epoch 35 - iter 4/4 - loss 1.40346918 - samples/sec: 188.15 - lr: 0.006250\n", + "2021-05-16 19:14:14,155 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:14,155 EPOCH 35 done: loss 1.4035 - lr 0.0062500\n", + "2021-05-16 19:14:14,251 DEV : loss 3.4555253982543945 - score 0.6667\n", + "Epoch 35: reducing learning rate of group 0 to 3.1250e-03.\n", + "2021-05-16 19:14:14,251 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:14:14,251 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:15,020 epoch 36 - iter 1/4 - loss 1.60199451 - samples/sec: 41.61 - lr: 0.003125\n", + "2021-05-16 19:14:15,758 epoch 36 - iter 2/4 - loss 1.76909965 - samples/sec: 43.41 - lr: 0.003125\n", + "2021-05-16 19:14:16,694 epoch 36 - iter 3/4 - loss 1.96563844 - samples/sec: 34.46 - lr: 0.003125\n", + "2021-05-16 19:14:16,926 epoch 36 - iter 4/4 - loss 2.04810312 - samples/sec: 137.94 - lr: 0.003125\n", + "2021-05-16 19:14:16,926 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:16,926 EPOCH 36 done: loss 2.0481 - lr 0.0031250\n", + "2021-05-16 19:14:17,022 DEV : loss 3.467947483062744 - score 0.6667\n", + "2021-05-16 19:14:17,022 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:14:17,022 ----------------------------------------------------------------------------------------------------\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2021-05-16 19:14:17,771 epoch 37 - iter 1/4 - loss 1.59361398 - samples/sec: 42.71 - lr: 0.003125\n", + "2021-05-16 19:14:18,573 epoch 37 - iter 2/4 - loss 1.86242718 - samples/sec: 39.93 - lr: 0.003125\n", + "2021-05-16 19:14:19,367 epoch 37 - iter 3/4 - loss 1.84938045 - samples/sec: 40.27 - lr: 0.003125\n", + "2021-05-16 19:14:19,575 epoch 37 - iter 4/4 - loss 1.94639012 - samples/sec: 159.98 - lr: 0.003125\n", + "2021-05-16 19:14:19,575 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:19,575 EPOCH 37 done: loss 1.9464 - lr 0.0031250\n", + "2021-05-16 19:14:19,663 DEV : loss 3.4721953868865967 - score 0.6667\n", + "2021-05-16 19:14:19,663 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:14:19,663 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:20,420 epoch 38 - iter 1/4 - loss 1.87127459 - samples/sec: 42.26 - lr: 0.003125\n", + "2021-05-16 19:14:21,214 epoch 38 - iter 2/4 - loss 1.65014571 - samples/sec: 40.34 - lr: 0.003125\n", + "2021-05-16 19:14:22,201 epoch 38 - iter 3/4 - loss 1.78922117 - samples/sec: 32.41 - lr: 0.003125\n", + "2021-05-16 19:14:22,409 epoch 38 - iter 4/4 - loss 1.57039295 - samples/sec: 153.84 - lr: 0.003125\n", + "2021-05-16 19:14:22,417 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:22,417 EPOCH 38 done: loss 1.5704 - lr 0.0031250\n", + "2021-05-16 19:14:22,522 DEV : loss 3.4747495651245117 - score 0.6667\n", + "2021-05-16 19:14:22,522 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:14:22,522 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:23,532 epoch 39 - iter 1/4 - loss 1.71339095 - samples/sec: 31.94 - lr: 0.003125\n", + "2021-05-16 19:14:24,351 epoch 39 - iter 2/4 - loss 1.87997061 - samples/sec: 39.07 - lr: 0.003125\n", + "2021-05-16 19:14:25,353 epoch 39 - iter 3/4 - loss 1.93014069 - samples/sec: 31.93 - lr: 0.003125\n", + "2021-05-16 19:14:25,553 epoch 39 - iter 4/4 - loss 1.66254094 - samples/sec: 166.68 - lr: 0.003125\n", + "2021-05-16 19:14:25,561 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:25,561 EPOCH 39 done: loss 1.6625 - lr 0.0031250\n", + "2021-05-16 19:14:25,650 DEV : loss 3.4640121459960938 - score 0.6667\n", + "Epoch 39: reducing learning rate of group 0 to 1.5625e-03.\n", + "2021-05-16 19:14:25,650 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:14:25,650 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:26,482 epoch 40 - iter 1/4 - loss 1.51390183 - samples/sec: 38.46 - lr: 0.001563\n", + "2021-05-16 19:14:27,268 epoch 40 - iter 2/4 - loss 1.62989253 - samples/sec: 40.73 - lr: 0.001563\n", + "2021-05-16 19:14:28,116 epoch 40 - iter 3/4 - loss 1.59191600 - samples/sec: 37.73 - lr: 0.001563\n", + "2021-05-16 19:14:28,389 epoch 40 - iter 4/4 - loss 1.58031228 - samples/sec: 116.91 - lr: 0.001563\n", + "2021-05-16 19:14:28,389 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:28,389 EPOCH 40 done: loss 1.5803 - lr 0.0015625\n", + "2021-05-16 19:14:28,493 DEV : loss 3.464979648590088 - score 0.6667\n", + "2021-05-16 19:14:28,493 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:14:28,493 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:29,395 epoch 41 - iter 1/4 - loss 2.09950924 - samples/sec: 35.51 - lr: 0.001563\n", + "2021-05-16 19:14:30,198 epoch 41 - iter 2/4 - loss 2.02299452 - samples/sec: 39.85 - lr: 0.001563\n", + "2021-05-16 19:14:30,959 epoch 41 - iter 3/4 - loss 1.83912905 - samples/sec: 42.02 - lr: 0.001563\n", + "2021-05-16 19:14:31,168 epoch 41 - iter 4/4 - loss 2.28552222 - samples/sec: 152.95 - lr: 0.001563\n", + "2021-05-16 19:14:31,176 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:31,176 EPOCH 41 done: loss 2.2855 - lr 0.0015625\n", + "2021-05-16 19:14:31,256 DEV : loss 3.46785044670105 - score 0.6667\n", + "2021-05-16 19:14:31,256 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:14:31,264 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:31,960 epoch 42 - iter 1/4 - loss 2.07870221 - samples/sec: 45.98 - lr: 0.001563\n", + "2021-05-16 19:14:32,809 epoch 42 - iter 2/4 - loss 1.80660170 - samples/sec: 38.05 - lr: 0.001563\n", + "2021-05-16 19:14:33,486 epoch 42 - iter 3/4 - loss 1.86924104 - samples/sec: 47.31 - lr: 0.001563\n", + "2021-05-16 19:14:33,738 epoch 42 - iter 4/4 - loss 2.06889942 - samples/sec: 126.97 - lr: 0.001563\n", + "2021-05-16 19:14:33,738 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:33,738 EPOCH 42 done: loss 2.0689 - lr 0.0015625\n", + "2021-05-16 19:14:33,827 DEV : loss 3.464182138442993 - score 0.6667\n", + "2021-05-16 19:14:33,835 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:14:33,835 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:34,689 epoch 43 - iter 1/4 - loss 2.16509676 - samples/sec: 37.68 - lr: 0.001563\n", + "2021-05-16 19:14:35,420 epoch 43 - iter 2/4 - loss 1.79616153 - samples/sec: 44.27 - lr: 0.001563\n", + "2021-05-16 19:14:36,298 epoch 43 - iter 3/4 - loss 1.79792849 - samples/sec: 36.44 - lr: 0.001563\n", + "2021-05-16 19:14:36,517 epoch 43 - iter 4/4 - loss 1.78867936 - samples/sec: 146.19 - lr: 0.001563\n", + "2021-05-16 19:14:36,517 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:36,517 EPOCH 43 done: loss 1.7887 - lr 0.0015625\n", + "2021-05-16 19:14:36,589 DEV : loss 3.464967966079712 - score 0.6667\n", + "Epoch 43: reducing learning rate of group 0 to 7.8125e-04.\n", + "2021-05-16 19:14:36,589 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:14:36,603 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:37,308 epoch 44 - iter 1/4 - loss 1.60833621 - samples/sec: 45.36 - lr: 0.000781\n", + "2021-05-16 19:14:38,140 epoch 44 - iter 2/4 - loss 1.45758373 - samples/sec: 38.48 - lr: 0.000781\n", + "2021-05-16 19:14:38,983 epoch 44 - iter 3/4 - loss 1.52034609 - samples/sec: 37.96 - lr: 0.000781\n", + "2021-05-16 19:14:39,226 epoch 44 - iter 4/4 - loss 2.32687372 - samples/sec: 131.50 - lr: 0.000781\n", + "2021-05-16 19:14:39,235 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:39,236 EPOCH 44 done: loss 2.3269 - lr 0.0007813\n", + "2021-05-16 19:14:39,343 DEV : loss 3.467527151107788 - score 0.6667\n", + "2021-05-16 19:14:39,343 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:14:39,343 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:40,254 epoch 45 - iter 1/4 - loss 2.09789848 - samples/sec: 35.42 - lr: 0.000781\n", + "2021-05-16 19:14:41,142 epoch 45 - iter 2/4 - loss 1.90345168 - samples/sec: 36.05 - lr: 0.000781\n", + "2021-05-16 19:14:41,828 epoch 45 - iter 3/4 - loss 1.76009802 - samples/sec: 46.62 - lr: 0.000781\n", + "2021-05-16 19:14:42,079 epoch 45 - iter 4/4 - loss 1.94041607 - samples/sec: 127.70 - lr: 0.000781\n", + "2021-05-16 19:14:42,079 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:42,079 EPOCH 45 done: loss 1.9404 - lr 0.0007813\n", + "2021-05-16 19:14:42,174 DEV : loss 3.4680516719818115 - score 0.6667\n", + "2021-05-16 19:14:42,174 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:14:42,174 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:42,949 epoch 46 - iter 1/4 - loss 2.13200164 - samples/sec: 41.69 - lr: 0.000781\n", + "2021-05-16 19:14:43,628 epoch 46 - iter 2/4 - loss 1.92884541 - samples/sec: 47.13 - lr: 0.000781\n", + "2021-05-16 19:14:44,188 epoch 46 - iter 3/4 - loss 1.86859485 - samples/sec: 57.14 - lr: 0.000781\n", + "2021-05-16 19:14:44,420 epoch 46 - iter 4/4 - loss 2.23936662 - samples/sec: 137.82 - lr: 0.000781\n", + "2021-05-16 19:14:44,420 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:44,420 EPOCH 46 done: loss 2.2394 - lr 0.0007813\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2021-05-16 19:14:44,516 DEV : loss 3.467272996902466 - score 0.6667\n", + "2021-05-16 19:14:44,516 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:14:44,516 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:45,083 epoch 47 - iter 1/4 - loss 1.17524457 - samples/sec: 57.22 - lr: 0.000781\n", + "2021-05-16 19:14:45,804 epoch 47 - iter 2/4 - loss 1.69363821 - samples/sec: 44.40 - lr: 0.000781\n", + "2021-05-16 19:14:46,515 epoch 47 - iter 3/4 - loss 1.80291025 - samples/sec: 45.00 - lr: 0.000781\n", + "2021-05-16 19:14:46,744 epoch 47 - iter 4/4 - loss 1.68751404 - samples/sec: 139.56 - lr: 0.000781\n", + "2021-05-16 19:14:46,744 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:46,744 EPOCH 47 done: loss 1.6875 - lr 0.0007813\n", + "2021-05-16 19:14:46,841 DEV : loss 3.4656827449798584 - score 0.6667\n", + "Epoch 47: reducing learning rate of group 0 to 3.9063e-04.\n", + "2021-05-16 19:14:46,841 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:14:46,845 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:47,512 epoch 48 - iter 1/4 - loss 1.40106690 - samples/sec: 47.97 - lr: 0.000391\n", + "2021-05-16 19:14:48,126 epoch 48 - iter 2/4 - loss 1.41452271 - samples/sec: 52.10 - lr: 0.000391\n", + "2021-05-16 19:14:48,882 epoch 48 - iter 3/4 - loss 1.74593834 - samples/sec: 42.34 - lr: 0.000391\n", + "2021-05-16 19:14:49,064 epoch 48 - iter 4/4 - loss 1.58755332 - samples/sec: 176.07 - lr: 0.000391\n", + "2021-05-16 19:14:49,064 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:49,064 EPOCH 48 done: loss 1.5876 - lr 0.0003906\n", + "2021-05-16 19:14:49,149 DEV : loss 3.467986822128296 - score 0.6667\n", + "2021-05-16 19:14:49,149 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:14:49,149 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:49,930 epoch 49 - iter 1/4 - loss 1.38971734 - samples/sec: 40.97 - lr: 0.000391\n", + "2021-05-16 19:14:50,510 epoch 49 - iter 2/4 - loss 1.67799520 - samples/sec: 55.24 - lr: 0.000391\n", + "2021-05-16 19:14:51,137 epoch 49 - iter 3/4 - loss 1.69751259 - samples/sec: 51.05 - lr: 0.000391\n", + "2021-05-16 19:14:51,356 epoch 49 - iter 4/4 - loss 1.83348897 - samples/sec: 145.87 - lr: 0.000391\n", + "2021-05-16 19:14:51,356 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:51,356 EPOCH 49 done: loss 1.8335 - lr 0.0003906\n", + "2021-05-16 19:14:51,446 DEV : loss 3.4678850173950195 - score 0.6667\n", + "2021-05-16 19:14:51,446 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:14:51,462 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:52,179 epoch 50 - iter 1/4 - loss 1.13970292 - samples/sec: 44.71 - lr: 0.000391\n", + "2021-05-16 19:14:52,916 epoch 50 - iter 2/4 - loss 1.94286901 - samples/sec: 43.40 - lr: 0.000391\n", + "2021-05-16 19:14:53,640 epoch 50 - iter 3/4 - loss 1.91910776 - samples/sec: 44.19 - lr: 0.000391\n", + "2021-05-16 19:14:53,807 epoch 50 - iter 4/4 - loss 1.56437027 - samples/sec: 191.98 - lr: 0.000391\n", + "2021-05-16 19:14:53,807 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:53,807 EPOCH 50 done: loss 1.5644 - lr 0.0003906\n", + "2021-05-16 19:14:53,886 DEV : loss 3.4673101902008057 - score 0.6667\n", + "2021-05-16 19:14:53,886 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:14:53,898 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:54,525 epoch 51 - iter 1/4 - loss 1.64230800 - samples/sec: 50.99 - lr: 0.000391\n", + "2021-05-16 19:14:55,323 epoch 51 - iter 2/4 - loss 1.66435432 - samples/sec: 40.11 - lr: 0.000391\n", + "2021-05-16 19:14:56,158 epoch 51 - iter 3/4 - loss 1.76997383 - samples/sec: 38.33 - lr: 0.000391\n", + "2021-05-16 19:14:56,348 epoch 51 - iter 4/4 - loss 1.45529963 - samples/sec: 168.77 - lr: 0.000391\n", + "2021-05-16 19:14:56,348 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:56,348 EPOCH 51 done: loss 1.4553 - lr 0.0003906\n", + "2021-05-16 19:14:56,451 DEV : loss 3.46675705909729 - score 0.6667\n", + "Epoch 51: reducing learning rate of group 0 to 1.9531e-04.\n", + "2021-05-16 19:14:56,451 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:14:56,451 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:57,134 epoch 52 - iter 1/4 - loss 1.39893460 - samples/sec: 47.38 - lr: 0.000195\n", + "2021-05-16 19:14:57,904 epoch 52 - iter 2/4 - loss 1.95114291 - samples/sec: 41.57 - lr: 0.000195\n", + "2021-05-16 19:14:58,589 epoch 52 - iter 3/4 - loss 1.87273510 - samples/sec: 46.70 - lr: 0.000195\n", + "2021-05-16 19:14:58,814 epoch 52 - iter 4/4 - loss 1.66518828 - samples/sec: 142.21 - lr: 0.000195\n", + "2021-05-16 19:14:58,814 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:58,814 EPOCH 52 done: loss 1.6652 - lr 0.0001953\n", + "2021-05-16 19:14:58,898 DEV : loss 3.4661099910736084 - score 0.6667\n", + "2021-05-16 19:14:58,898 BAD EPOCHS (no improvement): 1\n", + "2021-05-16 19:14:58,898 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:14:59,621 epoch 53 - iter 1/4 - loss 1.52661002 - samples/sec: 44.90 - lr: 0.000195\n", + "2021-05-16 19:15:00,323 epoch 53 - iter 2/4 - loss 1.72744888 - samples/sec: 45.60 - lr: 0.000195\n", + "2021-05-16 19:15:01,033 epoch 53 - iter 3/4 - loss 1.67759216 - samples/sec: 45.09 - lr: 0.000195\n", + "2021-05-16 19:15:01,186 epoch 53 - iter 4/4 - loss 1.46851297 - samples/sec: 208.70 - lr: 0.000195\n", + "2021-05-16 19:15:01,186 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:01,186 EPOCH 53 done: loss 1.4685 - lr 0.0001953\n", + "2021-05-16 19:15:01,282 DEV : loss 3.466641426086426 - score 0.6667\n", + "2021-05-16 19:15:01,282 BAD EPOCHS (no improvement): 2\n", + "2021-05-16 19:15:01,282 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:01,903 epoch 54 - iter 1/4 - loss 1.67276871 - samples/sec: 51.56 - lr: 0.000195\n", + "2021-05-16 19:15:02,720 epoch 54 - iter 2/4 - loss 1.84151357 - samples/sec: 39.15 - lr: 0.000195\n", + "2021-05-16 19:15:03,497 epoch 54 - iter 3/4 - loss 1.79460196 - samples/sec: 41.16 - lr: 0.000195\n", + "2021-05-16 19:15:03,697 epoch 54 - iter 4/4 - loss 1.73617950 - samples/sec: 160.20 - lr: 0.000195\n", + "2021-05-16 19:15:03,697 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:03,697 EPOCH 54 done: loss 1.7362 - lr 0.0001953\n", + "2021-05-16 19:15:03,791 DEV : loss 3.4663610458374023 - score 0.6667\n", + "2021-05-16 19:15:03,807 BAD EPOCHS (no improvement): 3\n", + "2021-05-16 19:15:03,809 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:04,563 epoch 55 - iter 1/4 - loss 2.19241428 - samples/sec: 42.46 - lr: 0.000195\n", + "2021-05-16 19:15:05,206 epoch 55 - iter 2/4 - loss 1.68816346 - samples/sec: 49.73 - lr: 0.000195\n", + "2021-05-16 19:15:05,899 epoch 55 - iter 3/4 - loss 1.67743218 - samples/sec: 46.20 - lr: 0.000195\n", + "2021-05-16 19:15:06,147 epoch 55 - iter 4/4 - loss 1.62165421 - samples/sec: 129.04 - lr: 0.000195\n", + "2021-05-16 19:15:06,147 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:06,147 EPOCH 55 done: loss 1.6217 - lr 0.0001953\n", + "2021-05-16 19:15:06,243 DEV : loss 3.4659790992736816 - score 0.6667\n", + "Epoch 55: reducing learning rate of group 0 to 9.7656e-05.\n", + "2021-05-16 19:15:06,243 BAD EPOCHS (no improvement): 4\n", + "2021-05-16 19:15:06,243 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:06,243 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:06,243 learning rate too small - quitting training!\n", + "2021-05-16 19:15:06,243 ----------------------------------------------------------------------------------------------------\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2021-05-16 19:15:14,421 ----------------------------------------------------------------------------------------------------\n", + "2021-05-16 19:15:14,421 Testing using best model ...\n", + "2021-05-16 19:15:14,426 loading file slot-model\\best-model.pt\n", + "2021-05-16 19:15:34,103 0.6759\t0.6901\t0.6829\n", + "2021-05-16 19:15:34,103 \n", "Results:\n", - "- F1-score (micro) 0.1714\n", - "- F1-score (macro) 0.1161\n", + "- F1-score (micro) 0.6829\n", + "- F1-score (macro) 0.3185\n", "\n", "By class:\n", - "appoinment/doctor tp: 1 - fp: 9 - fn: 5 - precision: 0.1000 - recall: 0.1667 - f1-score: 0.1250\n", - "appointment/type tp: 0 - fp: 0 - fn: 2 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", - "datetime tp: 0 - fp: 1 - fn: 3 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", - "login/id tp: 2 - fp: 2 - fn: 1 - precision: 0.5000 - recall: 0.6667 - f1-score: 0.5714\n", - "login/password tp: 0 - fp: 0 - fn: 3 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", - "prescription/type tp: 0 - fp: 2 - fn: 1 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", - "2021-05-16 11:41:45,503 ----------------------------------------------------------------------------------------------------\n" + "NoLabel I-end_conversation tp: 0 - fp: 0 - fn: 2 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "affirm tp: 11 - fp: 6 - fn: 2 - precision: 0.6471 - recall: 0.8462 - f1-score: 0.7333\n", + "appoinment tp: 0 - fp: 0 - fn: 2 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "appoinment/doctor tp: 0 - fp: 0 - fn: 2 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "appointment tp: 19 - fp: 4 - fn: 1 - precision: 0.8261 - recall: 0.9500 - f1-score: 0.8837\n", + "appointment/doctor tp: 16 - fp: 13 - fn: 5 - precision: 0.5517 - recall: 0.7619 - f1-score: 0.6400\n", + "appointment/office tp: 0 - fp: 0 - fn: 1 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "appointment/type tp: 4 - fp: 2 - fn: 2 - precision: 0.6667 - recall: 0.6667 - f1-score: 0.6667\n", + "datetime tp: 12 - fp: 7 - fn: 6 - precision: 0.6316 - recall: 0.6667 - f1-score: 0.6486\n", + "deny tp: 0 - fp: 0 - fn: 4 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "doctor tp: 0 - fp: 0 - fn: 1 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "end_conversation tp: 14 - fp: 8 - fn: 6 - precision: 0.6364 - recall: 0.7000 - f1-score: 0.6667\n", + "greeting tp: 18 - fp: 3 - fn: 2 - precision: 0.8571 - recall: 0.9000 - f1-score: 0.8780\n", + "prescription tp: 4 - fp: 3 - fn: 2 - precision: 0.5714 - recall: 0.6667 - f1-score: 0.6154\n", + "prescription/type tp: 0 - fp: 0 - fn: 1 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "register/email tp: 0 - fp: 0 - fn: 1 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "register/name tp: 0 - fp: 0 - fn: 1 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "results tp: 0 - fp: 1 - fn: 3 - precision: 0.0000 - recall: 0.0000 - f1-score: 0.0000\n", + "2021-05-16 19:15:34,103 ----------------------------------------------------------------------------------------------------\n" ] }, { "data": { "text/plain": [ - "{'test_score': 0.17142857142857143,\n", - " 'dev_score_history': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],\n", - " 'train_loss_history': [11.51309585571289,\n", - " 5.878437042236328,\n", - " 7.245883822441101,\n", - " 3.1684603691101074,\n", - " 3.1224594116210938,\n", - " 4.798194766044617,\n", - " 1.9025391936302185,\n", - " 3.3012349605560303,\n", - " 2.347049653530121,\n", - " 2.182261645793915],\n", - " 'dev_loss_history': [5.320306777954102,\n", - " 2.201185703277588,\n", - " 2.3815672397613525,\n", - " 1.7660648822784424,\n", - " 1.8835055828094482,\n", - " 1.9106686115264893,\n", - 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" max_epochs=10,\n", + " max_epochs=100,\n", " train_with_dev=False)" ] }, @@ -703,7 +1327,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "2021-05-16 11:41:45,529 loading file slot-model/final-model.pt\n" + "2021-05-16 19:15:34,133 loading file slot-model/final-model.pt\n" ] } ], @@ -742,7 +1366,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -750,31 +1374,46 @@ "text/html": [ "\n", "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", "\n", "
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