['/home/yogeshchandrasekharuni/Developer/food-ordering/PURE/run_relation.py', '--task=food', '--do_train', '--train_file=./custom_data/train.json', '--do_eval', '--model=bert-base-uncased', '--do_lower_case', '--train_batch_size=32', '--eval_batch_size=32', '--learning_rate=2e-5', '--num_train_epochs=10', '--context_window=0', '--max_seq_length=128', '--entity_output_dir=./custom_data_out/', '--output_dir=./relation_model_stuff/output_dir']
Namespace(add_new_tokens=False, bertadam=False, context_window=0, do_eval=True, do_lower_case=True, do_train=True, entity_output_dir='./custom_data_out/', entity_predictions_dev='ent_pred_dev.json', entity_predictions_test='ent_pred_test.json', eval_batch_size=32, eval_metric='f1', eval_per_epoch=10, eval_test=False, eval_with_gold=False, learning_rate=2e-05, max_seq_length=128, model='bert-base-uncased', negative_label='no_relation', no_cuda=False, num_train_epochs=10.0, output_dir='./relation_model_stuff/output_dir', prediction_file='predictions.json', seed=0, task='food', train_batch_size=32, train_file='./custom_data/train.json', train_mode='random_sorted', warmup_proportion=0.1)
device: cuda, n_gpu: 1
Writing example 0 of 50000
*** Example ***
guid: b29357e9-14f2-4bec-baf1-7a3550136b4a@0::(4,6)-(6,7)
tokens: [CLS] can i get a [unused7] lunch - [unused9] sized [unused8] size [unused10] ada ##na ke ##ba ##p with ranch sauce [SEP]
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label: sizeOf (id = 5)
sub_idx, obj_idx: 5, 8
*** Example ***
guid: b29357e9-14f2-4bec-baf1-7a3550136b4a@0::(4,6)-(9,10)
tokens: [CLS] can i get a [unused7] lunch - sized [unused8] size ada ##na [unused12] ke ##ba ##p with [unused13] ranch sauce [SEP]
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label: no_relation (id = 0)
sub_idx, obj_idx: 5, 13
*** Example ***
guid: b29357e9-14f2-4bec-baf1-7a3550136b4a@0::(6,7)-(4,6)
tokens: [CLS] can i get a [unused18] lunch - [unused16] sized [unused19] size [unused17] ada ##na ke ##ba ##p with ranch sauce [SEP]
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label: no_relation (id = 0)
sub_idx, obj_idx: 8, 5
*** Example ***
guid: b29357e9-14f2-4bec-baf1-7a3550136b4a@0::(6,7)-(9,10)
tokens: [CLS] can i get a lunch - [unused16] sized size [unused17] ada ##na [unused12] ke ##ba ##p with [unused13] ranch sauce [SEP]
input_ids: 101 2064 1045 2131 1037 6265 1011 17 7451 2946 18 15262 2532 13 17710 3676 2361 2007 14 8086 12901 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: no_relation (id = 0)
sub_idx, obj_idx: 7, 13
*** Example ***
guid: b29357e9-14f2-4bec-baf1-7a3550136b4a@0::(9,10)-(4,6)
tokens: [CLS] can i get a [unused18] lunch - sized [unused19] size ada ##na [unused21] ke ##ba ##p with [unused22] ranch sauce [SEP]
input_ids: 101 2064 1045 2131 1037 19 6265 1011 7451 20 2946 15262 2532 22 17710 3676 2361 2007 23 8086 12901 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: no_relation (id = 0)
sub_idx, obj_idx: 13, 5
*** Example ***
guid: b29357e9-14f2-4bec-baf1-7a3550136b4a@0::(9,10)-(6,7)
tokens: [CLS] can i get a lunch - [unused9] sized size [unused10] ada ##na [unused21] ke ##ba ##p with [unused22] ranch sauce [SEP]
input_ids: 101 2064 1045 2131 1037 6265 1011 10 7451 2946 11 15262 2532 22 17710 3676 2361 2007 23 8086 12901 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 13, 7
*** Example ***
guid: e03cd791-b6ba-4e7a-99ac-dd894444411d@0::(9,9)-(4,7)
tokens: [CLS] we will have the [unused9] simple cup ##ka ##kes with sugar [unused10] with [unused21] mushroom [unused22] [SEP]
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label: addTo (id = 1)
sub_idx, obj_idx: 14, 5
*** Example ***
guid: 2a4f40af-98c8-4085-979b-8e678cf0ccb6@0::(11,11)-(4,7)
tokens: [CLS] may i have a [unused9] iced cinnamon crunch la ##tte [unused10] with an extra [unused21] pep ##pper ##oni [unused22] [SEP]
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label: addTo (id = 1)
sub_idx, obj_idx: 15, 5
*** Example ***
guid: bfe362fe-c224-4333-aea7-0986a578b4d9@0::(4,4)-(5,5)
tokens: [CLS] i feel like having [unused30] 11 [unused31] [unused9] ja ##le ##bi [unused10] with grille ##d pork , red rice , potato chips with sour ##cre ##am and onions and buffalo mo ##zar ##ella with peas on top [SEP]
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label: quantityOf (id = 4)
sub_idx, obj_idx: 5, 8
*** Example ***
guid: bfe362fe-c224-4333-aea7-0986a578b4d9@0::(20,21)-(13,18)
tokens: [CLS] i feel like having 11 ja ##le ##bi with grille ##d pork , red rice , [unused9] potato chips with sour ##cre ##am and onions [unused10] and [unused21] buffalo mo ##zar ##ella [unused22] with peas on top [SEP]
input_ids: 101 1045 2514 2066 2383 2340 14855 2571 5638 2007 26192 2094 15960 1010 2417 5785 1010 10 14557 11772 2007 14768 16748 3286 1998 24444 11 1998 22 6901 9587 9057 8411 23 2007 26072 2006 2327 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 28, 17
*** Example ***
guid: bfe362fe-c224-4333-aea7-0986a578b4d9@0::(23,23)-(13,18)
tokens: [CLS] i feel like having 11 ja ##le ##bi with grille ##d pork , red rice , [unused9] potato chips with sour ##cre ##am and onions [unused10] and buffalo mo ##zar ##ella with [unused21] peas [unused22] on top [SEP]
input_ids: 101 1045 2514 2066 2383 2340 14855 2571 5638 2007 26192 2094 15960 1010 2417 5785 1010 10 14557 11772 2007 14768 16748 3286 1998 24444 11 1998 6901 9587 9057 8411 2007 22 26072 23 2006 2327 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 33, 17
*** Example ***
guid: 09d62df0-36c5-45c6-8f36-0cf7ecc2190a@0::(11,11)-(6,9)
tokens: [CLS] finally can i please get a [unused9] mold ##avian pie with cheese [unused10] with [unused21] tomatoes [unused22] syrup bal ##zam ##ic g ##laze mayo ##nna ##ise and grille ##d pine ##apple [SEP]
input_ids: 101 2633 2064 1045 3531 2131 1037 10 18282 21654 11345 2007 8808 11 2007 22 12851 23 23353 28352 20722 2594 1043 24472 14415 9516 5562 1998 26192 2094 7222 23804 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 15, 7
*** Example ***
guid: 09d62df0-36c5-45c6-8f36-0cf7ecc2190a@0::(12,12)-(6,9)
tokens: [CLS] finally can i please get a [unused9] mold ##avian pie with cheese [unused10] with tomatoes [unused21] syrup [unused22] bal ##zam ##ic g ##laze mayo ##nna ##ise and grille ##d pine ##apple [SEP]
input_ids: 101 2633 2064 1045 3531 2131 1037 10 18282 21654 11345 2007 8808 11 2007 12851 22 23353 23 28352 20722 2594 1043 24472 14415 9516 5562 1998 26192 2094 7222 23804 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 16, 7
*** Example ***
guid: 09d62df0-36c5-45c6-8f36-0cf7ecc2190a@0::(13,14)-(6,9)
tokens: [CLS] finally can i please get a [unused9] mold ##avian pie with cheese [unused10] with tomatoes syrup [unused21] bal ##zam ##ic g ##laze [unused22] mayo ##nna ##ise and grille ##d pine ##apple [SEP]
input_ids: 101 2633 2064 1045 3531 2131 1037 10 18282 21654 11345 2007 8808 11 2007 12851 23353 22 28352 20722 2594 1043 24472 23 14415 9516 5562 1998 26192 2094 7222 23804 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 17, 7
*** Example ***
guid: 09d62df0-36c5-45c6-8f36-0cf7ecc2190a@0::(15,15)-(6,9)
tokens: [CLS] finally can i please get a [unused9] mold ##avian pie with cheese [unused10] with tomatoes syrup bal ##zam ##ic g ##laze [unused21] mayo ##nna ##ise [unused22] and grille ##d pine ##apple [SEP]
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label: addTo (id = 1)
sub_idx, obj_idx: 22, 7
*** Example ***
guid: 09d62df0-36c5-45c6-8f36-0cf7ecc2190a@0::(17,18)-(6,9)
tokens: [CLS] finally can i please get a [unused9] mold ##avian pie with cheese [unused10] with tomatoes syrup bal ##zam ##ic g ##laze mayo ##nna ##ise and [unused21] grille ##d pine ##apple [unused22] [SEP]
input_ids: 101 2633 2064 1045 3531 2131 1037 10 18282 21654 11345 2007 8808 11 2007 12851 23353 28352 20722 2594 1043 24472 14415 9516 5562 1998 22 26192 2094 7222 23804 23 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 26, 7
*** Example ***
guid: 5fd3d320-776f-4b98-af6e-727b59c6037c@0::(3,3)-(5,6)
tokens: [CLS] i would prefer [unused30] twelve [unused31] party [unused9] size plum [unused10] pie , please [SEP]
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label: quantityOf (id = 4)
sub_idx, obj_idx: 4, 8
*** Example ***
guid: 5fd3d320-776f-4b98-af6e-727b59c6037c@0::(4,5)-(5,6)
tokens: [CLS] i would prefer twelve [unused7] party [unused9] size [unused8] plum [unused10] pie , please [SEP]
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label: sizeOf (id = 5)
sub_idx, obj_idx: 5, 7
*** Example ***
guid: 16ba0c27-ace4-48e9-91b0-dc6e576851a2@0::(6,6)-(8,10)
tokens: [CLS] i would like to order a [unused30] 5 [unused31] of [unused9] creamy tomato soup [unused10] with an extra foam [SEP]
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label: quantityOf (id = 4)
sub_idx, obj_idx: 7, 11
*** Example ***
guid: 16ba0c27-ace4-48e9-91b0-dc6e576851a2@0::(14,14)-(8,10)
tokens: [CLS] i would like to order a 5 of [unused9] creamy tomato soup [unused10] with an extra [unused21] foam [unused22] [SEP]
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label: addTo (id = 1)
sub_idx, obj_idx: 17, 9
Writing example 10000 of 50000
Writing example 20000 of 50000
Writing example 30000 of 50000
Writing example 40000 of 50000
Average #tokens: 38.25
Max #tokens: 76
50000 (100.00 %) examples can fit max_seq_length = 128
***** Dev *****
  Num examples = 174732
  Batch size = 32
Writing example 0 of 50000
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(3,4)-(14,15)
tokens: [CLS] i want a [unused16] mis ##i rot ##i [unused17] make it lunch - size for topping ##s i guess [unused12] i ' ll take [unused13] vega ##n pepper ##oni and extra mayo and hold the mustard sauce that ' s it [SEP]
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input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: no_relation (id = 0)
sub_idx, obj_idx: 4, 20
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(3,4)-(18,18)
tokens: [CLS] i want a [unused16] mis ##i rot ##i [unused17] make it lunch - size for topping ##s i guess i ' ll take vega ##n pepper ##oni [unused12] and [unused13] extra mayo and hold the mustard sauce that ' s it [SEP]
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input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: no_relation (id = 0)
sub_idx, obj_idx: 4, 28
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(3,4)-(22,23)
tokens: [CLS] i want a [unused16] mis ##i rot ##i [unused17] make it lunch - size for topping ##s i guess i ' ll take vega ##n pepper ##oni and extra mayo and [unused24] hold the [unused25] mustard sauce that ' s it [SEP]
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label: no_relation (id = 0)
sub_idx, obj_idx: 4, 32
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(3,4)-(7,9)
tokens: [CLS] i want a [unused16] mis ##i rot ##i [unused17] make it [unused18] lunch - size [unused19] for topping ##s i guess i ' ll take vega ##n pepper ##oni and extra mayo and hold the mustard sauce that ' s it [SEP]
input_ids: 101 1045 2215 1037 17 28616 2072 18672 2072 18 2191 2009 19 6265 1011 2946 20 2005 22286 2015 1045 3984 1045 1005 2222 2202 15942 2078 11565 10698 1998 4469 14415 1998 2907 1996 23187 12901 2008 1005 1055 2009 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: no_relation (id = 0)
sub_idx, obj_idx: 4, 12
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(14,15)-(3,4)
tokens: [CLS] i want a [unused9] mis ##i rot ##i [unused10] make it lunch - size for topping ##s i guess [unused21] i ' ll take [unused22] vega ##n pepper ##oni and extra mayo and hold the mustard sauce that ' s it [SEP]
input_ids: 101 1045 2215 1037 10 28616 2072 18672 2072 11 2191 2009 6265 1011 2946 2005 22286 2015 1045 3984 22 1045 1005 2222 2202 23 15942 2078 11565 10698 1998 4469 14415 1998 2907 1996 23187 12901 2008 1005 1055 2009 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 20, 4
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(18,18)-(3,4)
tokens: [CLS] i want a [unused9] mis ##i rot ##i [unused10] make it lunch - size for topping ##s i guess i ' ll take vega ##n pepper ##oni [unused21] and [unused22] extra mayo and hold the mustard sauce that ' s it [SEP]
input_ids: 101 1045 2215 1037 10 28616 2072 18672 2072 11 2191 2009 6265 1011 2946 2005 22286 2015 1045 3984 1045 1005 2222 2202 15942 2078 11565 10698 22 1998 23 4469 14415 1998 2907 1996 23187 12901 2008 1005 1055 2009 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 28, 4
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(22,23)-(3,4)
tokens: [CLS] i want a [unused9] mis ##i rot ##i [unused10] make it lunch - size for topping ##s i guess i ' ll take vega ##n pepper ##oni and extra mayo and [unused27] hold the [unused28] mustard sauce that ' s it [SEP]
input_ids: 101 1045 2215 1037 10 28616 2072 18672 2072 11 2191 2009 6265 1011 2946 2005 22286 2015 1045 3984 1045 1005 2222 2202 15942 2078 11565 10698 1998 4469 14415 1998 28 2907 1996 29 23187 12901 2008 1005 1055 2009 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: removeFrom (id = 2)
sub_idx, obj_idx: 32, 4
*** Example ***
guid: bf7926a3-b648-454c-bbe0-a4daae5a1a50@0::(7,9)-(3,4)
tokens: [CLS] i want a [unused9] mis ##i rot ##i [unused10] make it [unused7] lunch - size [unused8] for topping ##s i guess i ' ll take vega ##n pepper ##oni and extra mayo and hold the mustard sauce that ' s it [SEP]
input_ids: 101 1045 2215 1037 10 28616 2072 18672 2072 11 2191 2009 8 6265 1011 2946 9 2005 22286 2015 1045 3984 1045 1005 2222 2202 15942 2078 11565 10698 1998 4469 14415 1998 2907 1996 23187 12901 2008 1005 1055 2009 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: sizeOf (id = 5)
sub_idx, obj_idx: 12, 4
*** Example ***
guid: dc7ebb9a-e83e-4170-9173-bc7960128fb6@0::(6,6)-(7,7)
tokens: [CLS] can i put an order for [unused30] seven [unused31] [unused9] pay ##ok ##h [unused10] bowls with danish cookies with sugar roasted green pepper and cara ##mel ##ized onions with kala ##mata olive and a side of pep ##er ##ron ##ni [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 31 2698 32 10 3477 6559 2232 11 15220 2007 5695 16324 2007 5699 28115 2665 11565 1998 14418 10199 3550 24444 2007 26209 21022 9724 1998 1037 2217 1997 27233 2121 4948 3490 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: quantityOf (id = 4)
sub_idx, obj_idx: 7, 10
*** Example ***
guid: dc7ebb9a-e83e-4170-9173-bc7960128fb6@0::(14,16)-(10,13)
tokens: [CLS] can i put an order for seven pay ##ok ##h bowls with [unused9] danish cookies with sugar [unused10] [unused21] roasted green pepper [unused22] and cara ##mel ##ized onions with kala ##mata olive and a side of pep ##er ##ron ##ni [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 2698 3477 6559 2232 15220 2007 10 5695 16324 2007 5699 11 22 28115 2665 11565 23 1998 14418 10199 3550 24444 2007 26209 21022 9724 1998 1037 2217 1997 27233 2121 4948 3490 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 19, 13
*** Example ***
guid: dc7ebb9a-e83e-4170-9173-bc7960128fb6@0::(18,19)-(10,13)
tokens: [CLS] can i put an order for seven pay ##ok ##h bowls with [unused9] danish cookies with sugar [unused10] roasted green pepper and [unused21] cara ##mel ##ized onions [unused22] with kala ##mata olive and a side of pep ##er ##ron ##ni [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 2698 3477 6559 2232 15220 2007 10 5695 16324 2007 5699 11 28115 2665 11565 1998 22 14418 10199 3550 24444 23 2007 26209 21022 9724 1998 1037 2217 1997 27233 2121 4948 3490 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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label: addTo (id = 1)
sub_idx, obj_idx: 23, 13
*** Example ***
guid: dc7ebb9a-e83e-4170-9173-bc7960128fb6@0::(21,22)-(10,13)
tokens: [CLS] can i put an order for seven pay ##ok ##h bowls with [unused9] danish cookies with sugar [unused10] roasted green pepper and cara ##mel ##ized onions with [unused21] kala ##mata olive [unused22] and a side of pep ##er ##ron ##ni [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 2698 3477 6559 2232 15220 2007 10 5695 16324 2007 5699 11 28115 2665 11565 1998 14418 10199 3550 24444 2007 22 26209 21022 9724 23 1998 1037 2217 1997 27233 2121 4948 3490 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: addTo (id = 1)
sub_idx, obj_idx: 28, 13
*** Example ***
guid: dc7ebb9a-e83e-4170-9173-bc7960128fb6@0::(27,27)-(10,13)
tokens: [CLS] can i put an order for seven pay ##ok ##h bowls with [unused9] danish cookies with sugar [unused10] roasted green pepper and cara ##mel ##ized onions with kala ##mata olive and a side of [unused21] pep ##er ##ron ##ni [unused22] [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 2698 3477 6559 2232 15220 2007 10 5695 16324 2007 5699 11 28115 2665 11565 1998 14418 10199 3550 24444 2007 26209 21022 9724 1998 1037 2217 1997 22 27233 2121 4948 3490 23 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: addTo (id = 1)
sub_idx, obj_idx: 35, 13
*** Example ***
guid: e619dfb2-534c-4e41-a6f7-4958534c44b9@0::(6,6)-(7,12)
tokens: [CLS] i would like an order of [unused30] 4 [unused31] [unused9] french fries with dried vegetable powder [unused10] [SEP]
input_ids: 101 1045 2052 2066 2019 2344 1997 31 1018 32 10 2413 22201 2007 9550 15415 9898 11 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: quantityOf (id = 4)
sub_idx, obj_idx: 7, 10
*** Example ***
guid: b11acaf7-ca74-435c-8a3c-7862fcfe4d78@0::(7,8)-(5,5)
tokens: [CLS] could you bring us the [unused9] pan ##jee ##ri [unused10] with [unused21] bb ##q chicken [unused22] [SEP]
input_ids: 101 2071 2017 3288 2149 1996 10 6090 16963 3089 11 2007 22 22861 4160 7975 23 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: addTo (id = 1)
sub_idx, obj_idx: 12, 6
*** Example ***
guid: 6fe63cff-c136-4cb0-b180-76174896d518@0::(3,3)-(4,6)
tokens: [CLS] get me a [unused7] personal [unused8] [unused9] cocoa milk burger [unused10] and ras ##mal ##ai with cu ##cum ##bers [SEP]
input_ids: 101 2131 2033 1037 8 3167 9 10 22940 6501 15890 11 1998 20710 9067 4886 2007 12731 24894 17198 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: sizeOf (id = 5)
sub_idx, obj_idx: 4, 7
*** Example ***
guid: 6fe63cff-c136-4cb0-b180-76174896d518@0::(10,10)-(8,8)
tokens: [CLS] get me a personal cocoa milk burger and [unused9] ras ##mal ##ai [unused10] with [unused21] cu ##cum ##bers [unused22] [SEP]
input_ids: 101 2131 2033 1037 3167 22940 6501 15890 1998 10 20710 9067 4886 11 2007 22 12731 24894 17198 23 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: addTo (id = 1)
sub_idx, obj_idx: 15, 9
*** Example ***
guid: a5b9843a-8608-41d5-819d-ae9ff7249491@0::(6,6)-(7,7)
tokens: [CLS] can i put an order for [unused30] twelve [unused31] [unused9] sand ##esh [unused10] bowls with ban ##ate ##an sal ##ami cheese and beef with plain syrup and a side of hot peppers [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 31 4376 32 10 5472 9953 11 15220 2007 7221 3686 2319 16183 10631 8808 1998 12486 2007 5810 23353 1998 1037 2217 1997 2980 23582 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: quantityOf (id = 4)
sub_idx, obj_idx: 7, 10
*** Example ***
guid: a5b9843a-8608-41d5-819d-ae9ff7249491@0::(12,12)-(10,11)
tokens: [CLS] can i put an order for twelve sand ##esh bowls with [unused9] ban ##ate ##an sal ##ami [unused10] [unused21] cheese [unused22] and beef with plain syrup and a side of hot peppers [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 4376 5472 9953 15220 2007 10 7221 3686 2319 16183 10631 11 22 8808 23 1998 12486 2007 5810 23353 1998 1037 2217 1997 2980 23582 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: addTo (id = 1)
sub_idx, obj_idx: 19, 12
*** Example ***
guid: a5b9843a-8608-41d5-819d-ae9ff7249491@0::(14,14)-(10,11)
tokens: [CLS] can i put an order for twelve sand ##esh bowls with [unused9] ban ##ate ##an sal ##ami [unused10] cheese and [unused21] beef [unused22] with plain syrup and a side of hot peppers [SEP]
input_ids: 101 2064 1045 2404 2019 2344 2005 4376 5472 9953 15220 2007 10 7221 3686 2319 16183 10631 11 8808 1998 22 12486 23 2007 5810 23353 1998 1037 2217 1997 2980 23582 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
label: addTo (id = 1)
sub_idx, obj_idx: 21, 12
Writing example 10000 of 50000
Writing example 20000 of 50000
Writing example 30000 of 50000
Writing example 40000 of 50000
Average #tokens: 39.85
Max #tokens: 76
50000 (100.00 %) examples can fit max_seq_length = 128
***** Training *****
  Num examples = 751032
  Batch size = 32
  Num steps = 15630
Start epoch #0 (lr = 2e-05)...
Epoch: 0, Step: 156 / 1563, used_time = 62.03s, loss = 0.896986
***** Eval results *****
  accuracy = 0.85582
  eval_loss = 0.5648643986172426
  f1 = 6.989585517578807e-05
  n_correct = 1
  n_gold = 28590
  n_pred = 24
  precision = 0.041666666666666664
  recall = 3.497726477789437e-05
  task_f1 = 0.0002771618625277162
  task_ngold = 7192
  task_recall = 0.00013904338153503893
!!! Best dev f1 (lr=2e-05, epoch=0): 0.01
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 312 / 1563, used_time = 315.24s, loss = 0.704925
***** Eval results *****
  accuracy = 0.86832
  eval_loss = 0.41091112889497233
  f1 = 0.0591469957081545
  n_correct = 882
  n_gold = 28590
  n_pred = 1234
  precision = 0.7147487844408428
  recall = 0.030849947534102834
  task_f1 = 0.2093520056966532
  task_ngold = 7192
  task_recall = 0.12263626251390433
!!! Best dev f1 (lr=2e-05, epoch=0): 5.91
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 468 / 1563, used_time = 576.66s, loss = 0.595780
***** Eval results *****
  accuracy = 0.8921
  eval_loss = 0.323161855509227
  f1 = 0.19474752227744607
  n_correct = 3311
  n_gold = 28590
  n_pred = 5413
  precision = 0.611675595787918
  recall = 0.11580972367960825
  task_f1 = 0.5253470844902817
  task_ngold = 7192
  task_recall = 0.4603726362625139
!!! Best dev f1 (lr=2e-05, epoch=0): 19.47
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 624 / 1563, used_time = 843.35s, loss = 0.523883
***** Eval results *****
  accuracy = 0.9351
  eval_loss = 0.19846073595386282
  f1 = 0.26795888399412626
  n_correct = 4562
  n_gold = 28590
  n_pred = 5460
  precision = 0.8355311355311356
  recall = 0.15956628191675412
  task_f1 = 0.7211508061966488
  task_ngold = 7192
  task_recall = 0.6343159065628476
!!! Best dev f1 (lr=2e-05, epoch=0): 26.80
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 780 / 1563, used_time = 1112.38s, loss = 0.461763
***** Eval results *****
  accuracy = 0.9472
  eval_loss = 0.1504482383005886
  f1 = 0.30507505360972126
  n_correct = 5335
  n_gold = 28590
  n_pred = 6385
  precision = 0.8355520751761942
  recall = 0.18660370759006645
  task_f1 = 0.7858878986521323
  task_ngold = 7192
  task_recall = 0.7417964404894327
!!! Best dev f1 (lr=2e-05, epoch=0): 30.51
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 936 / 1563, used_time = 1379.87s, loss = 0.411694
***** Eval results *****
  accuracy = 0.96578
  eval_loss = 0.09778755579474611
  f1 = 0.3418779209743662
  n_correct = 6035
  n_gold = 28590
  n_pred = 6715
  precision = 0.8987341772151899
  recall = 0.2110877929345925
  task_f1 = 0.8679082476450709
  task_ngold = 7192
  task_recall = 0.83912680756396
!!! Best dev f1 (lr=2e-05, epoch=0): 34.19
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 1092 / 1563, used_time = 1645.46s, loss = 0.368526
***** Eval results *****
  accuracy = 0.97978
  eval_loss = 0.07032443524137352
  f1 = 0.37795841627958415
  n_correct = 6835
  n_gold = 28590
  n_pred = 7578
  precision = 0.901953021905516
  recall = 0.239069604756908
  task_f1 = 0.9255247122545701
  task_ngold = 7192
  task_recall = 0.9503615127919911
!!! Best dev f1 (lr=2e-05, epoch=0): 37.80
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 1248 / 1563, used_time = 1911.14s, loss = 0.334796
***** Eval results *****
  accuracy = 0.97648
  eval_loss = 0.07704464960369246
  f1 = 0.3727386064551877
  n_correct = 6727
  n_gold = 28590
  n_pred = 7505
  precision = 0.8963357761492339
  recall = 0.2352920601608954
  task_f1 = 0.9154249166496564
  task_ngold = 7192
  task_recall = 0.9353448275862069
Epoch: 0, Step: 1404 / 1563, used_time = 2178.59s, loss = 0.304812
***** Eval results *****
  accuracy = 0.97904
  eval_loss = 0.07993560546967922
  f1 = 0.3874451201221674
  n_correct = 7104
  n_gold = 28590
  n_pred = 8081
  precision = 0.8790991213958669
  recall = 0.2484784889821616
  task_f1 = 0.9302691023374583
  task_ngold = 7192
  task_recall = 0.9877641824249166
!!! Best dev f1 (lr=2e-05, epoch=0): 38.74
Saving model to ./relation_model_stuff/output_dir
Epoch: 0, Step: 1560 / 1563, used_time = 2444.11s, loss = 0.280629
***** Eval results *****
  accuracy = 0.98562
  eval_loss = 0.06063681081464457
  f1 = 0.39080523055746735
  n_correct = 7098
  n_gold = 28590
  n_pred = 7735
  precision = 0.9176470588235294
  recall = 0.24826862539349423
  task_f1 = 0.9510283379111677
  task_ngold = 7192
  task_recall = 0.9869299221357063
!!! Best dev f1 (lr=2e-05, epoch=0): 39.08
Saving model to ./relation_model_stuff/output_dir
Start epoch #1 (lr = 2e-05)...
Epoch: 1, Step: 156 / 1563, used_time = 2713.24s, loss = 0.258083
***** Eval results *****
  accuracy = 0.98416
  eval_loss = 0.0635332486597554
  f1 = 0.3899288089937055
  n_correct = 7093
  n_gold = 28590
  n_pred = 7791
  precision = 0.910409446797587
  recall = 0.24809373906960475
  task_f1 = 0.9468063805646398
  task_ngold = 7192
  task_recall = 0.9862347052280311
Epoch: 1, Step: 312 / 1563, used_time = 2980.46s, loss = 0.238736
***** Eval results *****
  accuracy = 0.98934
  eval_loss = 0.05576145187918014
  f1 = 0.39338458985563357
  n_correct = 7112
  n_gold = 28590
  n_pred = 7568
  precision = 0.9397463002114165
  recall = 0.24875830710038474
  task_f1 = 0.9636856368563685
  task_ngold = 7192
  task_recall = 0.9888765294771968
!!! Best dev f1 (lr=2e-05, epoch=1): 39.34
Saving model to ./relation_model_stuff/output_dir
Epoch: 1, Step: 468 / 1563, used_time = 3247.83s, loss = 0.223138
***** Eval results *****
  accuracy = 0.98276
  eval_loss = 0.07188565101998895
  f1 = 0.3898602356810085
  n_correct = 7113
  n_gold = 28590
  n_pred = 7900
  precision = 0.9003797468354431
  recall = 0.24879328436516265
  task_f1 = 0.942618605883912
  task_ngold = 7192
  task_recall = 0.9890155728587319
Epoch: 1, Step: 624 / 1563, used_time = 3516.30s, loss = 0.209376
***** Eval results *****
  accuracy = 0.98976
  eval_loss = 0.047998133040274456
  f1 = 0.39021539489063284
  n_correct = 7011
  n_gold = 28590
  n_pred = 7344
  precision = 0.9546568627450981
  recall = 0.24522560335781743
  task_f1 = 0.9646395156851953
  task_ngold = 7192
  task_recall = 0.9748331479421579
Epoch: 1, Step: 780 / 1563, used_time = 3782.61s, loss = 0.196693
***** Eval results *****
  accuracy = 0.98856
  eval_loss = 0.061109847675754246
  f1 = 0.39350867993265803
  n_correct = 7129
  n_gold = 28590
  n_pred = 7643
  precision = 0.9327489205809237
  recall = 0.24935292060160896
  task_f1 = 0.9611054937647456
  task_ngold = 7192
  task_recall = 0.9912402669632926
!!! Best dev f1 (lr=2e-05, epoch=1): 39.35
Saving model to ./relation_model_stuff/output_dir
Epoch: 1, Step: 936 / 1563, used_time = 4050.95s, loss = 0.186094
***** Eval results *****
  accuracy = 0.9918
  eval_loss = 0.04863314045465692
  f1 = 0.3947273484112668
  n_correct = 7112
  n_gold = 28590
  n_pred = 7445
  precision = 0.9552719946272666
  recall = 0.24875830710038474
  task_f1 = 0.9717838354854136
  task_ngold = 7192
  task_recall = 0.9888765294771968
!!! Best dev f1 (lr=2e-05, epoch=1): 39.47
Saving model to ./relation_model_stuff/output_dir
Epoch: 1, Step: 1092 / 1563, used_time = 4317.64s, loss = 0.176892
***** Eval results *****
  accuracy = 0.98784
  eval_loss = 0.07303302968109897
  f1 = 0.39337394228384004
  n_correct = 7136
  n_gold = 28590
  n_pred = 7691
  precision = 0.9278377324145105
  recall = 0.24959776145505422
  task_f1 = 0.9589464489686219
  task_ngold = 7192
  task_recall = 0.9922135706340378
Epoch: 1, Step: 1248 / 1563, used_time = 4581.43s, loss = 0.168221
***** Eval results *****
  accuracy = 0.99252
  eval_loss = 0.05078523849304111
  f1 = 0.3956031754843724
  n_correct = 7126
  n_gold = 28590
  n_pred = 7436
  precision = 0.9583109198493814
  recall = 0.24924798880727528
  task_f1 = 0.9742958709324583
  task_ngold = 7192
  task_recall = 0.9908231368186874
!!! Best dev f1 (lr=2e-05, epoch=1): 39.56
Saving model to ./relation_model_stuff/output_dir
Epoch: 1, Step: 1404 / 1563, used_time = 4846.98s, loss = 0.161102
***** Eval results *****
  accuracy = 0.99106
  eval_loss = 0.0564079134216213
  f1 = 0.3940427656210999
  n_correct = 7104
  n_gold = 28590
  n_pred = 7467
  precision = 0.9513860988348735
  recall = 0.2484784889821616
  task_f1 = 0.9692339177297224
  task_ngold = 7192
  task_recall = 0.9877641824249166
Epoch: 1, Step: 1560 / 1563, used_time = 5111.32s, loss = 0.154017
***** Eval results *****
  accuracy = 0.98914
  eval_loss = 0.06297700283904327
  f1 = 0.39396868354919773
  n_correct = 7133
  n_gold = 28590
  n_pred = 7621
  precision = 0.9359664086077942
  recall = 0.24949282966072053
  task_f1 = 0.9630729764396139
  task_ngold = 7192
  task_recall = 0.9917964404894327
Start epoch #2 (lr = 2e-05)...
Epoch: 2, Step: 156 / 1563, used_time = 5376.10s, loss = 0.147425
***** Eval results *****
  accuracy = 0.99116
  eval_loss = 0.053565176762699715
  f1 = 0.3931229863348517
  n_correct = 7077
  n_gold = 28590
  n_pred = 7414
  precision = 0.9545454545454546
  recall = 0.24753410283315844
  task_f1 = 0.9690538135013008
  task_ngold = 7192
  task_recall = 0.9840100111234705
Epoch: 2, Step: 312 / 1563, used_time = 5641.26s, loss = 0.140980
***** Eval results *****
  accuracy = 0.9916
  eval_loss = 0.057540530607658576
  f1 = 0.394774794763701
  n_correct = 7117
  n_gold = 28590
  n_pred = 7466
  precision = 0.9532547548888294
  recall = 0.24893319342427422
  task_f1 = 0.9710738163460227
  task_ngold = 7192
  task_recall = 0.9895717463848721
Epoch: 2, Step: 468 / 1563, used_time = 5906.57s, loss = 0.136119
***** Eval results *****
  accuracy = 0.99032
  eval_loss = 0.0551174545458525
  f1 = 0.39417513357880457
  n_correct = 7119
  n_gold = 28590
  n_pred = 7531
  precision = 0.9452927898021511
  recall = 0.24900314795383002
  task_f1 = 0.9670583440874823
  task_ngold = 7192
  task_recall = 0.9898498331479422
Epoch: 2, Step: 624 / 1563, used_time = 6169.67s, loss = 0.130950
***** Eval results *****
  accuracy = 0.99214
  eval_loss = 0.048078447049186505
  f1 = 0.3942409250097282
  n_correct = 7092
  n_gold = 28590
  n_pred = 7388
  precision = 0.9599350297780184
  recall = 0.24805876180482686
  task_f1 = 0.9728395061728394
  task_ngold = 7192
  task_recall = 0.9860956618464961
Epoch: 2, Step: 780 / 1563, used_time = 6432.31s, loss = 0.126720
***** Eval results *****
  accuracy = 0.9922
  eval_loss = 0.04979654191947149
  f1 = 0.39532689532689536
  n_correct = 7123
  n_gold = 28590
  n_pred = 7446
  precision = 0.95662100456621
  recall = 0.2491430570129416
  task_f1 = 0.973220385298538
  task_ngold = 7192
  task_recall = 0.9904060066740823
Epoch: 2, Step: 936 / 1563, used_time = 6695.13s, loss = 0.122293
***** Eval results *****
  accuracy = 0.99182
  eval_loss = 0.053397004566395144
  f1 = 0.3946484581008688
  n_correct = 7109
  n_gold = 28590
  n_pred = 7437
  precision = 0.9558961947021648
  recall = 0.24865337530605106
  task_f1 = 0.9719051199671884
  task_ngold = 7192
  task_recall = 0.9884593993325917
Epoch: 2, Step: 1092 / 1563, used_time = 6959.13s, loss = 0.118404
***** Eval results *****
  accuracy = 0.9925
  eval_loss = 0.05193930938693358
  f1 = 0.39567027477102407
  n_correct = 7128
  n_gold = 28590
  n_pred = 7440
  precision = 0.9580645161290322
  recall = 0.24931794333683105
  task_f1 = 0.9743028977583379
  task_ngold = 7192
  task_recall = 0.9911012235817576
!!! Best dev f1 (lr=2e-05, epoch=2): 39.57
Saving model to ./relation_model_stuff/output_dir
Epoch: 2, Step: 1248 / 1563, used_time = 7225.22s, loss = 0.114695
***** Eval results *****
  accuracy = 0.99016
  eval_loss = 0.059763990643260025
  f1 = 0.39431164231961047
  n_correct = 7126
  n_gold = 28590
  n_pred = 7554
  precision = 0.9433412761450887
  recall = 0.24924798880727528
  task_f1 = 0.9664993896649938
  task_ngold = 7192
  task_recall = 0.9908231368186874
Epoch: 2, Step: 1404 / 1563, used_time = 7491.68s, loss = 0.111113
***** Eval results *****
  accuracy = 0.99148
  eval_loss = 0.05836684462891162
  f1 = 0.39511167765892596
  n_correct = 7129
  n_gold = 28590
  n_pred = 7496
  precision = 0.9510405549626467
  recall = 0.24935292060160896
  task_f1 = 0.9707244008714597
  task_ngold = 7192
  task_recall = 0.9912402669632926
Epoch: 2, Step: 1560 / 1563, used_time = 7756.90s, loss = 0.107869
***** Eval results *****
  accuracy = 0.99104
  eval_loss = 0.05806312847084926
  f1 = 0.3944567627494457
  n_correct = 7116
  n_gold = 28590
  n_pred = 7490
  precision = 0.9500667556742323
  recall = 0.24889821615949634
  task_f1 = 0.9693502247650184
  task_ngold = 7192
  task_recall = 0.9894327030033371
Start epoch #3 (lr = 2e-05)...
Epoch: 3, Step: 156 / 1563, used_time = 8024.38s, loss = 0.104532
***** Eval results *****
  accuracy = 0.99166
  eval_loss = 0.059693051826907866
  f1 = 0.39519862501039554
  n_correct = 7128
  n_gold = 28590
  n_pred = 7483
  precision = 0.9525591340371509
  recall = 0.24931794333683105
  task_f1 = 0.9714480408858603
  task_ngold = 7192
  task_recall = 0.9911012235817576
Epoch: 3, Step: 312 / 1563, used_time = 8291.38s, loss = 0.101774
***** Eval results *****
  accuracy = 0.99228
  eval_loss = 0.056395247367049345
  f1 = 0.39563914780292947
  n_correct = 7131
  n_gold = 28590
  n_pred = 7458
  precision = 0.9561544650040226
  recall = 0.24942287513116473
  task_f1 = 0.9735153583617748
  task_ngold = 7192
  task_recall = 0.9915183537263627
Epoch: 3, Step: 468 / 1563, used_time = 8564.93s, loss = 0.098936
***** Eval results *****
  accuracy = 0.99232
  eval_loss = 0.05976161361239109
  f1 = 0.3956610997059313
  n_correct = 7131
  n_gold = 28590
  n_pred = 7456
  precision = 0.9564109442060086
  recall = 0.24942287513116473
  task_f1 = 0.9736482796286182
  task_ngold = 7192
  task_recall = 0.9915183537263627
Epoch: 3, Step: 624 / 1563, used_time = 8829.76s, loss = 0.096143