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[01;32mxgg@decs[00m:[01;34m~/pros/MLM_transfer[00m$ bash scx[Kripts/p[Kfusion_method/run[K[K[Kfine_tune_yelp_fusion_method.sh
+ sleep 2h
+ PROJECTPATH=/home/xgg/pros/MLM_transfer
+ cp configs/bert_yelp_fusion_method.config run.config
+ PYTHONPATH=/home/xgg/pros/MLM_transfer
+ /home/xgg/.conda/envs/py36/bin//python fine_tune_bert.py
03/14/2019 09:05:58 - INFO - dataloader - device cuda n_gpu 1 distributed training False
03/14/2019 09:06:01 - INFO - dataloader - *** Example ***
03/14/2019 09:06:01 - INFO - dataloader - guid: train-1
03/14/2019 09:06:01 - INFO - dataloader - tokens: [CLS] james you are wonderful . [SEP]
03/14/2019 09:06:01 - INFO - dataloader - init_ids: 101 2508 2017 2024 6919 1012 102
03/14/2019 09:06:01 - INFO - dataloader - input_ids: 101 2508 2017 2024 103 1012 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
03/14/2019 09:06:01 - INFO - dataloader - input_mask: 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
03/14/2019 09:06:01 - INFO - dataloader - 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
03/14/2019 09:06:01 - INFO - dataloader - masked_lm_labels: -1 -1 -1 -1 6919 -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
03/14/2019 09:06:01 - INFO - dataloader - *** Example ***
03/14/2019 09:06:01 - INFO - dataloader - guid: train-2
03/14/2019 09:06:01 - INFO - dataloader - tokens: [CLS] thanks for being nice best friends staff ( ha ) . [SEP]
03/14/2019 09:06:01 - INFO - dataloader - init_ids: 101 4283 2005 2108 3835 2190 2814 3095 1006 5292 1007 1012 102
03/14/2019 09:06:01 - INFO - dataloader - input_ids: 101 103 103 103 3835 2190 2814 3095 1006 5292 1007 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
03/14/2019 09:06:01 - INFO - dataloader - input_mask: 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
03/14/2019 09:06:01 - INFO - dataloader - 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
03/14/2019 09:06:01 - INFO - dataloader - masked_lm_labels: -1 4283 2005 2108 -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
03/14/2019 09:06:01 - INFO - dataloader - *** Example ***
03/14/2019 09:06:01 - INFO - dataloader - guid: train-3
03/14/2019 09:06:01 - INFO - dataloader - tokens: [CLS] the staff is very friendly , and the food is great . [SEP]
03/14/2019 09:06:01 - INFO - dataloader - init_ids: 101 1996 3095 2003 2200 5379 1010 1998 1996 2833 2003 2307 1012 102
03/14/2019 09:06:01 - INFO - dataloader - input_ids: 101 1996 3095 2003 103 103 1010 1998 1996 2833 103 103 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
03/14/2019 09:06:01 - INFO - dataloader - input_mask: 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
03/14/2019 09:06:01 - INFO - dataloader - 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
03/14/2019 09:06:01 - INFO - dataloader - masked_lm_labels: -1 -1 -1 -1 2200 5379 -1 -1 -1 -1 2003 2307 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
03/14/2019 09:06:01 - INFO - dataloader - *** Example ***
03/14/2019 09:06:01 - INFO - dataloader - guid: train-4
03/14/2019 09:06:01 - INFO - dataloader - tokens: [CLS] this little gem is right around the corner from me ! [SEP]
03/14/2019 09:06:01 - INFO - dataloader - init_ids: 101 2023 2210 17070 2003 2157 2105 1996 3420 2013 2033 999 102
03/14/2019 09:06:01 - INFO - dataloader - input_ids: 101 103 103 103 2003 2157 2105 1996 3420 2013 2033 999 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
03/14/2019 09:06:01 - INFO - dataloader - input_mask: 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
03/14/2019 09:06:01 - INFO - dataloader - 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
03/14/2019 09:06:01 - INFO - dataloader - masked_lm_labels: -1 2023 2210 17070 -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
03/14/2019 09:06:01 - INFO - dataloader - *** Example ***
03/14/2019 09:06:01 - INFO - dataloader - guid: train-5
03/14/2019 09:06:01 - INFO - dataloader - tokens: [CLS] for a _ nu ##m _ star restaurant we expected better tasting food and far better service . [SEP]
03/14/2019 09:06:01 - INFO - dataloader - init_ids: 101 2005 1037 1035 16371 2213 1035 2732 4825 2057 3517 2488 18767 2833 1998 2521 2488 2326 1012 102
03/14/2019 09:06:01 - INFO - dataloader - input_ids: 101 2005 1037 1035 16371 2213 1035 2732 103 2057 3517 2488 18767 103 1998 2521 2488 2326 1012 102 0 0 0 0 0 0 0 0 0 0 0 0
03/14/2019 09:06:01 - INFO - dataloader - input_mask: 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
03/14/2019 09:06:01 - INFO - dataloader - 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
03/14/2019 09:06:01 - INFO - dataloader - masked_lm_labels: -1 -1 -1 -1 -1 -1 -1 -1 4825 -1 -1 -1 -1 2833 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
03/14/2019 09:06:55 - INFO - dataloader - ***** Running training *****
03/14/2019 09:06:55 - INFO - dataloader - Num examples = 447223
03/14/2019 09:06:55 - INFO - dataloader - Batch size = 32
03/14/2019 09:06:55 - INFO - dataloader - Num steps = 139757
**********************************************************
Namespace(bert_model='/home/xgg/.pytorch_pretrained_bert/bert-base-uncased.tar.gz', data_dir='./processed_data_fusion_method/yelp/', do_lower_case=True, do_train=True, eval_batch_size=8, gradient_accumulation_steps=1, learning_rate=2e-05, local_rank=-1, loss_scale=128, max_seq_length=32, no_cuda=False, num_train_epochs=10.0, optimize_on_cpu=False, output_dir='/tmp/yelp_output/', seed=42, task_name=None, train_batch_size=32, warmup_proportion=0.1)
03/14/2019 09:06:56 - INFO - pytorch_pretrained_bert.modeling - loading archive file /home/xgg/.pytorch_pretrained_bert/bert-base-uncased.tar.gz
03/14/2019 09:06:56 - INFO - pytorch_pretrained_bert.modeling - extracting archive file /home/xgg/.pytorch_pretrained_bert/bert-base-uncased.tar.gz to temp dir /tmp/tmp6ab2ywpb
03/14/2019 09:06:58 - INFO - pytorch_pretrained_bert.modeling - Model config {
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"max_position_embeddings": 512,
"num_attention_heads": 12,
"num_hidden_layers": 12,
"type_vocab_size": 2,
"vocab_size": 30522
}
03/14/2019 09:07:00 - INFO - pytorch_pretrained_bert.modeling - Weights from pretrained model not used in BertForMaskedLM: ['cls.seq_relationship.weight', 'cls.seq_relationship.bias']
Epoch: 0%| | 0/10 [00:00<?, ?it/s]avg_loss: 5.667283020019531
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Epoch: 10%|███████████████▋ | 1/10 [36:36<5:29:24, 2196.04s/it]avg_loss: 2.4292388725280762
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Epoch: 20%|███████████████████████████████ | 2/10 [1:13:06<4:52:35, 2194.48s/it]avg_loss: 2.047275018692017
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