seed:  5703958
{'<start>': 4, 'E-MISC': 3, '<pad>': 5, 'O': 6, 'S-MISC': 0, 'I-MISC': 2, 'B-MISC': 1}
setting:
Namespace(allowspan=6, batch_size=10, char_embedding_dim=30, char_lstm=True, char_lstm_hidden_dim=300, char_lstm_layers=1, checkpoint='./checkpoint/', clip_grad=5.0, cnn_filter_num=30, dev_file='./data/validation.txt', dropout_ratio=0.55, early_stop=10, emb_file='./data/myembed.txt', epoch=150, grconv=False, high_way=True, highway_layers=1, index_embeds_dim=10, least_epoch=75, load_check_point='', load_opt=False, lr=0.015, lr_decay=0.05, mini_count=5, model_name='HSCRF', momentum=0.9, scrf_dense_dim=100, shrink_embedding=False, start_epoch=0, test_file='./data/test.txt', train_file='./data/train.txt', unk='unk', word_embedding_dim=300, word_hidden_dim=300, word_lstm_layers=1)
loading corpus
constructing coding table
/Users/Troller/Downloads/HSCRF-pytorch-master/model/utils.py:637: UserWarning: nn.init.uniform is now deprecated in favor of nn.init.uniform_.
  nn.init.uniform(input_embedding, -bias, bias)
constructing dataset
Traceback (most recent call last):
  File "train.py", line 119, in <module>
    dataset, dataset_onlycrf = utils.construct_bucket_mean_vb_wc(train_features, train_labels, CRF_l_map, SCRF_l_map, c_map, f_map, SCRF_stop_tag=SCRF_l_map['<STOP>'], ALLOW_SPANLEN=args.allowspan, train_set=True)
ValueError: too many values to unpack