Closed Ricardokevins closed 2 years ago
I try to fix error myself, so i print the output_dict
{'coref': {'loss': 0}, 'relation': {'loss': 0}, 'ner': {'loss': 0}, 'events': {'loss': 0}, 'loss': tensor(0.), 'metadata': 0: Marseille prosecutor says " so far no videos were used in the crash investigation " despite media reports .
1: Journalists at Bild and Paris Match are " very confident " the video clip is real , an editor says .
2: Andreas Lubitz had informed his Lufthansa training school of an episode of severe depression , airline says .
3:
Membership gives the ICC jurisdiction over alleged crimes committed in Palestinian territories since last June .
4: Israel and the United States opposed the move , which could open the door to war crimes investigations against Israelis .
5:
Amnesty 's annual death penalty report catalogs encouraging signs , but setbacks in numbers of those sentenced to death .
6: Organization claims that governments around the world are using the threat of terrorism to advance executions .
7: The number of executions worldwide has gone down by almost 22 % compared with 2013 , but death sentences up by 28 % .
8:
Amnesty International releases its annual review of the death penalty worldwide ; much of it makes for grim reading .
9: Salil Shetty : Countries that use executions to deal with problems are on the wrong side of history .
10:
Museum : Anne Frank died earlier than previously believed .
11: Researchers re - examined archives and testimonies of survivors .
12: Anne and older sister Margot Frank are believed to have died in February 1945 .
13:
Student is no longer on Duke University campus and will face disciplinary review .
14: School officials identified student during investigation and the person admitted to hanging the noose , Duke says .
15: The noose , made of rope , was discovered on campus about 2 a.m.
16:
The Rev. Robert Schuller , 88 , had been diagnosed with esophageal cancer in 2013 .
17: His TV show , " Hour of Power , " was enormously popular in the 1970s and 1980s .
18:
Theia , a bully breed mix , was apparently hit by a car , whacked with a hammer and buried in a field .
19: " She 's a true miracle dog and she deserves a good life , " says Sara Mellado , who is looking for a home for Theia .
20:
Mohammad Javad Zarif has spent more time with John Kerry than any other foreign minister .
21: He once participated in a takeover of the Iranian Consulate in San Francisco .
22: The Iranian foreign minister tweets in English .
23:
Bob Barker returned to host " The Price Is Right " on Wednesday .
24: Barker , 91 , had retired as host in 2007 .
25:
College - bound basketball star asks girl with Down syndrome to high school prom .
26: Pictures of the two during the " prom - posal " have gone viral .
27:
28: Former GOP representative compares President Obama to Andreas Lubitz .
29: Bachmann said with possible Iran deal , Obama will fly " entire nation into the rocks " Reaction on social media ?
30: She was blasted by Facebook commenters .
31:
}
{'coref': 0, 'events': 1, 'ner': 0.5, 'relation': 0.5}
full log as follows:
2022-03-12 18:09:00,918 - INFO - allennlp.common.plugins - Plugin allennlp_models available
2022-03-12 18:09:01,029 - INFO - allennlp.models.archival - loading archive file Mydata/ace05-event.tar.gz
2022-03-12 18:09:01,030 - INFO - allennlp.models.archival - extracting archive file Mydata/ace05-event.tar.gz to temp dir /tmp/tmpl55upr30
2022-03-12 18:09:06,447 - INFO - allennlp.common.params - type = from_instances
2022-03-12 18:09:06,448 - INFO - allennlp.data.vocabulary - Loading token dictionary from /tmp/tmpl55upr30/vocabulary.
2022-03-12 18:09:06,449 - INFO - allennlp.common.params - model.type = dygie
2022-03-12 18:09:06,450 - INFO - allennlp.common.params - model.embedder.type = basic
2022-03-12 18:09:06,453 - INFO - allennlp.common.params - model.embedder.token_embedders.bert.type = pretrained_transformer_mismatched
2022-03-12 18:09:06,453 - INFO - allennlp.common.params - model.embedder.token_embedders.bert.model_name = roberta-base
2022-03-12 18:09:06,453 - INFO - allennlp.common.params - model.embedder.token_embedders.bert.max_length = 512
2022-03-12 18:09:06,453 - INFO - allennlp.common.params - model.embedder.token_embedders.bert.train_parameters = True
2022-03-12 18:09:06,454 - INFO - allennlp.common.params - model.embedder.token_embedders.bert.last_layer_only = True
2022-03-12 18:09:06,454 - INFO - allennlp.common.params - model.embedder.token_embedders.bert.gradient_checkpointing = None
roberta-base
2022-03-12 18:09:06,455 - INFO - transformers.configuration_utils - loading configuration file /root/SheShuaijie/Data/PLM/roberta-base/config.json
2022-03-12 18:09:06,456 - INFO - transformers.configuration_utils - Model config RobertaConfig {
"architectures": [
"RobertaForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"type_vocab_size": 1,
"vocab_size": 50265
}
2022-03-12 18:09:06,456 - INFO - transformers.modeling_utils - loading weights file /root/SheShuaijie/Data/PLM/roberta-base/pytorch_model.bin
2022-03-12 18:09:12,244 - INFO - transformers.modeling_utils - All model checkpoint weights were used when initializing RobertaModel.
2022-03-12 18:09:12,245 - INFO - transformers.modeling_utils - All the weights of RobertaModel were initialized from the model checkpoint at /root/SheShuaijie/Data/PLM/roberta-base.
If your task is similar to the task the model of the ckeckpoint was trained on, you can already use RobertaModel for predictions without further training.
2022-03-12 18:09:12,394 - INFO - transformers.configuration_utils - loading configuration file /root/SheShuaijie/Data/PLM/roberta-base/config.json
2022-03-12 18:09:12,395 - INFO - transformers.configuration_utils - Model config RobertaConfig {
"architectures": [
"RobertaForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"type_vocab_size": 1,
"vocab_size": 50265
}
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - Model name '/root/SheShuaijie/Data/PLM/roberta-base' not found in model shortcut name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). Assuming '/root/SheShuaijie/Data/PLM/roberta-base' is a path, a model identifier, or url to a directory containing tokenizer files.
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - Didn't find file /root/SheShuaijie/Data/PLM/roberta-base/added_tokens.json. We won't load it.
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - Didn't find file /root/SheShuaijie/Data/PLM/roberta-base/special_tokens_map.json. We won't load it.
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - Didn't find file /root/SheShuaijie/Data/PLM/roberta-base/tokenizer_config.json. We won't load it.
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - loading file /root/SheShuaijie/Data/PLM/roberta-base/vocab.json
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - loading file /root/SheShuaijie/Data/PLM/roberta-base/merges.txt
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - loading file None
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - loading file None
2022-03-12 18:09:12,396 - INFO - transformers.tokenization_utils_base - loading file None
2022-03-12 18:09:12,397 - INFO - transformers.tokenization_utils_base - loading file /root/SheShuaijie/Data/PLM/roberta-base/tokenizer.json
2022-03-12 18:09:12,488 - INFO - transformers.configuration_utils - loading configuration file /root/SheShuaijie/Data/PLM/roberta-base/config.json
2022-03-12 18:09:12,489 - INFO - transformers.configuration_utils - Model config RobertaConfig {
"architectures": [
"RobertaForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"type_vocab_size": 1,
"vocab_size": 50265
}
2022-03-12 18:09:12,490 - INFO - transformers.tokenization_utils_base - Model name '/root/SheShuaijie/Data/PLM/roberta-base' not found in model shortcut name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). Assuming '/root/SheShuaijie/Data/PLM/roberta-base' is a path, a model identifier, or url to a directory containing tokenizer files.
2022-03-12 18:09:12,490 - INFO - transformers.tokenization_utils_base - Didn't find file /root/SheShuaijie/Data/PLM/roberta-base/added_tokens.json. We won't load it.
2022-03-12 18:09:12,490 - INFO - transformers.tokenization_utils_base - Didn't find file /root/SheShuaijie/Data/PLM/roberta-base/special_tokens_map.json. We won't load it.
2022-03-12 18:09:12,490 - INFO - transformers.tokenization_utils_base - Didn't find file /root/SheShuaijie/Data/PLM/roberta-base/tokenizer_config.json. We won't load it.
2022-03-12 18:09:12,490 - INFO - transformers.tokenization_utils_base - loading file /root/SheShuaijie/Data/PLM/roberta-base/vocab.json
2022-03-12 18:09:12,491 - INFO - transformers.tokenization_utils_base - loading file /root/SheShuaijie/Data/PLM/roberta-base/merges.txt
2022-03-12 18:09:12,491 - INFO - transformers.tokenization_utils_base - loading file None
2022-03-12 18:09:12,491 - INFO - transformers.tokenization_utils_base - loading file None
2022-03-12 18:09:12,491 - INFO - transformers.tokenization_utils_base - loading file None
2022-03-12 18:09:12,491 - INFO - transformers.tokenization_utils_base - loading file /root/SheShuaijie/Data/PLM/roberta-base/tokenizer.json
2022-03-12 18:09:12,579 - INFO - allennlp.common.params - model.feature_size = 20
2022-03-12 18:09:12,579 - INFO - allennlp.common.params - model.max_span_width = 8
2022-03-12 18:09:12,579 - INFO - allennlp.common.params - model.target_task = events
2022-03-12 18:09:12,580 - INFO - allennlp.common.params - model.initializer.regexes.0.1.type = xavier_normal
2022-03-12 18:09:12,580 - INFO - allennlp.common.params - model.initializer.regexes.0.1.gain = 1.0
2022-03-12 18:09:12,580 - INFO - allennlp.common.params - model.initializer.prevent_regexes = None
2022-03-12 18:09:12,581 - INFO - allennlp.common.params - model.module_initializer.regexes.0.1.type = xavier_normal
2022-03-12 18:09:12,581 - INFO - allennlp.common.params - model.module_initializer.regexes.0.1.gain = 1.0
2022-03-12 18:09:12,581 - INFO - allennlp.common.params - model.module_initializer.regexes.1.1.type = xavier_normal
2022-03-12 18:09:12,581 - INFO - allennlp.common.params - model.module_initializer.regexes.1.1.gain = 1.0
2022-03-12 18:09:12,582 - INFO - allennlp.common.params - model.module_initializer.prevent_regexes = None
2022-03-12 18:09:12,582 - INFO - allennlp.common.params - model.regularizer = None
2022-03-12 18:09:12,582 - INFO - allennlp.common.params - model.display_metrics = None
2022-03-12 18:09:12,583 - INFO - allennlp.common.params - ner.regularizer = None
2022-03-12 18:09:12,586 - INFO - allennlp.common.params - coref.spans_per_word = 0.3
2022-03-12 18:09:12,586 - INFO - allennlp.common.params - coref.max_antecedents = 100
2022-03-12 18:09:12,586 - INFO - allennlp.common.params - coref.coref_prop = 0
2022-03-12 18:09:12,586 - INFO - allennlp.common.params - coref.coref_prop_dropout_f = 0.0
2022-03-12 18:09:12,586 - INFO - allennlp.common.params - coref.regularizer = None
2022-03-12 18:09:12,637 - INFO - allennlp.common.params - relation.spans_per_word = 0.5
2022-03-12 18:09:12,637 - INFO - allennlp.common.params - relation.positive_label_weight = 1.0
2022-03-12 18:09:12,637 - INFO - allennlp.common.params - relation.regularizer = None
2022-03-12 18:09:12,648 - INFO - allennlp.common.params - events.trigger_spans_per_word = 0.3
2022-03-12 18:09:12,648 - INFO - allennlp.common.params - events.argument_spans_per_word = 0.8
2022-03-12 18:09:12,648 - INFO - allennlp.common.params - events.regularizer = None
2022-03-12 18:09:12,659 - INFO - allennlp.nn.initializers - Initializing parameters
2022-03-12 18:09:12,659 - INFO - allennlp.nn.initializers - Initializing _ner_scorers.ace-event__ner_labels.0._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - Initializing _ner_scorers.ace-event__ner_labels.0._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - Initializing _ner_scorers.ace-event__ner_labels.1._module.weight using .*weight initializer
2022-03-12 18:09:12,663 - WARNING - allennlp.nn.initializers - Did not use initialization regex that was passed: .*weight_matrix
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - Done initializing parameters; the following parameters are using their default initialization from their code
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - _ner_scorers.ace-event__ner_labels.0._module._linear_layers.0.bias
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - _ner_scorers.ace-event__ner_labels.0._module._linear_layers.1.bias
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - _ner_scorers.ace-event__ner_labels.1._module.bias
2022-03-12 18:09:12,663 - INFO - allennlp.nn.initializers - Initializing parameters
2022-03-12 18:09:12,664 - INFO - allennlp.nn.initializers - Initializing _distance_embedding.weight using .*weight initializer
2022-03-12 18:09:12,664 - INFO - allennlp.nn.initializers - Initializing _antecedent_feedforward._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,672 - INFO - allennlp.nn.initializers - Initializing _antecedent_feedforward._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,673 - INFO - allennlp.nn.initializers - Initializing _mention_pruner._scorer.0._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,676 - INFO - allennlp.nn.initializers - Initializing _mention_pruner._scorer.0._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,676 - INFO - allennlp.nn.initializers - Initializing _mention_pruner._scorer.1._module.weight using .*weight initializer
2022-03-12 18:09:12,676 - INFO - allennlp.nn.initializers - Initializing _antecedent_scorer._module.weight using .*weight initializer
2022-03-12 18:09:12,676 - INFO - allennlp.nn.initializers - Initializing _f_network._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,730 - WARNING - allennlp.nn.initializers - Did not use initialization regex that was passed: .*weight_matrix
2022-03-12 18:09:12,730 - INFO - allennlp.nn.initializers - Done initializing parameters; the following parameters are using their default initialization from their code
2022-03-12 18:09:12,730 - INFO - allennlp.nn.initializers - _antecedent_feedforward._module._linear_layers.0.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - _antecedent_feedforward._module._linear_layers.1.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - _antecedent_scorer._module.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - _f_network._linear_layers.0.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - _mention_pruner._scorer.0._module._linear_layers.0.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - _mention_pruner._scorer.0._module._linear_layers.1.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - _mention_pruner._scorer.1._module.bias
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - Initializing parameters
2022-03-12 18:09:12,731 - INFO - allennlp.nn.initializers - Initializing _mention_pruners.ace-event__relation_labels._scorer.0._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,734 - INFO - allennlp.nn.initializers - Initializing _mention_pruners.ace-event__relation_labels._scorer.0._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,734 - INFO - allennlp.nn.initializers - Initializing _mention_pruners.ace-event__relation_labels._scorer.1._module.weight using .*weight initializer
2022-03-12 18:09:12,735 - INFO - allennlp.nn.initializers - Initializing _relation_feedforwards.ace-event__relation_labels._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,743 - INFO - allennlp.nn.initializers - Initializing _relation_feedforwards.ace-event__relation_labels._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - Initializing _relation_scorers.ace-event__relation_labels.weight using .*weight initializer
2022-03-12 18:09:12,744 - WARNING - allennlp.nn.initializers - Did not use initialization regex that was passed: .*weight_matrix
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - Done initializing parameters; the following parameters are using their default initialization from their code
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - _mention_pruners.ace-event__relation_labels._scorer.0._module._linear_layers.0.bias
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - _mention_pruners.ace-event__relation_labels._scorer.0._module._linear_layers.1.bias
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - _mention_pruners.ace-event__relation_labels._scorer.1._module.bias
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - _relation_feedforwards.ace-event__relation_labels._linear_layers.0.bias
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - _relation_feedforwards.ace-event__relation_labels._linear_layers.1.bias
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - _relation_scorers.ace-event__relation_labels.bias
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - Initializing parameters
2022-03-12 18:09:12,744 - INFO - allennlp.nn.initializers - Initializing _trigger_scorers.ace-event__trigger_labels.0._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,746 - INFO - allennlp.nn.initializers - Initializing _trigger_scorers.ace-event__trigger_labels.0._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,746 - INFO - allennlp.nn.initializers - Initializing _trigger_scorers.ace-event__trigger_labels.1._module.weight using .*weight initializer
2022-03-12 18:09:12,746 - INFO - allennlp.nn.initializers - Initializing _trigger_pruners.ace-event__trigger_labels._scorer.0._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,748 - INFO - allennlp.nn.initializers - Initializing _trigger_pruners.ace-event__trigger_labels._scorer.0._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,749 - INFO - allennlp.nn.initializers - Initializing _trigger_pruners.ace-event__trigger_labels._scorer.1._module.weight using .*weight initializer
2022-03-12 18:09:12,749 - INFO - allennlp.nn.initializers - Initializing _mention_pruners.ace-event__argument_labels._scorer.0._module._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,752 - INFO - allennlp.nn.initializers - Initializing _mention_pruners.ace-event__argument_labels._scorer.0._module._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,752 - INFO - allennlp.nn.initializers - Initializing _mention_pruners.ace-event__argument_labels._scorer.1._module.weight using .*weight initializer
2022-03-12 18:09:12,752 - INFO - allennlp.nn.initializers - Initializing _argument_feedforwards.ace-event__argument_labels._linear_layers.0.weight using .*weight initializer
2022-03-12 18:09:12,757 - INFO - allennlp.nn.initializers - Initializing _argument_feedforwards.ace-event__argument_labels._linear_layers.1.weight using .*weight initializer
2022-03-12 18:09:12,757 - INFO - allennlp.nn.initializers - Initializing _argument_scorers.ace-event__argument_labels.weight using .*weight initializer
2022-03-12 18:09:12,757 - INFO - allennlp.nn.initializers - Initializing _distance_embedding.weight using .*weight initializer
2022-03-12 18:09:12,757 - WARNING - allennlp.nn.initializers - Did not use initialization regex that was passed: .*weight_matrix
2022-03-12 18:09:12,757 - INFO - allennlp.nn.initializers - Done initializing parameters; the following parameters are using their default initialization from their code
2022-03-12 18:09:12,757 - INFO - allennlp.nn.initializers - _argument_feedforwards.ace-event__argument_labels._linear_layers.0.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _argument_feedforwards.ace-event__argument_labels._linear_layers.1.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _argument_scorers.ace-event__argument_labels.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _mention_pruners.ace-event__argument_labels._scorer.0._module._linear_layers.0.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _mention_pruners.ace-event__argument_labels._scorer.0._module._linear_layers.1.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _mention_pruners.ace-event__argument_labels._scorer.1._module.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _trigger_pruners.ace-event__trigger_labels._scorer.0._module._linear_layers.0.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _trigger_pruners.ace-event__trigger_labels._scorer.0._module._linear_layers.1.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _trigger_pruners.ace-event__trigger_labels._scorer.1._module.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _trigger_scorers.ace-event__trigger_labels.0._module._linear_layers.0.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _trigger_scorers.ace-event__trigger_labels.0._module._linear_layers.1.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - _trigger_scorers.ace-event__trigger_labels.1._module.bias
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - Initializing parameters
2022-03-12 18:09:12,758 - INFO - allennlp.nn.initializers - Initializing _endpoint_span_extractor._span_width_embedding.weight using _span_width_embedding.weight initializer
2022-03-12 18:09:12,761 - INFO - allennlp.nn.initializers - Done initializing parameters; the following parameters are using their default initialization from their code
2022-03-12 18:09:12,761 - INFO - allennlp.nn.initializers - _coref._antecedent_feedforward._module._linear_layers.0.bias
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2022-03-12 18:09:12,762 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.embeddings.LayerNorm.bias
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2022-03-12 18:09:12,764 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.1.attention.output.LayerNorm.bias
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2022-03-12 18:09:12,765 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.1.output.dense.bias
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2022-03-12 18:09:12,765 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.10.attention.output.LayerNorm.bias
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2022-03-12 18:09:12,765 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.10.intermediate.dense.bias
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2022-03-12 18:09:12,766 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.10.output.LayerNorm.bias
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2022-03-12 18:09:12,766 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.11.attention.output.LayerNorm.bias
2022-03-12 18:09:12,766 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.11.attention.output.LayerNorm.weight
2022-03-12 18:09:12,766 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.11.attention.output.dense.bias
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2022-03-12 18:09:12,766 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.11.attention.self.key.bias
2022-03-12 18:09:12,766 - INFO - allennlp.nn.initializers - _embedder.token_embedder_bert._matched_embedder.transformer_model.encoder.layer.11.attention.self.key.weight
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2022-03-12 18:09:12,778 - INFO - allennlp.nn.initializers - _relation._mention_pruners.ace-event__relation_labels._scorer.0._module._linear_layers.0.bias
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2022-03-12 18:09:12,779 - INFO - allennlp.nn.initializers - _relation._relation_scorers.ace-event__relation_labels.weight
2022-03-12 18:09:15,188 - INFO - root - Loading a model trained before embedding extension was implemented; pass an explicit vocab namespace if you want to extend the vocabulary.
2022-03-12 18:09:15,189 - INFO - root - Loading a model trained before embedding extension was implemented; pass an explicit vocab namespace if you want to extend the vocabulary.
2022-03-12 18:09:15,190 - INFO - root - Loading a model trained before embedding extension was implemented; pass an explicit vocab namespace if you want to extend the vocabulary.
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.type = dygie
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.lazy = False
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.cache_directory = None
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.max_instances = None
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.manual_distributed_sharding = False
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.manual_multi_process_sharding = False
2022-03-12 18:09:15,666 - INFO - allennlp.common.params - dataset_reader.max_span_width = 8
2022-03-12 18:09:15,667 - INFO - allennlp.common.params - dataset_reader.token_indexers.bert.type = pretrained_transformer_mismatched
2022-03-12 18:09:15,667 - INFO - allennlp.common.params - dataset_reader.token_indexers.bert.token_min_padding_length = 0
2022-03-12 18:09:15,667 - INFO - allennlp.common.params - dataset_reader.token_indexers.bert.model_name = roberta-base
2022-03-12 18:09:15,667 - INFO - allennlp.common.params - dataset_reader.token_indexers.bert.namespace = tags
2022-03-12 18:09:15,667 - INFO - allennlp.common.params - dataset_reader.token_indexers.bert.max_length = 512
reading instances: 0it [00:00, ?it/s]/root/SheShuaijie/workspace/dygiepp-master/dygie/data/dataset_readers/dygie.py:195: UserWarning: Document doc1 has a sentence with a single token or no tokens. This may break the modeling code.
warnings.warn(msg)
/root/SheShuaijie/workspace/dygiepp-master/dygie/data/dataset_readers/dygie.py:195: UserWarning: Document doc2 has a sentence with a single token or no tokens. This may break the modeling code.
warnings.warn(msg)
reading instances: 2it [00:00, 73.82it/s]
And my Data for predict
{"doc_key": "doc1", "dataset": "ace05-event", "sentences": [["Marseille", "prosecutor", "says", "\"", "so", "far", "no", "videos", "were", "used", "in", "the", "crash", "investigation", "\"", "despite", "media", "reports", "."], ["Journalists", "at", "Bild", "and", "Paris", "Match", "are", "\"", "very", "confident", "\"", "the", "video", "clip", "is", "real", ",", "an", "editor", "says", "."], ["Andreas", "Lubitz", "had", "informed", "his", "Lufthansa", "training", "school", "of", "an", "episode", "of", "severe", "depression", ",", "airline", "says", "."], ["\n", "Membership", "gives", "the", "ICC", "jurisdiction", "over", "alleged", "crimes", "committed", "in", "Palestinian", "territories", "since", "last", "June", "."], ["Israel", "and", "the", "United", "States", "opposed", "the", "move", ",", "which", "could", "open", "the", "door", "to", "war", "crimes", "investigations", "against", "Israelis", "."], ["\n", "Amnesty", "'s", "annual", "death", "penalty", "report", "catalogs", "encouraging", "signs", ",", "but", "setbacks", "in", "numbers", "of", "those", "sentenced", "to", "death", "."], ["Organization", "claims", "that", "governments", "around", "the", "world", "are", "using", "the", "threat", "of", "terrorism", "to", "advance", "executions", "."], ["The", "number", "of", "executions", "worldwide", "has", "gone", "down", "by", "almost", "22", "%", "compared", "with", "2013", ",", "but", "death", "sentences", "up", "by", "28", "%", "."], ["\n", "Amnesty", "International", "releases", "its", "annual", "review", "of", "the", "death", "penalty", "worldwide", ";", "much", "of", "it", "makes", "for", "grim", "reading", "."], ["Salil", "Shetty", ":", "Countries", "that", "use", "executions", "to", "deal", "with", "problems", "are", "on", "the", "wrong", "side", "of", "history", "."], ["\n", "Museum", ":", "Anne", "Frank", "died", "earlier", "than", "previously", "believed", "."], ["Researchers", "re", "-", "examined", "archives", "and", "testimonies", "of", "survivors", "."], ["Anne", "and", "older", "sister", "Margot", "Frank", "are", "believed", "to", "have", "died", "in", "February", "1945", "."], ["\n", "Student", "is", "no", "longer", "on", "Duke", "University", "campus", "and", "will", "face", "disciplinary", "review", "."], ["School", "officials", "identified", "student", "during", "investigation", "and", "the", "person", "admitted", "to", "hanging", "the", "noose", ",", "Duke", "says", "."], ["The", "noose", ",", "made", "of", "rope", ",", "was", "discovered", "on", "campus", "about", "2", "a.m."], ["\n", "The", "Rev.", "Robert", "Schuller", ",", "88", ",", "had", "been", "diagnosed", "with", "esophageal", "cancer", "in", "2013", "."], ["His", "TV", "show", ",", "\"", "Hour", "of", "Power", ",", "\"", "was", "enormously", "popular", "in", "the", "1970s", "and", "1980s", "."], ["\n", "Theia", ",", "a", "bully", "breed", "mix", ",", "was", "apparently", "hit", "by", "a", "car", ",", "whacked", "with", "a", "hammer", "and", "buried", "in", "a", "field", "."], ["\"", "She", "'s", "a", "true", "miracle", "dog", "and", "she", "deserves", "a", "good", "life", ",", "\"", "says", "Sara", "Mellado", ",", "who", "is", "looking", "for", "a", "home", "for", "Theia", "."], ["\n", "Mohammad", "Javad", "Zarif", "has", "spent", "more", "time", "with", "John", "Kerry", "than", "any", "other", "foreign", "minister", "."], ["He", "once", "participated", "in", "a", "takeover", "of", "the", "Iranian", "Consulate", "in", "San", "Francisco", "."], ["The", "Iranian", "foreign", "minister", "tweets", "in", "English", "."], ["\n", "Bob", "Barker", "returned", "to", "host", "\"", "The", "Price", "Is", "Right", "\"", "on", "Wednesday", "."], ["Barker", ",", "91", ",", "had", "retired", "as", "host", "in", "2007", "."], ["\n", "College", "-", "bound", "basketball", "star", "asks", "girl", "with", "Down", "syndrome", "to", "high", "school", "prom", "."], ["Pictures", "of", "the", "two", "during", "the", "\"", "prom", "-", "posal", "\"", "have", "gone", "viral", "."], ["\n"], ["Former", "GOP", "representative", "compares", "President", "Obama", "to", "Andreas", "Lubitz", "."], ["Bachmann", "said", "with", "possible", "Iran", "deal", ",", "Obama", "will", "fly", "\"", "entire", "nation", "into", "the", "rocks", "\"", "Reaction", "on", "social", "media", "?"], ["She", "was", "blasted", "by", "Facebook", "commenters", "."], ["\n"]]}
{"doc_key": "doc2", "dataset": "ace05-event", "sentences": [["Americans", "paid", "more", "for", "some", "fruits", "and", "vegetables", "last", "year", "because", "of", "the", "drought", "."], ["Tourists", "will", "now", "have", "to", "ask", "for", "a", "glass", "of", "water", "at", "a", "California", "restaurant", "."], ["Perhaps", "the", "only", "good", "thing", "is", "another", "\"", "great", "\"", "wine", "grape", "harvest", "last", "year", "."], ["\n"], ["While", "Republican", "Gov.", "Asa", "Hutchinson", "was", "weighing", "an", "Arkansas", "religious", "freedom", "bill", ",", "Walmart", "voiced", "its", "opposition", "."], ["Walmart", "and", "other", "high", "-", "profile", "businesses", "are", "showing", "their", "support", "for", "gay", "and", "lesbian", "rights", "."], ["Their", "stance", "puts", "them", "in", "conflict", "with", "socially", "conservative", "Republicans", ",", "traditionally", "seen", "as", "allies", "."], ["\n", "17", "Americans", "were", "exposed", "to", "the", "Ebola", "virus", "while", "in", "Sierra", "Leone", "in", "March", "."], ["Another", "person", "was", "diagnosed", "with", "the", "disease", "and", "taken", "to", "hospital", "in", "Maryland", "."], ["National", "Institutes", "of", "Health", "says", "the", "patient", "is", "in", "fair", "condition", "after", "weeks", "of", "treatment", "."], ["\n"], ["Andrew", "Getty", "'s", "death", "appears", "to", "be", "from", "natural", "causes", ",", "police", "say", ",", "citing", "coroner", "'s", "early", "assessment", "."], ["In", "a", "petition", "for", "a", "restraining", "order", ",", "Getty", "had", "written", "he", "had", "a", "serious", "medical", "condition", "."], ["Police", "say", "this", "is", "not", "a", "criminal", "matter", "at", "this", "time", "."], ["\n", "LZ", ":", "Indiana", "law", "pushing", "back", "LGBT", "rights", ",", "and", "other", "states", "'", "anti", "-", "LGBT", "moves", ",", "bow", "to", "far", "right", "wing", "that", "GOP", "candidates", "need", "for", "2016", "."], ["Cruz", ",", "Huckabee", ",", "Jindal", ",", "Carson", ",", "Walker", "are", "reviving", "culture", "wars", ",", "he", "says", "."], [" ", "Equality", "for", "LGBT", "has", "not", "yet", "\"", "won", "\"", "in", "America", "."], ["\n"], ["Once", "a", "super", "typhoon", ",", "Maysak", "is", "now", "a", "tropical", "storm", "with", "70", "mph", "winds", "."], ["It", "could", "still", "cause", "flooding", ",", "landslides", "and", "other", "problems", "in", "the", "Philippines", "."], ["\n", "Father", ":", "\"", "I", "know", "he", "went", "through", "what", "he", "went", "through", "\"", "Louis", "Jordan", "was", "found", "on", "his", "sailboat", ",", "which", "was", "listing", "and", "in", "bad", "shape", ",", "rescuer", "says", "."], ["He", "appears", "to", "be", "in", "good", "shape", ",", "physically", "and", "mentally", "."], ["\n", "\"", "Furious", "7", "\"", "pays", "tribute", "to", "star", "Paul", "Walker", ",", "who", "died", "during", "filming", "."], ["Vin", "Diesel", ":", "\"", "This", "movie", "is", "more", "than", "a", "movie", "\"", "\"", "Furious", "7", "\"", "opens", "Friday", "."]]}
Any Suggestion is highly Appreciate ~ I am still trying to Fix problem
one more thing to mention. when I run the code, It hit error with "Roberta-base' is not a identifier in huggingface model. So i download the model weight manully and modified the path to my local path. I not sure if it may cause the ERROR
ohhhhhhhhhh!!!!!
I fix this problem from history issue!
I create the test data with attribute "dataset" : ace05-event which cause the ERROR
When I read this issue https://github.com/dwadden/dygiepp/issues/80. I try to replace ace05-event with ace-event and fix the ERROR!
What's more this issue https://github.com/dwadden/dygiepp/issues/18 's data format is wrong which will cause same ERROR.
The Data format Will Cause ERROR:
{'doc_key': '0', 'sentences': [['Coronavirus', 'Thwarts', 'Rescue', 'of', 'Endangered', 'Albatrosses', 'Menaced', 'by', 'Giant', 'Mice'], ['The', 'covid-19', 'pandemic', 'has', 'forced', 'a', 'delay', 'to', 'an', 'effort', 'to', 'protect', 'vulnerable', 'seabirds', 'from', 'large,', 'invasive', 'mice', 'on', 'an', 'island', 'in', 'the', 'South', 'Atlantic', 'Ocean.']]}
And this
{"doc_key": "doc1", "dataset": "ace05-event", "sentences": [["Marseille", "prosecutor", "says", "\"", "so", "far", "no", "videos", "were", "used", "in", "the", "crash", "investigation", "\"", "despite", "media", "reports", "."], ["Journalists", "at", "Bild", "and", "Paris", "Match", "are", "\"", "very", "confident", "\"", "the", "video", "clip", "is", "real", ",", "an", "editor", "says", "."], ["Andreas", "Lubitz", "had", "informed", "his", "Lufthansa", "training", "school", "of", "an", "episode", "of", "severe", "depression", ",", "airline", "says", "."], ["\n", "Membership", "gives", "the", "ICC", "jurisdiction", "over", "alleged", "crimes", "committed", "in", "Palestinian", "territories", "since", "last", "June", "."], ["Israel", "and", "the", "United", "States", "opposed", "the", "move", ",", "which", "could", "open", "the", "door", "to", "war", "crimes", "investigations", "against", "Israelis", "."], ["\n", "Amnesty", "'s", "annual", "death", "penalty", "report", "catalogs", "encouraging", "signs", ",", "but", "setbacks", "in", "numbers", "of", "those", "sentenced", "to", "death", "."], ["Organization", "claims", "that", "governments", "around", "the", "world", "are", "using", "the", "threat", "of", "terrorism", "to", "advance", "executions", "."], ["The", "number", "of", "executions", "worldwide", "has", "gone", "down", "by", "almost", "22", "%", "compared", "with", "2013", ",", "but", "death", "sentences", "up", "by", "28", "%", "."], ["\n", "Amnesty", "International", "releases", "its", "annual", "review", "of", "the", "death", "penalty", "worldwide", ";", "much", "of", "it", "makes", "for", "grim", "reading", "."], ["Salil", "Shetty", ":", "Countries", "that", "use", "executions", "to", "deal", "with", "problems", "are", "on", "the", "wrong", "side", "of", "history", "."], ["\n", "Museum", ":", "Anne", "Frank", "died", "earlier", "than", "previously", "believed", "."], ["Researchers", "re", "-", "examined", "archives", "and", "testimonies", "of", "survivors", "."], ["Anne", "and", "older", "sister", "Margot", "Frank", "are", "believed", "to", "have", "died", "in", "February", "1945", "."], ["\n", "Student", "is", "no", "longer", "on", "Duke", "University", "campus", "and", "will", "face", "disciplinary", "review", "."], ["School", "officials", "identified", "student", "during", "investigation", "and", "the", "person", "admitted", "to", "hanging", "the", "noose", ",", "Duke", "says", "."], ["The", "noose", ",", "made", "of", "rope", ",", "was", "discovered", "on", "campus", "about", "2", "a.m."], ["\n", "The", "Rev.", "Robert", "Schuller", ",", "88", ",", "had", "been", "diagnosed", "with", "esophageal", "cancer", "in", "2013", "."], ["His", "TV", "show", ",", "\"", "Hour", "of", "Power", ",", "\"", "was", "enormously", "popular", "in", "the", "1970s", "and", "1980s", "."], ["\n", "Theia", ",", "a", "bully", "breed", "mix", ",", "was", "apparently", "hit", "by", "a", "car", ",", "whacked", "with", "a", "hammer", "and", "buried", "in", "a", "field", "."], ["\"", "She", "'s", "a", "true", "miracle", "dog", "and", "she", "deserves", "a", "good", "life", ",", "\"", "says", "Sara", "Mellado", ",", "who", "is", "looking", "for", "a", "home", "for", "Theia", "."], ["\n", "Mohammad", "Javad", "Zarif", "has", "spent", "more", "time", "with", "John", "Kerry", "than", "any", "other", "foreign", "minister", "."], ["He", "once", "participated", "in", "a", "takeover", "of", "the", "Iranian", "Consulate", "in", "San", "Francisco", "."], ["The", "Iranian", "foreign", "minister", "tweets", "in", "English", "."], ["\n", "Bob", "Barker", "returned", "to", "host", "\"", "The", "Price", "Is", "Right", "\"", "on", "Wednesday", "."], ["Barker", ",", "91", ",", "had", "retired", "as", "host", "in", "2007", "."], ["\n", "College", "-", "bound", "basketball", "star", "asks", "girl", "with", "Down", "syndrome", "to", "high", "school", "prom", "."], ["Pictures", "of", "the", "two", "during", "the", "\"", "prom", "-", "posal", "\"", "have", "gone", "viral", "."], ["\n"], ["Former", "GOP", "representative", "compares", "President", "Obama", "to", "Andreas", "Lubitz", "."], ["Bachmann", "said", "with", "possible", "Iran", "deal", ",", "Obama", "will", "fly", "\"", "entire", "nation", "into", "the", "rocks", "\"", "Reaction", "on", "social", "media", "?"], ["She", "was", "blasted", "by", "Facebook", "commenters", "."], ["\n"]]}
Correct Format
{"dataset": "ace-event","doc_key": "0", "sentences": [["Coronavirus", "Thwarts", "Rescue", "of", "Endangered", "Albatrosses", "Menaced", "by", "Giant", "Mice"], ["The", "covid-19", "pandemic", "has", "forced", "a", "delay", "to", "an", "effort", "to", "protect", "vulnerable", "seabirds", "from", "large", "invasive", "mice", "on", "an", "island", "in", "the", "South", "Atlantic", "Ocean."]]}
It`s quite Confused while the dataset will cause the output result ERROR
Hi, are you now able to get predictions out of the model? Are there any points you'd like clarified?
Hi, are you now able to get predictions out of the model? Are there any points you'd like clarified?
Thank you for your reply!
Hi I notice that in ACE dataset, An Event can be extract with TIME Argument. However in here's prediction I didn't see any TIME argument ( PERSON and ORG can be predicted) . Is it normal?
I believe the pretrained model wasn't trained with TIME
as an option. You can re-process the data with the appropriate flag set, and then train your own model if you'd like TIME
arguments included.
I believe the pretrained model wasn't trained with
TIME
as an option. You can re-process the data with the appropriate flag set, and then train your own model if you'd likeTIME
arguments included.
Thank you so much~
No problem, I hope it works!
Hi, Awesome and complete work. I want to use Trained ACE05-eventExtraction model as API to Extract Event. And I carefully Read the README.md, Click the model link in PretrainedModel Section (got a tar.xz file) And i use txt file ( one document per line ) and use the format_new_dataset.py create the data (from 2 txt file) After that I use the predict script under
However I meet ERROR: