Token Classification
spaCy
Turkish
Eval Results
BayanDuygu commited on
Commit
c7e06a7
1 Parent(s): c5b1ebd

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -31,3 +31,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tr_core_news_trf-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ morphologizer/model filter=lfs diff=lfs merge=lfs -text
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+ ner/model filter=lfs diff=lfs merge=lfs -text
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+ parser/model filter=lfs diff=lfs merge=lfs -text
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+ trainable_lemmatizer/model filter=lfs diff=lfs merge=lfs -text
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+ transformer/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
The diff for this file is too large to render. See raw diff
 
config.cfg ADDED
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+ [paths]
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+ tagger_model = "training/BOUN/model-best"
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+ ner_model = "training/NER/model-best"
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+ train = null
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+ dev = null
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+ vectors = null
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+ init_tok2vec = null
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+
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+ [system]
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+ seed = 0
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+ gpu_allocator = null
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+
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+ [nlp]
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+ lang = "tr"
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+ pipeline = ["transformer","tagger","morphologizer","trainable_lemmatizer","parser","ner"]
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+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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+ disabled = []
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+ before_creation = null
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+ after_creation = null
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+ after_pipeline_creation = null
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+ batch_size = 1000
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+
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+ [components]
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+
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+ [components.morphologizer]
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+ factory = "morphologizer"
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+ extend = false
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+ overwrite = true
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+ scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
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+
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+ [components.morphologizer.model]
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+ @architectures = "spacy.Tagger.v2"
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+ nO = null
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+ normalize = false
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+
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+ [components.morphologizer.model.tok2vec]
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+ @architectures = "spacy-transformers.TransformerListener.v1"
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+ grad_factor = 1.0
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ upstream = "*"
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+
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+ [components.ner]
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+ factory = "ner"
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+ incorrect_spans_key = null
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+ moves = null
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+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.ner.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ state_type = "ner"
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+ extra_state_tokens = false
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+ hidden_width = 64
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+ maxout_pieces = 2
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+ use_upper = false
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy-transformers.Tok2VecTransformer.v3"
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+ name = "dbmdz/bert-base-turkish-cased"
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+ mixed_precision = false
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ grad_factor = 1.0
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+
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+ [components.ner.model.tok2vec.get_spans]
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+ @span_getters = "spacy-transformers.strided_spans.v1"
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+ window = 128
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+ stride = 96
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+
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+ [components.ner.model.tok2vec.grad_scaler_config]
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+
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+ [components.ner.model.tok2vec.tokenizer_config]
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+ use_fast = true
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+
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+ [components.ner.model.tok2vec.transformer_config]
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+
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+ [components.parser]
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+ factory = "parser"
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+ learn_tokens = false
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+ min_action_freq = 30
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+ moves = null
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+ scorer = {"@scorers":"spacy.parser_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.parser.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ state_type = "parser"
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+ extra_state_tokens = false
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+ hidden_width = 128
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+ maxout_pieces = 3
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+ use_upper = false
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+ nO = null
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+
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+ [components.parser.model.tok2vec]
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+ @architectures = "spacy-transformers.TransformerListener.v1"
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+ grad_factor = 1.0
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ upstream = "*"
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+
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+ [components.tagger]
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+ factory = "tagger"
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+ neg_prefix = "!"
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+ overwrite = false
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+ scorer = {"@scorers":"spacy.tagger_scorer.v1"}
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+
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+ [components.tagger.model]
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+ @architectures = "spacy.Tagger.v2"
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+ nO = null
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+ normalize = false
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+
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+ [components.tagger.model.tok2vec]
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+ @architectures = "spacy-transformers.TransformerListener.v1"
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+ grad_factor = 1.0
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ upstream = "*"
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+
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+ [components.trainable_lemmatizer]
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+ factory = "trainable_lemmatizer"
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+ backoff = null
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+ min_tree_freq = 1
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+ overwrite = false
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+ scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
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+ top_k = 7
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+
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+ [components.trainable_lemmatizer.model]
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+ @architectures = "spacy.Tagger.v2"
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+ nO = null
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+ normalize = false
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+
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+ [components.trainable_lemmatizer.model.tok2vec]
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+ @architectures = "spacy-transformers.TransformerListener.v1"
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+ grad_factor = 1.0
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ upstream = "*"
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+
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+ [components.transformer]
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+ factory = "transformer"
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+ max_batch_items = 4096
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+ set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
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+
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+ [components.transformer.model]
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+ @architectures = "spacy-transformers.TransformerModel.v3"
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+ name = "dbmdz/bert-base-turkish-cased"
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+ mixed_precision = false
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+
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+ [components.transformer.model.get_spans]
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+ @span_getters = "spacy-transformers.strided_spans.v1"
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+ window = 128
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+ stride = 96
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+
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+ [components.transformer.model.grad_scaler_config]
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+
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+ [components.transformer.model.tokenizer_config]
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+ use_fast = true
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+
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+ [components.transformer.model.transformer_config]
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+
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+ [corpora]
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+
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+ [corpora.dev]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.dev}
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+ gold_preproc = false
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+ max_length = 0
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+ limit = 0
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+ augmenter = null
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+
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+ [corpora.train]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
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+ gold_preproc = false
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+ max_length = 0
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+ limit = 0
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+ augmenter = null
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+
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+ [training]
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+ seed = ${system.seed}
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+ gpu_allocator = ${system.gpu_allocator}
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+ dropout = 0.1
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+ accumulate_gradient = 1
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+ patience = 1600
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+ max_epochs = 0
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+ max_steps = 20000
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+ eval_frequency = 200
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+ frozen_components = []
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+ annotating_components = []
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+ dev_corpus = "corpora.dev"
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+ train_corpus = "corpora.train"
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+ before_to_disk = null
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+
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+ [training.batcher]
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+ @batchers = "spacy.batch_by_words.v1"
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+ discard_oversize = false
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+ tolerance = 0.2
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+ get_length = null
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+
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+ [training.batcher.size]
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+ @schedules = "compounding.v1"
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+ start = 100
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+ stop = 1000
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+ compound = 1.001
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+ t = 0.0
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+
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+ [training.logger]
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+ @loggers = "spacy.ConsoleLogger.v1"
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+ progress_bar = false
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+
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+ [training.optimizer]
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+ @optimizers = "Adam.v1"
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+ beta1 = 0.9
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+ beta2 = 0.999
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+ L2_is_weight_decay = true
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+ L2 = 0.01
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+ grad_clip = 1.0
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+ use_averages = false
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+ eps = 0.00000001
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+ learn_rate = 0.001
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+
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+ [training.score_weights]
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+ tag_acc = 0.2
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+ pos_acc = 0.1
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+ morph_acc = 0.1
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+ morph_per_feat = null
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+ lemma_acc = 0.2
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+ dep_uas = 0.1
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+ dep_las = 0.1
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+ dep_las_per_type = null
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+ sents_p = null
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+ sents_r = null
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+ sents_f = 0.0
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+ ents_f = 0.2
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+ ents_p = 0.0
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+ ents_r = 0.0
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+ ents_per_type = null
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+
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+ [pretraining]
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+
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+ [initialize]
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+ vectors = ${paths.vectors}
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+ init_tok2vec = ${paths.init_tok2vec}
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+ vocab_data = null
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+ lookups = null
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+ before_init = null
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+ after_init = null
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+
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+ [initialize.components]
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+
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+ [initialize.tokenizer]
meta.json ADDED
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+ {
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+ "labels":[
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+ "ADP",
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+ "ADV",
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+ "ANum",
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+ "ANum_Adj",
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+ "ANum_Ness",
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+ "ANum_Noun",
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+ "ANum_With",
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+ "ANum_Zero",
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+ "Abr",
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+ "Adj_With",
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+ "Adj_Without",
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+ "Adj_Zero",
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+ "Adv",
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+ "Adverb",
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+ "Adverb_Adverb",
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+ "Adverb_Noun",
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+ "Adverb_Zero",
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+ "Conj",
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+ "Conj_Conj",
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+ "DET",
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+ "Demons",
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+ "Demons_Zero",
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+ "Det",
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+ "Det_Zero",
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+ "Dup",
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+ "NAdj",
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+ "Noun_With",
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+ "Noun_With_Zero",
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+ "Noun_Without",
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+ "Noun_Zero",
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+ "PCAbl",
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+ "PCAbl_Rel",
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+ "PCAcc",
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+ "PCDat",
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+ "PCDat_Zero",
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+ "PCGen",
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+ "PCNom",
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+ "PRON",
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+ "PUNCT",
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+ "Quant",
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+ "Reflex",
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+ "Rel",
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+ "SYM",
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+ "Zero"
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+ "neg_prefix":"!",
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
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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