[paths] train = null dev = null vectors = null init_tok2vec = null [system] gpu_allocator = null seed = 0 [nlp] lang = "es" pipeline = ["tok2vec","morphologizer","parser","senter","attribute_ruler","lemmatizer","ner"] disabled = ["senter"] before_creation = null after_creation = null after_pipeline_creation = null batch_size = 256 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} vectors = {"@vectors":"spacy.Vectors.v1"} [components] [components.attribute_ruler] factory = "attribute_ruler" scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"} validate = false [components.lemmatizer] factory = "lemmatizer" mode = "rule" model = null overwrite = false scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"} [components.morphologizer] factory = "morphologizer" extend = false label_smoothing = 0.0 overwrite = true scorer = {"@scorers":"spacy.morphologizer_scorer.v1"} [components.morphologizer.model] @architectures = "spacy.Tagger.v2" nO = null normalize = false [components.morphologizer.model.tok2vec] @architectures = "spacy.Tok2VecListener.v1" width = ${components.tok2vec.model.encode:width} upstream = "tok2vec" [components.ner] factory = "ner" incorrect_spans_key = null moves = null scorer = {"@scorers":"spacy.ner_scorer.v1"} update_with_oracle_cut_size = 100 [components.ner.model] @architectures = "spacy.TransitionBasedParser.v2" state_type = "ner" extra_state_tokens = false hidden_width = 64 maxout_pieces = 2 use_upper = true nO = null [components.ner.model.tok2vec] @architectures = "spacy.Tok2Vec.v2" [components.ner.model.tok2vec.embed] @architectures = "spacy.MultiHashEmbed.v2" width = 96 attrs = ["NORM","PREFIX","SUFFIX","SHAPE"] rows = [5000,1000,2500,2500] include_static_vectors = true [components.ner.model.tok2vec.encode] @architectures = "spacy.MaxoutWindowEncoder.v2" width = 96 depth = 4 window_size = 1 maxout_pieces = 3 [components.parser] factory = "parser" learn_tokens = false min_action_freq = 30 moves = null scorer = {"@scorers":"spacy.parser_scorer.v1"} update_with_oracle_cut_size = 100 [components.parser.model] @architectures = "spacy.TransitionBasedParser.v2" state_type = "parser" extra_state_tokens = false hidden_width = 64 maxout_pieces = 2 use_upper = true nO = null [components.parser.model.tok2vec] @architectures = "spacy.Tok2VecListener.v1" width = ${components.tok2vec.model.encode:width} upstream = "tok2vec" [components.senter] factory = "senter" overwrite = false scorer = {"@scorers":"spacy.senter_scorer.v1"} [components.senter.model] @architectures = "spacy.Tagger.v2" nO = null normalize = false [components.senter.model.tok2vec] @architectures = "spacy.Tok2Vec.v2" [components.senter.model.tok2vec.embed] @architectures = "spacy.MultiHashEmbed.v2" width = 16 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"] rows = [1000,500,500,500,50] include_static_vectors = true [components.senter.model.tok2vec.encode] @architectures = "spacy.MaxoutWindowEncoder.v2" width = 16 depth = 2 window_size = 1 maxout_pieces = 2 [components.tok2vec] factory = "tok2vec" [components.tok2vec.model] @architectures = "spacy.Tok2Vec.v2" [components.tok2vec.model.embed] @architectures = "spacy.MultiHashEmbed.v2" width = ${components.tok2vec.model.encode:width} attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"] rows = [5000,1000,2500,2500,50,50] include_static_vectors = true [components.tok2vec.model.encode] @architectures = "spacy.MaxoutWindowEncoder.v2" width = 96 depth = 4 window_size = 1 maxout_pieces = 3 [corpora] [corpora.dev] @readers = "spacy.Corpus.v1" path = ${paths.dev} gold_preproc = false max_length = 0 limit = 0 augmenter = null [corpora.train] @readers = "spacy.Corpus.v1" path = ${paths.train} gold_preproc = false max_length = 0 limit = 0 augmenter = null [training] train_corpus = "corpora.train" dev_corpus = "corpora.dev" seed = ${system:seed} gpu_allocator = ${system:gpu_allocator} dropout = 0.1 accumulate_gradient = 1 patience = 5000 max_epochs = 0 max_steps = 100000 eval_frequency = 1000 frozen_components = [] before_to_disk = null annotating_components = [] before_update = null [training.batcher] @batchers = "spacy.batch_by_words.v1" discard_oversize = false tolerance = 0.2 get_length = null [training.batcher.size] @schedules = "compounding.v1" start = 100 stop = 1000 compound = 1.001 t = 0.0 [training.logger] @loggers = "spacy.ConsoleLogger.v1" progress_bar = false [training.optimizer] @optimizers = "Adam.v1" beta1 = 0.9 beta2 = 0.999 L2_is_weight_decay = true L2 = 0.01 grad_clip = 1.0 use_averages = true eps = 0.00000001 learn_rate = 0.001 [training.score_weights] pos_acc = 0.08 morph_acc = 0.08 morph_per_feat = null dep_uas = 0.0 dep_las = 0.16 dep_las_per_type = null sents_p = null sents_r = null sents_f = 0.02 lemma_acc = 0.5 ents_f = 0.16 ents_p = 0.0 ents_r = 0.0 ents_per_type = null speed = 0.0 [pretraining] [initialize] vocab_data = null vectors = ${paths.vectors} init_tok2vec = ${paths.init_tok2vec} before_init = null after_init = null [initialize.components] [initialize.components.morphologizer] [initialize.components.morphologizer.labels] @readers = "spacy.read_labels.v1" path = "corpus/labels/morphologizer.json" require = false [initialize.components.ner] [initialize.components.ner.labels] @readers = "spacy.read_labels.v1" path = "corpus/labels/ner.json" require = false [initialize.components.parser] [initialize.components.parser.labels] @readers = "spacy.read_labels.v1" path = "corpus/labels/parser.json" require = false [initialize.lookups] @misc = "spacy.LookupsDataLoader.v1" lang = ${nlp.lang} tables = [] [initialize.tokenizer]