[paths] train = "corpus/en-core-web/train.spacy" dev = "corpus/en-core-web/dev.spacy" vectors = "corpus/en_vectors" raw = null init_tok2vec = null vocab_data = null [system] gpu_allocator = null seed = 0 [nlp] lang = "en" pipeline = ["tok2vec","tagger","parser","senter","attribute_ruler","lemmatizer","syllables","formality","readability"] disabled = ["senter"] before_creation = null after_creation = null after_pipeline_creation = null batch_size = 256 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} [components] [components.attribute_ruler] factory = "attribute_ruler" validate = false [components.formality] factory = "formality" [components.lemmatizer] factory = "lemmatizer" mode = "rule" model = null overwrite = false [components.parser] factory = "parser" learn_tokens = false min_action_freq = 30 moves = null 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.readability] factory = "readability" [components.senter] factory = "senter" [components.senter.model] @architectures = "spacy.Tagger.v1" nO = null [components.senter.model.tok2vec] @architectures = "spacy.Tok2Vec.v2" [components.senter.model.tok2vec.embed] @architectures = "spacy.MultiHashEmbed.v2" width = 16 attrs = ["NORM","PREFIX","SUFFIX","SHAPE"] rows = [1000,500,500,500] include_static_vectors = true [components.senter.model.tok2vec.encode] @architectures = "spacy.MaxoutWindowEncoder.v2" width = 16 depth = 2 window_size = 1 maxout_pieces = 2 [components.syllables] factory = "syllables" [components.tagger] factory = "tagger" [components.tagger.model] @architectures = "spacy.Tagger.v1" nO = null [components.tagger.model.tok2vec] @architectures = "spacy.Tok2VecListener.v1" width = ${components.tok2vec.model.encode:width} upstream = "tok2vec" [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"] rows = [5000,2500,2500,2500] 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" limit = 0 max_length = 0 path = ${paths:dev} gold_preproc = false augmenter = null [corpora.train] @readers = "spacy.Corpus.v1" path = ${paths:train} max_length = 5000 gold_preproc = false limit = 0 [corpora.train.augmenter] @augmenters = "spacy.orth_variants.v1" level = 0.2 lower = 0.5 [corpora.train.augmenter.orth_variants] @readers = "srsly.read_json.v1" path = "assets/orth_variants.json" [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 = 0 eval_frequency = 1000 frozen_components = [] before_to_disk = null annotating_components = [] [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.WandbLogger.v1" project_name = "spacy-v3.0.0a2" remove_config_values = [] [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] tag_acc = 0.16 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 = 0.33 ents_f = 0.33 ents_p = 0.0 ents_r = 0.0 ents_per_type = null [pretraining] [initialize] vocab_data = ${paths.vocab_data} vectors = ${paths.vectors} init_tok2vec = ${paths.init_tok2vec} before_init = null after_init = null [initialize.components] [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.components.tagger] [initialize.components.tagger.labels] @readers = "spacy.read_labels.v1" path = "corpus/labels/tagger.json" require = false [initialize.lookups] @misc = "spacy.LookupsDataLoader.v1" lang = ${nlp.lang} tables = ["lexeme_norm"] [initialize.tokenizer]