| [paths] | |
| vectors = "output/en_core_sci_md_vectors" | |
| init_tok2vec = null | |
| parser_tagger_path = "output/en_core_sci_md_parser_tagger/model-best" | |
| dev_path = "assets/BC5CDR-IOB/devel.tsv" | |
| train_path = "assets/BC5CDR-IOB/train.tsv" | |
| vocab_path = "project_data/vocab_md.jsonl" | |
| train = null | |
| dev = null | |
| [system] | |
| gpu_allocator = null | |
| seed = 0 | |
| [nlp] | |
| lang = "en" | |
| pipeline = ["tok2vec","tagger","attribute_ruler","lemmatizer","parser","ner"] | |
| tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} | |
| disabled = [] | |
| before_creation = null | |
| after_creation = null | |
| after_pipeline_creation = null | |
| batch_size = 1000 | |
| [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.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 = 128 | |
| maxout_pieces = 3 | |
| 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","SPACY"] | |
| rows = [5000,2500,2500,2500,100] | |
| include_static_vectors = ${vars.include_static_vectors} | |
| [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 = 128 | |
| maxout_pieces = 3 | |
| use_upper = true | |
| nO = null | |
| [components.parser.model.tok2vec] | |
| @architectures = "spacy.Tok2VecListener.v1" | |
| width = 96 | |
| upstream = "*" | |
| [components.tagger] | |
| factory = "tagger" | |
| neg_prefix = "!" | |
| overwrite = false | |
| scorer = {"@scorers":"spacy.tagger_scorer.v1"} | |
| [components.tagger.model] | |
| @architectures = "spacy.Tagger.v2" | |
| nO = null | |
| normalize = "False" | |
| [components.tagger.model.tok2vec] | |
| @architectures = "spacy.Tok2VecListener.v1" | |
| width = 96 | |
| upstream = "*" | |
| [components.tok2vec] | |
| factory = "tok2vec" | |
| [components.tok2vec.model] | |
| @architectures = "spacy.Tok2Vec.v2" | |
| [components.tok2vec.model.embed] | |
| @architectures = "spacy.MultiHashEmbed.v2" | |
| width = 96 | |
| attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"] | |
| rows = [5000,2500,2500,2500,100] | |
| 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 = "specialized_ner_reader" | |
| file_path = ${paths.dev_path} | |
| [corpora.train] | |
| @readers = "specialized_ner_reader" | |
| file_path = ${paths.train_path} | |
| [training] | |
| dev_corpus = "corpora.dev" | |
| train_corpus = "corpora.train" | |
| seed = ${system.seed} | |
| gpu_allocator = ${system.gpu_allocator} | |
| dropout = 0.1 | |
| accumulate_gradient = 1 | |
| patience = 0 | |
| max_epochs = 7 | |
| max_steps = 0 | |
| eval_frequency = 500 | |
| frozen_components = ["tok2vec","parser","tagger","attribute_ruler","lemmatizer"] | |
| before_to_disk = null | |
| annotating_components = [] | |
| [training.batcher] | |
| @batchers = "spacy.batch_by_sequence.v1" | |
| get_length = null | |
| [training.batcher.size] | |
| @schedules = "compounding.v1" | |
| start = 1 | |
| stop = 32 | |
| compound = 1.001 | |
| t = 0.0 | |
| [training.logger] | |
| @loggers = "spacy.ConsoleLogger.v1" | |
| progress_bar = true | |
| [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 = false | |
| eps = 0.00000001 | |
| learn_rate = 0.001 | |
| [training.score_weights] | |
| tag_acc = null | |
| lemma_acc = 0.5 | |
| dep_uas = null | |
| dep_las = null | |
| dep_las_per_type = null | |
| sents_p = null | |
| sents_r = null | |
| sents_f = null | |
| ents_f = 0.5 | |
| ents_p = 0.0 | |
| ents_r = 0.0 | |
| ents_per_type = null | |
| [pretraining] | |
| [initialize] | |
| vectors = ${paths.vectors} | |
| init_tok2vec = ${paths.init_tok2vec} | |
| vocab_data = ${paths.vocab_path} | |
| lookups = null | |
| before_init = {"@callbacks":"replace_tokenizer"} | |
| after_init = null | |
| [initialize.components] | |
| [initialize.tokenizer] | |
| [vars] | |
| include_static_vectors = "True" |