[paths] train = "corpus/da-core-news/train.spacy" dev = "corpus/da-core-news/dev.spacy" vectors = null raw = null init_tok2vec = null vocab_data = null [system] gpu_allocator = "pytorch" seed = 1 [nlp] lang = "da" pipeline = ["transformer","morphologizer","parser","attribute_ruler","lemmatizer","ner"] disabled = [] before_creation = null after_creation = null after_pipeline_creation = null batch_size = 64 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} [components] [components.attribute_ruler] factory = "attribute_ruler" validate = false [components.lemmatizer] factory = "lemmatizer" mode = "lookup" model = null overwrite = false [components.morphologizer] factory = "morphologizer" [components.morphologizer.model] @architectures = "spacy.Tagger.v1" nO = null [components.morphologizer.model.tok2vec] @architectures = "spacy-transformers.TransformerListener.v1" grad_factor = 1.0 upstream = "transformer" pooling = {"@layers":"reduce_mean.v1"} [components.ner] factory = "ner" incorrect_spans_key = null moves = null 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 = false nO = null [components.ner.model.tok2vec] @architectures = "spacy-transformers.TransformerListener.v1" grad_factor = 1.0 upstream = "transformer" pooling = {"@layers":"reduce_mean.v1"} [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 = false nO = null [components.parser.model.tok2vec] @architectures = "spacy-transformers.TransformerListener.v1" grad_factor = 1.0 upstream = "transformer" pooling = {"@layers":"reduce_mean.v1"} [components.transformer] factory = "transformer" max_batch_items = 4096 set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"} [components.transformer.model] @architectures = "spacy-transformers.TransformerModel.v1" name = "Maltehb/danish-bert-botxo" [components.transformer.model.get_spans] @span_getters = "spacy-transformers.strided_spans.v1" window = 128 stride = 96 [components.transformer.model.tokenizer_config] use_fast = true [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 = 500 gold_preproc = false limit = 0 [corpora.train.augmenter] @augmenters = "spacy.lower_case.v1" level = 0.1 [training] train_corpus = "corpora.train" dev_corpus = "corpora.dev" seed = ${system:seed} gpu_allocator = ${system:gpu_allocator} dropout = 0.1 accumulate_gradient = 3 patience = 5000 max_epochs = 0 max_steps = 20000 eval_frequency = 1000 frozen_components = [] before_to_disk = null annotating_components = [] [training.batcher] @batchers = "spacy.batch_by_padded.v1" discard_oversize = true get_length = null size = 2000 buffer = 256 [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 [training.optimizer.learn_rate] @schedules = "warmup_linear.v1" warmup_steps = 250 total_steps = 20000 initial_rate = 0.00005 [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 [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.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 = ["lexeme_norm"] [initialize.tokenizer]