| [paths] | |
| train = null | |
| dev = null | |
| init_tok2vec = null | |
| vectors = null | |
| model_source = "training/da_dacy_large_trf/model-last" | |
| [system] | |
| gpu_allocator = "pytorch" | |
| seed = 0 | |
| [nlp] | |
| lang = "da" | |
| pipeline = ["transformer","tagger","morphologizer","trainable_lemmatizer","parser","ner","coref","span_resolver","span_cleaner","entity_linker"] | |
| batch_size = 512 | |
| disabled = [] | |
| before_creation = null | |
| after_creation = null | |
| after_pipeline_creation = null | |
| tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} | |
| [components] | |
| [components.coref] | |
| factory = "experimental_coref" | |
| span_cluster_prefix = "coref_head_clusters" | |
| [components.coref.model] | |
| @architectures = "spacy-experimental.Coref.v1" | |
| distance_embedding_size = 20 | |
| dropout = 0.3 | |
| hidden_size = 1024 | |
| depth = 2 | |
| antecedent_limit = 100 | |
| antecedent_batch_size = 512 | |
| [components.coref.model.tok2vec] | |
| @architectures = "spacy-transformers.TransformerListener.v1" | |
| grad_factor = 0.5 | |
| upstream = "transformer" | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| [components.coref.scorer] | |
| @scorers = "spacy-experimental.coref_scorer.v1" | |
| span_cluster_prefix = "coref_head_clusters" | |
| [components.entity_linker] | |
| factory = "entity_linker" | |
| candidates_batch_size = 1 | |
| entity_vector_length = 768 | |
| generate_empty_kb = {"@misc":"spacy.EmptyKB.v2"} | |
| get_candidates = {"@misc":"spacy.CandidateGenerator.v1"} | |
| get_candidates_batch = {"@misc":"spacy.CandidateBatchGenerator.v1"} | |
| incl_context = true | |
| incl_prior = true | |
| labels_discard = [] | |
| n_sents = 0 | |
| overwrite = true | |
| scorer = {"@scorers":"spacy.entity_linker_scorer.v1"} | |
| threshold = null | |
| use_gold_ents = true | |
| [components.entity_linker.model] | |
| @architectures = "spacy.EntityLinker.v2" | |
| nO = null | |
| [components.entity_linker.model.tok2vec] | |
| @architectures = "spacy.HashEmbedCNN.v2" | |
| pretrained_vectors = null | |
| width = 96 | |
| depth = 2 | |
| embed_size = 2000 | |
| window_size = 1 | |
| maxout_pieces = 3 | |
| subword_features = true | |
| [components.morphologizer] | |
| factory = "morphologizer" | |
| extend = false | |
| 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-transformers.TransformerListener.v1" | |
| grad_factor = 1.0 | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| upstream = "transformer" | |
| [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 = false | |
| nO = null | |
| [components.ner.model.tok2vec] | |
| @architectures = "spacy-transformers.TransformerListener.v1" | |
| grad_factor = 1.0 | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| upstream = "transformer" | |
| [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 = false | |
| nO = null | |
| [components.parser.model.tok2vec] | |
| @architectures = "spacy-transformers.TransformerListener.v1" | |
| grad_factor = 1.0 | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| upstream = "transformer" | |
| [components.span_cleaner] | |
| factory = "experimental_span_cleaner" | |
| prefix = "coref_head_clusters" | |
| [components.span_resolver] | |
| factory = "experimental_span_resolver" | |
| input_prefix = "coref_head_clusters" | |
| output_prefix = "coref_clusters" | |
| [components.span_resolver.model] | |
| @architectures = "spacy-experimental.SpanResolver.v1" | |
| hidden_size = 1024 | |
| distance_embedding_size = 64 | |
| conv_channels = 4 | |
| window_size = 1 | |
| max_distance = 128 | |
| prefix = "coref_head_clusters" | |
| [components.span_resolver.model.tok2vec] | |
| @architectures = "spacy-transformers.TransformerListener.v1" | |
| grad_factor = 0.0 | |
| upstream = "transformer" | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| [components.span_resolver.scorer] | |
| @scorers = "spacy-experimental.span_resolver_scorer.v1" | |
| input_prefix = "coref_head_clusters" | |
| output_prefix = "coref_clusters" | |
| [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-transformers.TransformerListener.v1" | |
| grad_factor = 1.0 | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| upstream = "transformer" | |
| [components.trainable_lemmatizer] | |
| factory = "trainable_lemmatizer" | |
| backoff = "orth" | |
| min_tree_freq = 3 | |
| overwrite = false | |
| scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"} | |
| top_k = 1 | |
| [components.trainable_lemmatizer.model] | |
| @architectures = "spacy.Tagger.v2" | |
| nO = null | |
| normalize = false | |
| [components.trainable_lemmatizer.model.tok2vec] | |
| @architectures = "spacy-transformers.TransformerListener.v1" | |
| grad_factor = 1.0 | |
| pooling = {"@layers":"reduce_mean.v1"} | |
| upstream = "transformer" | |
| [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.v3" | |
| name = "chcaa/dfm-encoder-large-v1" | |
| mixed_precision = false | |
| [components.transformer.model.get_spans] | |
| @span_getters = "spacy-transformers.strided_spans.v1" | |
| window = 400 | |
| stride = 350 | |
| [components.transformer.model.grad_scaler_config] | |
| [components.transformer.model.tokenizer_config] | |
| use_fast = true | |
| [components.transformer.model.transformer_config] | |
| [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] | |
| seed = ${system.seed} | |
| gpu_allocator = ${system.gpu_allocator} | |
| dropout = 0.1 | |
| accumulate_gradient = 1 | |
| patience = 1600 | |
| max_epochs = 0 | |
| max_steps = 20000 | |
| eval_frequency = 200 | |
| frozen_components = [] | |
| annotating_components = [] | |
| dev_corpus = "corpora.dev" | |
| train_corpus = "corpora.train" | |
| before_to_disk = null | |
| 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 = false | |
| eps = 0.00000001 | |
| learn_rate = 0.001 | |
| [training.score_weights] | |
| tag_acc = 0.12 | |
| pos_acc = 0.06 | |
| morph_acc = 0.06 | |
| morph_per_feat = null | |
| lemma_acc = 0.12 | |
| dep_uas = 0.06 | |
| dep_las = 0.06 | |
| dep_las_per_type = null | |
| sents_p = null | |
| sents_r = null | |
| sents_f = 0.0 | |
| ents_f = 0.12 | |
| ents_p = 0.0 | |
| ents_r = 0.0 | |
| ents_per_type = null | |
| coref_f = 0.12 | |
| coref_p = null | |
| coref_r = null | |
| span_accuracy = 0.12 | |
| nel_micro_f = 0.12 | |
| nel_micro_r = null | |
| nel_micro_p = null | |
| [pretraining] | |
| [initialize] | |
| vectors = ${paths.vectors} | |
| init_tok2vec = ${paths.init_tok2vec} | |
| vocab_data = null | |
| lookups = null | |
| before_init = null | |
| after_init = null | |
| [initialize.components] | |
| [initialize.tokenizer] |