| [paths] |
| train = null |
| dev = null |
| init_tok2vec = null |
| vectors = null |
| model_source = "training/da_dacy_small_trf2/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 = "jonfd/electra-small-nordic" |
| mixed_precision = false |
|
|
| [components.transformer.model.get_spans] |
| @span_getters = "spacy-transformers.strided_spans.v1" |
| window = 128 |
| stride = 96 |
|
|
| [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] |
