[paths] train = "train_docs.spacy" dev = "test_docs.spacy" raw = null init_tok2vec = null vectors = null [system] gpu_allocator = "pytorch" seed = 0 [nlp] lang = "en" pipeline = ["transformer","ner"] tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} before_creation = null after_creation = null after_pipeline_creation = null disabled = [] batch_size = 50 [components] [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 = "*" [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 = "emilyalsentzer/Bio_ClinicalBERT" [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" path = ${paths.dev} max_length = 0 gold_preproc = false limit = 0 augmenter = null [corpora.train] @readers = "spacy.Corpus.v1" path = ${paths.train} max_length = 2000 gold_preproc = false limit = 0 augmenter = null [training] train_corpus = "corpora.train" dev_corpus = "corpora.dev" seed = ${system.seed} gpu_allocator = ${system.gpu_allocator} dropout = 0.1 accumulate_gradient = 1 patience = 1600 max_epochs = 8 max_steps = 20000 eval_frequency = 200 frozen_components = [] before_to_disk = null annotating_components = [] 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 = 10 stop = 50 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 [training.optimizer.learn_rate] @schedules = "warmup_linear.v1" warmup_steps = 250 total_steps = 20000 initial_rate = 0.00005 [training.score_weights] ents_f = 1.0 ents_p = 0.0 ents_r = 0.0 ents_per_type = 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]