de_ggponc_medbertde / config.cfg
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[paths]
base = "../data/ggponc_spacy_up"
vectors = null
init_tok2vec = null
train = null
dev = null
[system]
gpu_allocator = "pytorch"
seed = 0
[nlp]
lang = "de"
pipeline = ["transformer","morphologizer","parser","transformer_spancat","spancat"]
batch_size = 1000
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
[components]
[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
upstream = "transformer"
pooling = {"@layers":"reduce_mean.v1"}
[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 = 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.spancat]
factory = "spancat"
max_positive = 1
scorer = {"@scorers":"phlobo.flat_scorer"}
spans_key = "entities"
threshold = 0.25
[components.spancat.model]
@architectures = "spacy.SpanCategorizer.v1"
[components.spancat.model.reducer]
@layers = "spacy.mean_max_reducer.v1"
hidden_size = 128
[components.spancat.model.scorer]
@layers = "spacy.LinearLogistic.v1"
nO = null
nI = null
[components.spancat.model.tok2vec]
@architectures = "spacy-transformers.TransformerListener.v1"
grad_factor = 1.0
pooling = {"@layers":"reduce_mean.v1"}
upstream = "transformer_spancat"
[components.spancat.suggester]
@misc = "phlobo.chunk_and_ngram_suggester"
max_depth = 5
sizes = [1,2,3,4,5,6,7,8]
[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 = "bert-base-german-cased"
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]
[components.transformer_spancat]
factory = "transformer"
max_batch_items = 4096
set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
[components.transformer_spancat.model]
@architectures = "spacy-transformers.TransformerModel.v3"
name = "GerMedBERT/medbert-512"
mixed_precision = true
[components.transformer_spancat.model.get_spans]
@span_getters = "spacy-transformers.strided_spans.v1"
window = 128
stride = 96
[components.transformer_spancat.model.grad_scaler_config]
[components.transformer_spancat.model.tokenizer_config]
use_fast = true
[components.transformer_spancat.model.transformer_config]
[corpora]
[corpora.dev]
@readers = "spacy.Corpus.v1"
path = ${paths.base}/validation.spacy
max_length = 0
gold_preproc = false
limit = 0
augmenter = null
[corpora.train]
@readers = "spacy.Corpus.v1"
path = ${paths.base}/train.spacy
max_length = 0
gold_preproc = false
limit = 0
augmenter = null
[training]
accumulate_gradient = 3
dev_corpus = "corpora.dev"
train_corpus = "corpora.train"
seed = ${system.seed}
gpu_allocator = ${system.gpu_allocator}
dropout = 0.1
patience = 3200
max_epochs = 100
max_steps = 40000
eval_frequency = 100
frozen_components = ["transformer","morphologizer","parser"]
annotating_components = ["transformer","morphologizer","parser"]
before_to_disk = null
[training.batcher]
@batchers = "spacy.batch_by_padded.v1"
discard_oversize = true
size = 2000
buffer = 256
get_length = null
[training.logger]
@loggers = "spacy.WandbLogger.v3"
project_name = "ggponc"
remove_config_values = []
run_name = "2023-12-27_18-02-08-cuda-4"
model_log_interval = null
log_dataset_dir = null
entity = null
[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 = 40000
initial_rate = 0.000025
[training.score_weights]
pos_acc = null
morph_acc = null
morph_per_feat = null
dep_uas = null
dep_las = null
dep_las_per_type = null
sents_p = null
sents_r = null
sents_f = null
spans_sc_f = null
spans_sc_p = null
spans_sc_r = null
tag_acc = null
spans_entities_f = 1.0
spans_entities_p = 0.0
spans_entities_r = 0.0
Diagnosis_or_Pathology_f = null
Other_Finding_f = null
Clinical_Drug_f = null
Nutrient_or_Body_Substance_f = 0.0
External_Substance_f = 0.0
Therapeutic_f = null
Diagnostic_f = 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]