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[paths] |
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tagger_model = "models/hu_core_news_trf-tagger-3.4.0/model-best" |
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parser_model = "models/hu_core_news_trf-parser-3.4.0/model-best" |
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ner_model = "models/hu_core_news_trf-ner-3.4.0/model-best" |
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lemmatizer_lookups = "models/hu_core_news_trf-lookup-lemmatizer-3.4.0" |
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train = null |
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dev = null |
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vectors = null |
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init_tok2vec = null |
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|
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[system] |
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seed = 0 |
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gpu_allocator = null |
|
|
|
[nlp] |
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lang = "hu" |
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pipeline = ["transformer","senter","tagger","morphologizer","lookup_lemmatizer","trainable_lemmatizer","lemma_smoother","experimental_arc_predicter","experimental_arc_labeler","ner"] |
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tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} |
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disabled = [] |
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before_creation = null |
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after_creation = null |
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after_pipeline_creation = null |
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batch_size = 1000 |
|
|
|
[components] |
|
|
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[components.experimental_arc_labeler] |
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factory = "experimental_arc_labeler" |
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scorer = {"@scorers":"spacy-experimental.biaffine_parser_scorer.v1"} |
|
|
|
[components.experimental_arc_labeler.model] |
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@architectures = "spacy-experimental.Bilinear.v1" |
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hidden_width = 128 |
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mixed_precision = false |
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nO = null |
|
dropout = 0.1 |
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grad_scaler = null |
|
|
|
[components.experimental_arc_labeler.model.tok2vec] |
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@architectures = "spacy-transformers.Tok2VecTransformer.v3" |
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name = "SZTAKI-HLT/hubert-base-cc" |
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mixed_precision = false |
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pooling = {"@layers":"reduce_mean.v1"} |
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grad_factor = 1.0 |
|
|
|
[components.experimental_arc_labeler.model.tok2vec.get_spans] |
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@span_getters = "spacy-transformers.strided_spans.v1" |
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window = 128 |
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stride = 96 |
|
|
|
[components.experimental_arc_labeler.model.tok2vec.grad_scaler_config] |
|
|
|
[components.experimental_arc_labeler.model.tok2vec.tokenizer_config] |
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use_fast = true |
|
|
|
[components.experimental_arc_labeler.model.tok2vec.transformer_config] |
|
|
|
[components.experimental_arc_predicter] |
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factory = "experimental_arc_predicter" |
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scorer = {"@scorers":"spacy-experimental.biaffine_parser_scorer.v1"} |
|
|
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[components.experimental_arc_predicter.model] |
|
@architectures = "spacy-experimental.PairwiseBilinear.v1" |
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hidden_width = 256 |
|
nO = 1 |
|
mixed_precision = false |
|
dropout = 0.1 |
|
grad_scaler = null |
|
|
|
[components.experimental_arc_predicter.model.tok2vec] |
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@architectures = "spacy-transformers.Tok2VecTransformer.v3" |
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name = "SZTAKI-HLT/hubert-base-cc" |
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mixed_precision = false |
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pooling = {"@layers":"reduce_mean.v1"} |
|
grad_factor = 1.0 |
|
|
|
[components.experimental_arc_predicter.model.tok2vec.get_spans] |
|
@span_getters = "spacy-transformers.strided_spans.v1" |
|
window = 128 |
|
stride = 96 |
|
|
|
[components.experimental_arc_predicter.model.tok2vec.grad_scaler_config] |
|
|
|
[components.experimental_arc_predicter.model.tok2vec.tokenizer_config] |
|
use_fast = true |
|
|
|
[components.experimental_arc_predicter.model.tok2vec.transformer_config] |
|
|
|
[components.lemma_smoother] |
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factory = "hu.lemma_smoother" |
|
|
|
[components.lookup_lemmatizer] |
|
factory = "hu.lookup_lemmatizer" |
|
scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"} |
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source = ${paths.lemmatizer_lookups} |
|
|
|
[components.morphologizer] |
|
factory = "morphologizer" |
|
extend = false |
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overwrite = true |
|
scorer = {"@scorers":"spacy.morphologizer_scorer.v1"} |
|
|
|
[components.morphologizer.model] |
|
@architectures = "spacy.Tagger.v1" |
|
nO = null |
|
|
|
[components.morphologizer.model.tok2vec] |
|
@architectures = "spacy-transformers.TransformerListener.v1" |
|
grad_factor = 1.0 |
|
pooling = {"@layers":"reduce_mean.v1"} |
|
upstream = "*" |
|
|
|
[components.ner] |
|
factory = "beam_ner" |
|
beam_density = 0.01 |
|
beam_update_prob = 1 |
|
beam_width = 32 |
|
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 = true |
|
hidden_width = 64 |
|
maxout_pieces = 3 |
|
use_upper = false |
|
nO = null |
|
|
|
[components.ner.model.tok2vec] |
|
@architectures = "spacy-transformers.Tok2VecTransformer.v3" |
|
name = "SZTAKI-HLT/hubert-base-cc" |
|
mixed_precision = false |
|
pooling = {"@layers":"reduce_mean.v1"} |
|
grad_factor = 1.0 |
|
|
|
[components.ner.model.tok2vec.get_spans] |
|
@span_getters = "spacy-transformers.strided_spans.v1" |
|
window = 128 |
|
stride = 96 |
|
|
|
[components.ner.model.tok2vec.grad_scaler_config] |
|
|
|
[components.ner.model.tok2vec.tokenizer_config] |
|
use_fast = true |
|
|
|
[components.ner.model.tok2vec.transformer_config] |
|
|
|
[components.senter] |
|
factory = "senter" |
|
overwrite = false |
|
scorer = {"@scorers":"spacy.senter_scorer.v1"} |
|
|
|
[components.senter.model] |
|
@architectures = "spacy.Tagger.v1" |
|
nO = null |
|
|
|
[components.senter.model.tok2vec] |
|
@architectures = "spacy-transformers.TransformerListener.v1" |
|
grad_factor = 1.0 |
|
upstream = "transformer" |
|
pooling = {"@layers":"reduce_mean.v1"} |
|
|
|
[components.tagger] |
|
factory = "tagger" |
|
neg_prefix = "!" |
|
overwrite = false |
|
scorer = {"@scorers":"spacy.tagger_scorer.v1"} |
|
|
|
[components.tagger.model] |
|
@architectures = "spacy.Tagger.v1" |
|
nO = null |
|
|
|
[components.tagger.model.tok2vec] |
|
@architectures = "spacy-transformers.TransformerListener.v1" |
|
grad_factor = 1.0 |
|
pooling = {"@layers":"reduce_mean.v1"} |
|
upstream = "*" |
|
|
|
[components.trainable_lemmatizer] |
|
factory = "trainable_lemmatizer_v2" |
|
backoff = "orth" |
|
min_tree_freq = 1 |
|
overwrite = false |
|
overwrite_labels = true |
|
scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"} |
|
top_k = 3 |
|
|
|
[components.trainable_lemmatizer.model] |
|
@architectures = "spacy.Tagger.v1" |
|
nO = null |
|
|
|
[components.trainable_lemmatizer.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.v3" |
|
name = "SZTAKI-HLT/hubert-base-cc" |
|
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 |
|
|
|
[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] |
|
sents_f = 0.2 |
|
sents_p = 0.0 |
|
sents_r = 0.0 |
|
tag_acc = 0.2 |
|
pos_acc = 0.1 |
|
morph_acc = 0.1 |
|
morph_per_feat = null |
|
lemma_acc = 0.2 |
|
ents_f = 0.2 |
|
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] |