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spaCy-roberta-workout-entity-model

Token Classification
Transformers
English
roberta
ner
entity-extraction
workout
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spaCy-roberta-workout-entity-model
File size: 2,846 Bytes 
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[paths]
train = "voice_assistant/data/entity_data/train.spacy"
dev = "voice_assistant/data/entity_data/dev.spacy"
vectors = null
init_tok2vec = null

[system]
seed = 42
gpu_allocator = "pytorch"

[nlp]
lang = "en"
pipeline = ["transformer","ner"]
batch_size = 16
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
vectors = {"@vectors":"spacy.Vectors.v1"}

[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 = 128
maxout_pieces = 2
use_upper = false
nO = null

[components.ner.model.tok2vec]
@architectures = "spacy-transformers.TransformerListener.v1"
upstream = "transformer"
pooling = {"@layers":"reduce_mean.v1"}
grad_factor = 1.0

[components.transformer]
factory = "transformer"
max_batch_items = 1024
set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}

[components.transformer.model]
@architectures = "spacy-transformers.TransformerModel.v3"
name = "roberta-base"
get_spans = {"@span_getters":"spacy-transformers.doc_spans.v1"}
mixed_precision = true

[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]
train_corpus = "corpora.train"
dev_corpus = "corpora.dev"
seed = 42
gpu_allocator = "pytorch"
dropout = 0.15
max_epochs = 600
patience = 300
eval_frequency = 200
accumulate_gradient = 1
max_steps = 6000
frozen_components = []
annotating_components = []
before_to_disk = null
before_update = null

[training.batcher]
@batchers = "spacy.batch_by_words.v1"
discard_oversize = true
tolerance = 0.2
size = 2048
get_length = null

[training.logger]
@loggers = "spacy.MLflowLogger.v1"
run_id = null
experiment_id = null
run_name = null
nested = false
tags = null
remove_config_values = []

[training.optimizer]
@optimizers = "Adam.v1"
learn_rate = 0.0001
L2_is_weight_decay = true
L2 = 0.01
grad_clip = 1.0
beta1 = 0.9
beta2 = 0.999
eps = 0.00000001
use_averages = false

[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]