152 lines
3.0 KiB
INI
152 lines
3.0 KiB
INI
[paths]
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train = "./train.spacy"
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dev = "./valid.spacy"
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vectors = null
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init_tok2vec = null
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[system]
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gpu_allocator = "pytorch"
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seed = 0
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[nlp]
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lang = "en"
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pipeline = ["transformer","ner"]
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batch_size = 128
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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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tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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[components]
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[components.ner]
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factory = "ner"
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incorrect_spans_key = null
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moves = null
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scorer = {"@scorers":"spacy.ner_scorer.v1"}
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update_with_oracle_cut_size = 100
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[components.ner.model]
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@architectures = "spacy.TransitionBasedParser.v2"
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state_type = "ner"
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extra_state_tokens = false
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hidden_width = 64
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maxout_pieces = 2
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use_upper = false
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nO = null
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[components.ner.model.tok2vec]
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@architectures = "spacy-transformers.TransformerListener.v1"
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grad_factor = 1.0
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pooling = {"@layers":"reduce_mean.v1"}
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upstream = "*"
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[components.transformer]
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factory = "transformer"
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max_batch_items = 4096
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set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
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[components.transformer.model]
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@architectures = "spacy-transformers.TransformerModel.v3"
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name = "roberta-base"
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mixed_precision = false
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[components.transformer.model.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
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[components.transformer.model.grad_scaler_config]
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[components.transformer.model.tokenizer_config]
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use_fast = true
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[components.transformer.model.transformer_config]
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[corpora]
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[corpora.dev]
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@readers = "spacy.Corpus.v1"
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path = ${paths.dev}
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max_length = 0
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gold_preproc = false
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limit = 0
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augmenter = null
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[corpora.train]
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@readers = "spacy.Corpus.v1"
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path = ${paths.train}
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max_length = 0
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gold_preproc = false
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limit = 0
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augmenter = null
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[training]
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accumulate_gradient = 3
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dev_corpus = "corpora.dev"
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train_corpus = "corpora.train"
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seed = ${system.seed}
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gpu_allocator = ${system.gpu_allocator}
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dropout = 0.1
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patience = 1600
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max_epochs = 0
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max_steps = 20000
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eval_frequency = 200
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frozen_components = []
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annotating_components = []
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before_to_disk = null
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[training.batcher]
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@batchers = "spacy.batch_by_padded.v1"
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discard_oversize = true
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size = 2000
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buffer = 256
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get_length = null
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[training.logger]
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@loggers = "spacy.WandbLogger.v4"
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project_name = "entity_extraction_new"
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remove_config_values = ["paths.train","paths.dev","corpora.train.path","corpora.dev.path"]
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model_log_interval = 1000
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run_name = "'entity_extraction_train'"
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log_dataset_dir = null
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entity = null
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log_best_dir = null
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log_latest_dir = null
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[training.optimizer]
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@optimizers = "Adam.v1"
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beta1 = 0.9
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beta2 = 0.999
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L2_is_weight_decay = true
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L2 = 0.01
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grad_clip = 1.0
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use_averages = false
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eps = 0.00000001
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[training.optimizer.learn_rate]
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@schedules = "warmup_linear.v1"
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warmup_steps = 250
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total_steps = 20000
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initial_rate = 0.00005
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[training.score_weights]
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ents_f = 1.0
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ents_p = 0.0
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ents_r = 0.0
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ents_per_type = null
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[pretraining]
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[initialize]
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vectors = ${paths.vectors}
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init_tok2vec = ${paths.init_tok2vec}
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vocab_data = null
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lookups = null
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before_init = null
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after_init = null
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[initialize.components]
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[initialize.tokenizer] |