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[paths] |
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train = "./realec/train.spacy" |
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dev = "./realec/dev.spacy" |
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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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gpu_allocator = "pytorch" |
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seed = 0 |
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|
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[nlp] |
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lang = "en" |
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pipeline = ["transformer","spancat"] |
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batch_size = 16 |
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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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|
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[components] |
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|
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[components.spancat] |
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factory = "spancat" |
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max_positive = null |
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scorer = {"@scorers":"spacy.spancat_scorer.v1"} |
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spans_key = "errors" |
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threshold = 0.5 |
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|
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[components.spancat.model] |
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@architectures = "spacy.SpanCategorizer.v1" |
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|
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[components.spancat.model.reducer] |
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@layers = "spacy.mean_max_reducer.v1" |
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hidden_size = 128 |
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|
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[components.spancat.model.scorer] |
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@layers = "spacy.LinearLogistic.v1" |
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nO = null |
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nI = null |
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|
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[components.spancat.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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|
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[components.spancat.suggester] |
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@misc = "spacy.ngram_suggester.v1" |
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sizes = [1,2,3] |
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|
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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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|
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[components.transformer.model] |
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@architectures = "spacy-transformers.TransformerModel.v3" |
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name = "bert-base-cased" |
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mixed_precision = false |
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|
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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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|
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[components.transformer.model.grad_scaler_config] |
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|
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[components.transformer.model.tokenizer_config] |
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use_fast = true |
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|
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[components.transformer.model.transformer_config] |
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|
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[corpora] |
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|
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[corpora.dev] |
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@readers = "spacy.Corpus.v1" |
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path = "./realec/dev.spacy" |
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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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|
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[corpora.train] |
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@readers = "spacy.Corpus.v1" |
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path = "./realec/train.spacy" |
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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 = 0 |
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gpu_allocator = "pytorch" |
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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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|
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[training.logger] |
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@loggers = "spacy.WandbLogger.v3" |
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project_name = "my-awesome-project" |
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remove_config_values = ["paths.train","paths.dev","corpora.train.path","corpora.dev.path"] |
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log_dataset_dir = null |
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entity = null |
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run_name = "grammar-checker" |
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model_log_interval = null |
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|
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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 |
|
total_steps = 20000 |
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initial_rate = 0.00005 |
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|
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[training.score_weights] |
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spans_sc_f = 0.5 |
|
spans_sc_p = 0.0 |
|
spans_sc_r = 0.0 |
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spans_Agreement_errors_f = 0.06 |
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spans_Articles_f = 0.03 |
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spans_Capitalisation_f = 0.05 |
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spans_Formational_affixes_f = 0.1 |
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spans_Noun_number_f = 0.04 |
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spans_Numerals_f = 0.06 |
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spans_Prepositions_f = 0.05 |
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spans_Punctuation_f = 0.03 |
|
spans_Spelling_f = 0.02 |
|
spans_Tense_choice_f = 0.03 |
|
spans_lex_item_choice_f = 0.03 |
|
|
|
[pretraining] |
|
|
|
[initialize] |
|
vectors = null |
|
init_tok2vec = null |
|
vocab_data = null |
|
lookups = null |
|
before_init = null |
|
after_init = null |
|
|
|
[initialize.components] |
|
|
|
[initialize.tokenizer] |