[paths] train = "drive/MyDrive/ARCHES/TAL/donnees/pretraitement/modele_segmentation/extraction_wavestone/spacy/train.spacy" dev = "drive/MyDrive/ARCHES/TAL/donnees/pretraitement/modele_segmentation/extraction_wavestone/spacy/dev.spacy" vectors = null init_tok2vec = null [system] gpu_allocator = "pytorch" seed = 0 [nlp] lang = "fr" pipeline = ["preprocess_text","senter"] batch_size = 128 disabled = [] before_creation = null after_creation = null after_pipeline_creation = null tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} [components] [components.preprocess_text] factory = "preprocess_text" [components.senter] factory = "senter" overwrite = false scorer = {"@scorers":"spacy.senter_scorer.v1"} [components.senter.model] @architectures = "spacy.Tagger.v2" nO = null normalize = false [components.senter.model.tok2vec] @architectures = "spacy.HashEmbedCNN.v2" pretrained_vectors = null width = 12 depth = 1 embed_size = 2000 window_size = 1 maxout_pieces = 2 subword_features = true [corpora] [corpora.dev] @readers = "spacy.Corpus.v1" path = ${paths.dev} max_length = 0 gold_preproc = false limit = 0 augmenter = null [corpora.train] @readers = "spacy.Corpus.v1" path = ${paths.train} 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 = 1600 max_epochs = 0 max_steps = 20000 eval_frequency = 200 frozen_components = [] annotating_components = [] before_to_disk = null before_update = null [training.batcher] @batchers = "spacy.batch_by_padded.v1" discard_oversize = true size = 2000 buffer = 256 get_length = null [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 [training.optimizer.learn_rate] @schedules = "warmup_linear.v1" warmup_steps = 250 total_steps = 20000 initial_rate = 0.00005 [training.score_weights] sents_f = 1.0 sents_p = 0.0 sents_r = 0.0 [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]