| [paths] |
| train = "/home/daza/ids-projects/DeReKo/spacy_train/spacy_bin_corpora/Tiger.NewOrth.train.spacy" |
| dev = "/home/daza/ids-projects/DeReKo/spacy_train/spacy_bin_corpora/Tiger.NewOrth.test.spacy" |
| vectors = null |
| init_tok2vec = null |
| |
| [system] |
| gpu_allocator = "pytorch" |
| seed = 0 |
| |
| [nlp] |
| lang = "de" |
| pipeline = ["transformer","tagger"] |
| tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"} |
| disabled = [] |
| before_creation = null |
| after_creation = null |
| after_pipeline_creation = null |
| |
| [components] |
| |
| [components.tagger] |
| factory = "tagger" |
| |
| [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"} |
| |
| [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.v1" |
| name = "bert-base-german-cased" |
| |
| [components.transformer.model.get_spans] |
| @span_getters = "spacy-transformers.strided_spans.v1" |
| window = 128 |
| stride = 96 |
| |
| [components.transformer.model.tokenizer_config] |
| use_fast = 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 = 500 |
| 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 = [] |
| before_to_disk = 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] |
| tag_acc = 1.0 |
| |
| [pretraining] |
| |
| [initialize] |
| vectors = null |
| init_tok2vec = ${paths.init_tok2vec} |
| vocab_data = null |
| lookups = null |
| |
| [initialize.components] |
| |
| [initialize.tokenizer] |