83 lines
1.6 KiB
INI
83 lines
1.6 KiB
INI
# This is an auto-generated partial config. To use it with 'spacy train'
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# you can run spacy init fill-config to auto-fill all default settings:
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# python -m spacy init fill-config ./base_config.cfg ./config.cfg
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[paths]
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train = null
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dev = null
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vectors = null
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[system]
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gpu_allocator = "pytorch"
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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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[components]
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[components.transformer]
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factory = "transformer"
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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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tokenizer_config = {"use_fast": true}
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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.ner]
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factory = "ner"
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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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[components.ner.model.tok2vec.pooling]
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@layers = "reduce_mean.v1"
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[corpora]
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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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[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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[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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[training.optimizer]
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@optimizers = "Adam.v1"
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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 = 5e-5
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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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[initialize]
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vectors = ${paths.vectors} |