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project.yml
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project.yml
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title: "Finnish model"
description: "Train spaCy model for Finnish on UD Finnish TDT"
vars:
vector_size: 50000
vector_dim: 300
max_texts: 4000000
texts_per_batch: 250000
minn: 4
maxn: 5
max_steps: 20000
pretrain_max_steps: 30
pretrain_max_texts: 200000
treebank: "UD_Finnish-TDT"
corpus_ner: "turku-one"
train_name: "fi_tdt-ud-train"
dev_name: "fi_tdt-ud-dev"
test_name: "fi_tdt-ud-test"
n_threads: 4
gpu_id: -1
floret_epochs: 5
floret_min_count: 200
directories: ["assets", "corpus", "data", "metrics", "training"]
assets:
- dest: "assets/${vars.treebank}"
git:
repo: "https://github.com/UniversalDependencies/${vars.treebank}"
branch: "r2.11"
path: ""
- dest: "assets/${vars.corpus_ner}"
git:
repo: "https://github.com/TurkuNLP/turku-one.git"
branch: "main"
path: ""
workflows:
floret-vectors:
- download-mc4-fi
- train-floret-mc4
pretrain:
- download-mc4-fi
- count-word-frequencies
- init-lexdata
- init-floret-vectors
- convert-mc4-jsonl
- pretrain-mc4
train-pipeline:
- download-mc4-fi
- count-word-frequencies
- init-lexdata
- init-floret-vectors
- convert
- convert-ner
- train
- train-ner
- merge-parser-and-ner
- functional-tests
- evaluate
commands:
- name: "download-mc4-fi"
help: "Download a subset of the MC4 corpus"
script:
- "rm -rf corpus/mc4/raw/"
- "mkdir -p corpus/mc4/raw"
- "python -m tools.download_huggingface allenai/c4 fi ${vars.max_texts} ${vars.texts_per_batch} corpus/mc4/raw"
outputs:
- "corpus/mc4/raw"
- name: "train-floret-mc4"
help: "Train floret vectors on the MC4 corpus"
script:
- "rm -rf corpus/mc4/tokenized/"
- "mkdir -p corpus/mc4/tokenized"
- "python -m tools.tokenize_fi --threads ${vars.n_threads} corpus/mc4/raw/ corpus/mc4/tokenized"
- "tools/merge_text_batches.sh corpus/mc4/tokenized/ corpus/mc4/tokenized/merged"
- "floret cbow -mode floret -hashCount 2 -bucket ${vars.vector_size} -minn ${vars.minn} -maxn ${vars.maxn} -minCount ${vars.floret_min_count} -dim ${vars.vector_dim} -neg 10 -epoch ${vars.floret_epochs} -thread ${vars.n_threads} -input corpus/mc4/tokenized/merged -output vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}"
- "gzip -f vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}.floret"
- "rm -rf corpus/mc4/tokenized/"
deps:
- "corpus/mc4/raw"
outputs:
- "vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}.floret.gz"
- name: "convert-mc4-jsonl"
help: "Convert the MC4 corpus to JSONL format"
script:
- "tools/raw_text_to_jsonl.sh corpus/mc4/raw corpus/mc4/mc4_${vars.pretrain_max_texts}.jsonl ${vars.pretrain_max_texts}"
deps:
- "corpus/mc4/raw"
outputs:
- "corpus/mc4/mc4_${vars.pretrain_max_texts}.jsonl"
- name: "pretrain-mc4"
help: "Pretrain the tok2vec component"
script:
- "rm -rf training/pretrain"
- "mkdir -p training/pretrain"
- "python -m spacy pretrain configs/fi.cfg training/pretrain --code fi/fi.py --paths.pretrain corpus/mc4/mc4_${vars.pretrain_max_texts}.jsonl --paths.vectors data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret --paths.vocab_lookups data/vocab/lookups --pretraining.max_epochs ${vars.pretrain_max_steps} --gpu-id ${vars.gpu_id}"
- "cp training/pretrain/model${vars.pretrain_max_steps}.bin pretrain/weights.bin"
deps:
- "configs/fi.cfg"
- "corpus/mc4/mc4_${vars.pretrain_max_texts}.jsonl"
- "data/vocab/lookups/lexeme_prob.json"
- "data/vocab/lookups/lexeme_settings.json"
- "data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret"
outputs:
- "pretrain/weights.bin"
- name: "count-word-frequencies"
script:
- "mkdir -p data/word_frequencies"
- "tools/frequencies.sh corpus/mc4/raw data/word_frequencies/finnish_vocab.txt.gz"
deps:
- "corpus/mc4/raw"
outputs:
- "data/word_frequencies/finnish_vocab.txt.gz"
- name: "init-lexdata"
script:
- "mkdir -p data/vocab/lookups"
- "python -m tools.create_lexdata data/word_frequencies/finnish_vocab.txt.gz data/vocab/lookups 500000"
deps:
- "data/word_frequencies/finnish_vocab.txt.gz"
outputs:
- "data/vocab/lookups/lexeme_prob.json"
- "data/vocab/lookups/lexeme_settings.json"
- name: "init-floret-vectors"
help: "Create floret embeddings"
script:
- "mkdir -p data/vectors"
- "python -m spacy init vectors fi vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}.floret.gz data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret --mode floret --name fi_web_floret.vectors"
deps:
- "vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}.floret.gz"
outputs:
- "data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret"
- name: "convert"
help: "Convert the data to spaCy's format"
script:
- "mkdir -p corpus/${vars.treebank}/preprocessed corpus/${vars.treebank}/spacy"
- "python tools/preprocess_UD-TDT.py --trainset assets/${vars.treebank}/${vars.train_name}.conllu corpus/${vars.treebank}/preprocessed/${vars.train_name}.conllu"
- "python -m spacy convert corpus/${vars.treebank}/preprocessed/${vars.train_name}.conllu corpus/${vars.treebank}/spacy --n-sents 6"
- "mv corpus/${vars.treebank}/spacy/${vars.train_name}.spacy corpus/${vars.treebank}/spacy/train.spacy"
- "python tools/preprocess_UD-TDT.py assets/${vars.treebank}/${vars.dev_name}.conllu corpus/${vars.treebank}/preprocessed/${vars.dev_name}.conllu"
- "python -m spacy convert corpus/${vars.treebank}/preprocessed/${vars.dev_name}.conllu corpus/${vars.treebank}/spacy --n-sents 6"
- "mv corpus/${vars.treebank}/spacy/${vars.dev_name}.spacy corpus/${vars.treebank}/spacy/dev.spacy"
- "python tools/preprocess_UD-TDT.py assets/${vars.treebank}/${vars.test_name}.conllu corpus/${vars.treebank}/preprocessed/${vars.test_name}.conllu"
- "python -m spacy convert corpus/${vars.treebank}/preprocessed/${vars.test_name}.conllu corpus/${vars.treebank}/spacy --n-sents 6"
- "mv corpus/${vars.treebank}/spacy/${vars.test_name}.spacy corpus/${vars.treebank}/spacy/test.spacy"
deps:
- "assets/${vars.treebank}/"
outputs:
- "corpus/${vars.treebank}/spacy/train.spacy"
- "corpus/${vars.treebank}/spacy/dev.spacy"
- "corpus/${vars.treebank}/spacy/test.spacy"
- name: "train"
help: "Train the model"
script:
- "python -m spacy train configs/fi.cfg --output training/${vars.treebank}/ --paths.train corpus/${vars.treebank}/spacy/train.spacy --paths.dev corpus/${vars.treebank}/spacy/dev.spacy --paths.init_tok2vec pretrain/weights.bin --paths.vectors data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret --paths.vocab_lookups data/vocab/lookups --code fi/fi.py --gpu-id ${vars.gpu_id} --training.max_steps ${vars.max_steps}"
deps:
- "configs/fi.cfg"
- "corpus/${vars.treebank}/spacy/train.spacy"
- "corpus/${vars.treebank}/spacy/dev.spacy"
- "pretrain/weights.bin"
- "data/vocab/lookups/lexeme_prob.json"
- "data/vocab/lookups/lexeme_settings.json"
- "data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret"
outputs:
- "training/${vars.treebank}/model-best"
- name: "convert-ner"
help: "Convert the NER corpus to spaCy's format"
script:
- "mkdir -p corpus/${vars.corpus_ner}/spacy"
- "python -m spacy convert assets/${vars.corpus_ner}/data/conll/train.tsv corpus/${vars.corpus_ner}/spacy --converter ner --n-sents 10"
- "python -m spacy convert assets/${vars.corpus_ner}/data/conll/dev.tsv corpus/${vars.corpus_ner}/spacy --converter ner --n-sents 10"
- "python -m spacy convert assets/${vars.corpus_ner}/data/conll/test.tsv corpus/${vars.corpus_ner}/spacy --converter ner --n-sents 10"
deps:
- "assets/${vars.corpus_ner}/"
outputs:
- "corpus/${vars.corpus_ner}/spacy/train.spacy"
- "corpus/${vars.corpus_ner}/spacy/dev.spacy"
- "corpus/${vars.corpus_ner}/spacy/test.spacy"
- name: "train-ner"
help: "Train the NER model"
script:
- "python -m spacy train configs/fi-ner.cfg --output training/${vars.corpus_ner}/ --paths.train corpus/${vars.corpus_ner}/spacy/train.spacy --paths.dev corpus/${vars.corpus_ner}/spacy/dev.spacy --paths.init_tok2vec pretrain/weights.bin --paths.vectors data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret --paths.vocab_lookups data/vocab/lookups --code fi/fi.py --gpu-id ${vars.gpu_id} --training.max_steps ${vars.max_steps}"
deps:
- "configs/fi-ner.cfg"
- "corpus/${vars.corpus_ner}/spacy/train.spacy"
- "corpus/${vars.corpus_ner}/spacy/dev.spacy"
- "pretrain/weights.bin"
- "data/vocab/lookups/lexeme_prob.json"
- "data/vocab/lookups/lexeme_settings.json"
- "data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret"
outputs:
- "training/${vars.corpus_ner}/model-best"
- name: "merge-parser-and-ner"
help: "Merge the parser and NER models into one model"
script:
- "spacy assemble configs/merged.cfg training/merged --paths.init_tok2vec pretrain/weights.bin --paths.vectors data/vectors/fi-${vars.vector_dim}-${vars.vector_size}-minn${vars.minn}-maxn${vars.maxn}-floret --paths.vocab_lookups data/vocab/lookups --code fi/fi.py"
deps:
- "training/${vars.treebank}/model-best"
- "training/${vars.corpus_ner}/model-best"
outputs:
- "training/merged"
- name: "functional-tests"
help: "Run functional tests to check that all capabilities are include in the trained model"
script:
- "python -m pytest tests/functional"
deps:
- "training/merged"
- name: "evaluate"
help: "Evaluate the full model"
script:
- "mkdir -p metrics/${vars.treebank}"
- "mkdir -p metrics/${vars.corpus_ner}"
- "python -m spacy evaluate training/merged corpus/${vars.treebank}/spacy/dev.spacy --output metrics/${vars.treebank}/dev.json --code fi/fi.py --gpu-id ${vars.gpu_id}"
- "python -m spacy evaluate training/merged corpus/${vars.treebank}/spacy/test.spacy --output metrics/${vars.treebank}/test.json --code fi/fi.py --gpu-id ${vars.gpu_id}"
- "python -m spacy evaluate training/merged corpus/${vars.corpus_ner}/spacy/dev.spacy --output metrics/${vars.corpus_ner}/dev.json --code fi/fi.py --gpu-id ${vars.gpu_id}"
- "python -m spacy evaluate training/merged corpus/${vars.corpus_ner}/spacy/test.spacy --output metrics/${vars.corpus_ner}/test.json --code fi/fi.py --gpu-id ${vars.gpu_id}"
deps:
- "corpus/${vars.treebank}/spacy/dev.spacy"
- "corpus/${vars.treebank}/spacy/test.spacy"
- "corpus/${vars.corpus_ner}/spacy/dev.spacy"
- "corpus/${vars.corpus_ner}/spacy/test.spacy"
- "training/merged/meta.json"
outputs:
- "metrics/${vars.corpus_ner}/dev.json"
- "metrics/${vars.corpus_ner}/test.json"