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eda07efaa5
* Add more token classification examples * POS tagging example * Phrase chunking example * PR review fixes * Add conllu to third party list (used in token classification examples)
34 lines
1.3 KiB
Bash
Executable File
34 lines
1.3 KiB
Bash
Executable File
curl -L 'https://sites.google.com/site/germeval2014ner/data/NER-de-train.tsv?attredirects=0&d=1' \
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| grep -v "^#" | cut -f 2,3 | tr '\t' ' ' > train.txt.tmp
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curl -L 'https://sites.google.com/site/germeval2014ner/data/NER-de-dev.tsv?attredirects=0&d=1' \
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| grep -v "^#" | cut -f 2,3 | tr '\t' ' ' > dev.txt.tmp
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curl -L 'https://sites.google.com/site/germeval2014ner/data/NER-de-test.tsv?attredirects=0&d=1' \
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| grep -v "^#" | cut -f 2,3 | tr '\t' ' ' > test.txt.tmp
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export MAX_LENGTH=128
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export BERT_MODEL=bert-base-multilingual-cased
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python3 scripts/preprocess.py train.txt.tmp $BERT_MODEL $MAX_LENGTH > train.txt
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python3 scripts/preprocess.py dev.txt.tmp $BERT_MODEL $MAX_LENGTH > dev.txt
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python3 scripts/preprocess.py test.txt.tmp $BERT_MODEL $MAX_LENGTH > test.txt
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cat train.txt dev.txt test.txt | cut -d " " -f 2 | grep -v "^$"| sort | uniq > labels.txt
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export OUTPUT_DIR=germeval-model
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export BATCH_SIZE=32
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export NUM_EPOCHS=3
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export SAVE_STEPS=750
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export SEED=1
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python3 run_ner.py \
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--task_type NER \
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--data_dir . \
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--labels ./labels.txt \
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--model_name_or_path $BERT_MODEL \
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--output_dir $OUTPUT_DIR \
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--max_seq_length $MAX_LENGTH \
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--num_train_epochs $NUM_EPOCHS \
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--per_gpu_train_batch_size $BATCH_SIZE \
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--save_steps $SAVE_STEPS \
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--seed $SEED \
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--do_train \
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--do_eval \
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--do_predict
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